Mechanical Properties of High- and Low-Fusing Zirconia Veneering Ceramics Fired on Different Trays and Substrates.

This study aimed to evaluate the effect of ceramic type, firing tray, and firing substrate on the density, shrinkage, biaxial flexural strength, Martens' hardness, and elastic indentation modulus of zirconia veneering ceramics. Disk-shaped specimens were fabricated from a high-fusing (HFZ) and a low-fusing (STR) zirconia veneering ceramic. These specimens were then divided into 10 groups according to firing trays (round, small honeycomb-shaped, cordierite [RSC]; round, large honeycomb-shaped, aluminum oxide [RLA]; rectangular, plane, silicon nitride [RCPS]; round, plane, silicon nitride [RPS]; and rectangular, plane, calcium silicate [RCPC]) and firing substrates (firing cotton and platinum foil) used (n = 12). The density, shrinkage, biaxial flexural strength, Martens' hardness, and indentation modulus were measured, and analyzed with generalized linear model analysis (α = 0.05). The interaction between the ceramic type and firing substrate affected density (p < 0.001), and the other outcomes were affected by the interaction among all main factors (p ≤ 0.045). Higher density was observed with HFZ or platinum foil (p ≤ 0.007). RSC and RLA led to a higher density than RCPS within HFZ and led to the lowest density within STR (p ≤ 0.046). STR had a higher shrinkage (p < 0.001). RSC mostly led to a lower shrinkage of HFZ (p ≤ 0.045). The effect of ceramic type and firing substrates on the biaxial flexural strength, Martens' hardness, and indentation modulus was minimal while there was no clear trend on the effect of firing tray on these properties. Ceramic type, firing tray, and firing substrate affected the mechanical properties of the tested zirconia veneering ceramics. Firing the tested zirconia veneering ceramics over a round and small honeycomb-shaped cordierite firing tray with firing cotton mostly led to improved mechanical properties.

Influence of additives and binder on the physical properties of dental silicate glass-ceramic feedstock for additive manufacturing.

OBJECTIVES: The aim of the study was to investigate the impact of organic additives (binder, plasticizer, and the cross-linking ink) in the formulation of water-based feedstocks on the properties of a dental feldspathic glass-ceramic material developed for the slurry-based additive manufacturing technology "LSD-print." MATERIAL AND METHODS: Three water-based feldspathic feedstocks were produced to study the effects of polyvinyl alcohol (AC1) and poly (sodium 4-styrenesulfonate) (AC2) as binder systems. A feedstock without organic additives was tested as the control group (CG). Disc-shaped (n = 15) and bar (n = 7) specimens were slip-cast and characterized in the green and fired states. In the green state, density and flexural strength were measured. In the fired state, density, shrinkage, flexural strength (FS), Weibull modulus, fracture toughness (KIC), Martens parameters, and microstructure were analyzed. Disc-shaped and bar specimens were also cut from commercially available CAD/CAM blocks and used as a target reference (TR) for the fired state. RESULTS: In the green state, CG showed the highest bulk density but the lowest FS, while the highest FS in the green state was achieved with the addition of a cross-linking ink. After firing, no significant differences in density and a similar microstructure were observed for all slip-cast groups, indicating that almost complete densification could be achieved. The CAD/CAM specimens showed the highest mean FS, Weibull modulus, and KIC, with significant differences between some of the slip-cast groups. SIGNIFICANCE: These results suggest that the investigated feedstocks are promising candidates for the slurry-based additive manufacturing of restorations meeting the class 1a requirements according to DIN EN ISO 6871:2019-01.

Fracture toughness, work of fracture, flexural strength and elastic modulus of 3D-printed denture base resins in two measurement environments after artificial aging.

OBJECTIVES: To investigate the fracture toughness (KIC), work of fracture (WOF), flexural strength (FS) and elastic modulus (E) of four additively manufactured denture base resins in two different measurement environments after artificial aging. METHODS: Rectangular specimens in two different dimensions (n = 480) were 3D-printed with four denture base resins: Denture 3D+ (DEN; NextDent), Fotodent Denture (FOT; Dreve ProDiMed), Freeprint Denture (FRE; Detax), V-Print dentbase (VPR; VOCO)). KIC, WOF, FS and E were measured after (1) water-storage (37 °C; KIC = 7 d; FS = 50 h); (2) water-storage + hydrothermal-aging (20 min, 0.2 MPa, 134 °C); (3) water storage + thermocycling (10,000 cycles, 5/55 °C) in two measurement environments (i) air-23 °C and (ii) water-37 °C. For FS, fracture types were classified, and relative frequencies determined. Univariate ANOVA, Kruskal-Wallis, Mann-Whitney U, and Spearman's correlation were calculated (p < 0.05, SPSS V.27.0). Weibull modulus (m) was calculated using the maximum likelihood estimation method. RESULTS: DEN showed the highest KIC (5/6 groups), WOF and highest corresponding m (1/6 groups), while FRE presented the highest FS (2/6 groups) and E values. Hydrothermal-aging and thermocycling reduced KIC and WOF, FS and E, and the number of FS fracture pieces. For 6/8 groups, hydrothermal aging resulted in lower FS than thermocycling. Measurement in air-23 °C led to higher FS for 7/12 groups and a more brittle fracture behavior. A positive correlation between KIC and FS was observed. SIGNIFICANCE: With measurements in air-23 °C resulting in higher FS than reported in water-37 °C, the measurement environment should be adapted to the clinical situation to allow valid predictions on the mechanical behavior of denture base resins when in situ.

Influence of different surface finishing procedures of strength-gradient multilayered zirconia crowns on two-body wear and fracture load: Lithium silicate or leucite glazing versus polishing?

OBJECTIVES: To examine the influence of different finishing procedures on the surface roughness, wear resistance and fracture load of strength-gradient multilayered zirconia. MATERIALS AND METHODS: Zirconia crowns (Multilayer 3D pro; n = 96) were manufactured and treated with a lithium-silicate- (LISI_S), leucite-based glaze spray (LEU_S), leucite-based glaze mass (LEU_M) or polished (POL). Natural molars (CG; n = 24) acted as a control. Roughness was determined on flat glazed specimens (n = 28). Two-body wear was examined by digitalizing and matching the occlusal surface before and after thermo-mechanical aging (6,000 thermal and 1,200,000 chewing cycles). The groups were split to measure fracture load initially and after aging. Kolmogorov-Smirnov, Spearman correlation, Kruskal-Wallis-H, Levene's test, one-way ANOVA with Scheffé post-hoc and Weibull modulus were computed. RESULTS: POL presented the lowest and LEU_S the highest roughness. Following POL, no ceramic loss was observed. LISI_S, LEU_S and LEU_M showed lower ceramic wear than the CG. The lowest wear of the antagonist was observed for the CG. LISI_S showed a lower antagonistic wear than LEU_S, LEU_M and POL. LISI_S, LEU_S, LEU_M and POL showed higher fracture load values and Weibull moduli than the CG. Artificial aging did not impact the fracture load or Weibull moduli. SIGNIFICANCE: With glazed groups showing height losses closer to the CG, glazing should be preferred to polishing when approximating the wear behavior of a natural dentition. Finishing of monolithic zirconia by glazing with a lithium silicate-based spray is recommended to preserve the antagonists. All examined zirconia crowns presented sufficient mechanical properties to withstand masticatory forces, even after prolonged aging.

A New Implant System with Directly Screwed Supraconstructions: Impact of Restoration Material and Artificial Aging on the Bending Moment.

PURPOSE: To investigate the bending moment of implants restored with a directly screwed single-unit fixed dental prosthesis (FDP) compared to implants restored with an FDP polymerized to a titanium base before and after thermomechanical aging. MATERIALS AND METHODS: A total of 240 implants (120 with and 120 without a titanium base) were restored with FDPs manufactured from conventionally sintered 3Y-TZP, 5Y-TZP, 4Y-TZP, and CoCrMo, as well as high-speed sintered 4Y-TZP. Half the specimens per subgroup were aged using chewing simulation combined with thermocycling (1,200,000 cycles at 50 N; 6,000 cycles at 5° to 55°). Initial and aged fracture load were measured. The bending moment was calculated and subjected to statistical analysis (Kolmogorov-Smirnov test, one-way ANOVA followed by post hoc Scheffé, t, and chi-square tests; P < .05). Failure types were analyzed. RESULTS: Implants without a titanium base showed higher bending moments for all initially tested zirconia groups compared to implants with a titanium base. The highest initial values were observed for 4Y-TZP FDPs regardless of implant type. High-speed sintered FDPs demonstrated higher initial bending moments compared to conventionally sintered FDPs. Artificial aging led to a decrease of the bending moment in most subgroups. After aging, no differences were found within the restoration materials, sintering protocols, or implant types. Implant deformation occurred mainly with directly screwed FDPs, whereas FDP mobility was predominantly observed among implants with a titanium base. FDP fractures were mainly observed for 5Y-TZP. CONCLUSIONS: Both implant types exhibited similar values after aging. Thus, implants without a titanium base seem to show equally sufficient stability for clinical applications with all tested materials.

Dimensional Stability and Reproducibility of Varying FFF Models for Aligners in Comparison to Plaster Models.

To test the impact of FFF filaments, printing parameters, thermoforming foils, repeated thermoforming cycles, and type of jaw on the dimensional stability of FFF models for aligners and to compare them with plaster models, FFF models (maxilla, n = 48; mandible, n = 48) from two filaments (SIMPLEX aligner and Renfert PLA HT, both Renfert GmbH) were fabricated using four printing parameters (one, two, or three loops; four loops acted as the default) and conventional plaster models (n = 12) based on a young, female dentition. All models were thermoformed under pressure three times in total using two different thermoforming foils, namely 0.75 mm × 125 mm Ø aligner foil (CA Pro+ Clear Aligner, Scheu Dental) and 1.0 mm × 125 mm Ø Duran foil (Duran+, Scheu Dental). Aligner foil was heated at 220 °C for 25 s and Duran foil at 220 °C for 30 s. All models were scanned after fabrication as well as after each thermoforming cycle. The obtained STL datasets were analyzed using the local best-fit method (GOM Inspect Pro, Carl Zeiss Metrology GmbH). Data were analyzed using a Kolmogorov-Smirnov-test, a one-way ANOVA with post-hoc Scheffé, and a t-test (p < 0.05). The dimensional stability of the models was most strongly affected by the printing parameters (number of loops; ηp2 = 0.768, p < 0.001) followed by the thermoforming foil used (ηp2 = 0.663, p < 0.001) as well as the type of model (ηp2 = 0.588, p < 0.001). In addition, various interactions showed an influence on the dimensional stability (ηp2 = 0.041-0.386, p < 0.035). SIMPLEX maxillary models (default; four loops), thermoformed using aligner foil, showed higher deformation stability than did plaster models. These initial FFF models provide comparable precision to plaster models, but the dimensional stability of the FFF models, in contrast to that of plaster models, decreases with increasing numbers of thermoforming cycles.

Three-Dimensional Printed Resin: Impact of Different Cleaning Protocols on Degree of Conversion and Tensile Bond Strength to a Composite Resin Using Various Adhesive Systems.

The present investigation tested the effect of cleaning methods and adhesives on the tensile bond strength (TBS) of a resin-based composite luted to a temporary 3D printed resin. Substrates (n= 360) were printed using a Rapidshape D20II and cleaned with a butyldiglycol-based solution, isopropanol, or by centrifugation. Specimens were air-abraded with Al2O3 (mean particle size 50 µm) at 0.1 MPa followed by pretreatment (n = 30/subgroup) with: (1) Clearfil Ceramic Primer (CCP); (2) Clearfil Universal Bond (CUB); (3) Scotchbond Universal Plus (SUP) or 4. Visio.link (VL) and luted to PanaviaV5. TBS (n = 15/subgroup) was measured initially (24 h at 37 °C water) or after thermal cycling (10,000×, 5/55 °C). The degree of conversion (DC) for each cleaning method was determined prior and after air-abrasion. Univariate ANOVA followed by post-hoc Scheffé test was computed (p < 0.05). Using Ciba-Geigy tables and chi-square, failure types were analyzed. The DC values were >85% after all cleaning methods, with centrifugation showing the lowest. CCP pretreatment exhibited the lowest TBS values, with predominantly adhesive failures. The combination of CCP and centrifugation increased the TBS values (p < 0.001) compared to the chemical cleaning. CUB, SUP, and VL, regardless of cleaning, can increase the bond strength between the 3D printed resin and the conventional luting resin.

A new implant system with directly screwed supra-constructions: Impact of restoration material and artificial aging on the bending moment.

PURPOSE: To investigate the bending moment of implants restored with a directly screwed single-unit fixed dental prosthesis (FDP) compared to implants restored with an FDP polymerized to a titanium base before and after thermomechanical aging. MATERIALS AND METHODS: A total of 240 implants (120 with and 120 without a titanium base) were restored with FDPs manufactured from conventionally sintered 3Y-TZP, 5Y-TZP, 4Y-TZP, and CoCrMo, as well as high-speed sintered 4Y-TZP. Half of the specimens per subgroup were aged using chewing simulation combined with thermocycling (1,200,000 cycles at 50 N; 6,000 cycles at 5°C to 55°C). Initial and aged fracture load were measured. The bending moment was calculated and subjected to statistical analysis (Kolmogorov-Smirnov test, one-way ANOVA followed by post hoc Scheffé, t, and chi-square tests; P < .05). Failure types were analyzed. RESULTS: Implants without a titanium base showed higher bending moments for all initially tested zirconia groups compared to implants with a titanium base. The highest initial values were observed for 4Y-TZP FDPs regardless of implant type. High-speed sintered FDPs demonstrated higher initial bending moments compared to conventionally sintered FDPs. Artificial aging led to a decrease of the bending moment in most of the subgroups. After aging, no differences were found within the restoration materials, sintering protocols, or implant types. Implant deformation occurred mainly with directly screwed FDPs, whereas FDP mobility was predominantly observed among implants with a titanium base. FDP fractures were mainly observed for 5Y-TZP. CONCLUSION: Both implant types exhibited similar values after aging. Thus, implants without a titanium base seem to show equally sufficient stability for clinical applications with all tested materials.

Temporally Coherent Backmapping of Molecular Trajectories From Coarse-Grained to Atomistic Resolution.

Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampling molecular configurations of interest can be done efficiently using coarse-grained simulations, from which meaningful physicochemical information can be inferred if the corresponding all-atom configurations are reconstructed. However, this procedure of backmapping to reintroduce the lost atomistic detail into coarse-grain structures has proven a challenging task due to the many feasible atomistic configurations that can be associated with one coarse-grain structure. Existing backmapping methods are strictly frame-based, relying on either heuristics to replace coarse-grain particles with atomic fragments and subsequent relaxation or parametrized models to propose atomic coordinates separately and independently for each coarse-grain structure. These approaches neglect information from previous trajectory frames that is critical to ensuring temporal coherence of the backmapped trajectory, while also offering information potentially helpful to producing higher-fidelity atomic reconstructions. In this work, we present a deep learning-enabled data-driven approach for temporally coherent backmapping that explicitly incorporates information from preceding trajectory structures. Our method trains a conditional variational autoencoder to nondeterministically reconstruct atomistic detail conditioned on both the target coarse-grain configuration and the previously reconstructed atomistic configuration. We demonstrate our backmapping approach on two exemplar biomolecular systems: alanine dipeptide and the miniprotein chignolin. We show that our backmapped trajectories accurately recover the structural, thermodynamic, and kinetic properties of the atomistic trajectory data.

Bending moment of implants restored with CAD/CAM polymer-based restoration materials with or without a titanium base before and after artificial aging.

OBJECTIVES: To test and compare two types of implant systems restored with four monolithic polymer-based materials with regard to their bending moments (BM) before and after aging. METHODS: A total of 192 tissue-level implants (TRI Dental Implants) differing in the presence (TiB, Octa line, n = 96) or absence (NTiB, Matrix line, n = 96) of a titanium base were restored with mandibular right first molar crowns manufactured from composite (CC), polymer-infiltrated ceramic (VE), PMMA (PM) and a 3D printed resin (ND) (n = 24). Half of the specimens (n = 12) were loaded for 1,200,000 cycles (50 N, 1.3 Hz, TC: 5/55 °C, 6000×) and examined for failures. Fracture load was measured according to ISO standard 14801, BM was calculated, and fracture types were examined. Data were analyzed using parametric statistics (p < 0.05). RESULTS: No failures were observed after 600,000 cycles. After 1,200,000 cycles, wear traces were recorded in all groups except PM, VE and CC on TiB implants. In group CC on NTiB implants, three specimens were rated zero in BM testing as they showed fracture of the screw. Regarding BM, TiB implants exhibited higher values than NTiB implants with aged CC (p = 0.023), aged PM (p < 0.001), initial PM (p = 0.011) and initial VE (p < 0.001). No differences occurred among the implant types with initial CC, initial ND, aged ND and aged VE. With regard to initial BM values, NTiB implants showed higher values for ND and CC compared with PM and VE (p < 0.001). No differences in initial BM values were found for the tested materials on TiB implants (p > 0.116). When aged, restoration material had no impact on the BM values of NTiB implants (p ≥ 0.233). Aged TiB implants showed higher values in combination with CC than with ND (p = 0.001). PM and VE showed similar values as ND and CC. Artificial aging led to a decrease of BM within PM, CC and ND on NTiB implants and ND on TiB implants. The majority of failures after testing were characterized by crown fractures in two to four pieces. Fractures in more pieces with smaller fragments occurred primarily for ND. SIGNIFICANCE: The use of NTiB implants with the polymer-based materials tested can only be recommended for clinical use as interim prostheses. CC seems to show a positive effect on the BM. Clinical research investigating the in vivo behavior is necessary to confirm these findings.

An open-source drug discovery platform enables ultra-large virtual screens.

On average, an approved drug currently costs US$2-3 billion and takes more than 10 years to develop1. In part, this is due to expensive and time-consuming wet-laboratory experiments, poor initial hit compounds and the high attrition rates in the (pre-)clinical phases. Structure-based virtual screening has the potential to mitigate these problems. With structure-based virtual screening, the quality of the hits improves with the number of compounds screened2. However, despite the fact that large databases of compounds exist, the ability to carry out large-scale structure-based virtual screening on computer clusters in an accessible, efficient and flexible manner has remained difficult. Here we describe VirtualFlow, a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large libraries of compounds. VirtualFlow is able to use a variety of the most powerful docking programs. Using VirtualFlow, we prepared one of the largest and freely available ready-to-dock ligand libraries, with more than 1.4 billion commercially available molecules. To demonstrate the power of VirtualFlow, we screened more than 1 billion compounds and identified a set of structurally diverse molecules that bind to KEAP1 with submicromolar affinity. One of the lead inhibitors (iKeap1) engages KEAP1 with nanomolar affinity (dissociation constant (Kd) = 114 nM) and disrupts the interaction between KEAP1 and the transcription factor NRF2. This illustrates the potential of VirtualFlow to access vast regions of the chemical space and identify molecules that bind with high affinity to target proteins.

Variational selection of features for molecular kinetics.

The modeling of atomistic biomolecular simulations using kinetic models such as Markov state models (MSMs) has had many notable algorithmic advances in recent years. The variational principle has opened the door for a nearly fully automated toolkit for selecting models that predict the long time-scale kinetics from molecular dynamics simulations. However, one yet-unoptimized step of the pipeline involves choosing the features, or collective variables, from which the model should be constructed. In order to build intuitive models, these collective variables are often sought to be interpretable and familiar features, such as torsional angles or contact distances in a protein structure. However, previous approaches for evaluating the chosen features rely on constructing a full MSM, which in turn requires additional hyperparameters to be chosen, and hence leads to a computationally expensive framework. Here, we present a method to optimize the feature choice directly, without requiring the construction of the final kinetic model. We demonstrate our rigorous preprocessing algorithm on a canonical set of 12 fast-folding protein simulations and show that our procedure leads to more efficient model selection.

ReaDDy 2: Fast and flexible software framework for interacting-particle reaction dynamics.

Interacting-particle reaction dynamics (iPRD) combines the simulation of dynamical trajectories of interacting particles as in molecular dynamics (MD) simulations with reaction kinetics, in which particles appear, disappear, or change their type and interactions based on a set of reaction rules. This combination facilitates the simulation of reaction kinetics in crowded environments, involving complex molecular geometries such as polymers, and employing complex reaction mechanisms such as breaking and fusion of polymers. iPRD simulations are ideal to simulate the detailed spatiotemporal reaction mechanism in complex and dense environments, such as in signalling processes at cellular membranes, or in nano- to microscale chemical reactors. Here we introduce the iPRD software ReaDDy 2, which provides a Python interface in which the simulation environment, particle interactions and reaction rules can be conveniently defined and the simulation can be run, stored and analyzed. A C++ interface is available to enable deeper and more flexible interactions with the framework. The main computational work of ReaDDy 2 is done in hardware-specific simulation kernels. While the version introduced here provides single- and multi-threading CPU kernels, the architecture is ready to implement GPU and multi-node kernels. We demonstrate the efficiency and validity of ReaDDy 2 using several benchmark examples. ReaDDy 2 is available at the https://readdy.github.io/ website.

Reactive SINDy: Discovering governing reactions from concentration data.

The inner workings of a biological cell or a chemical reactor can be rationalized by the network of reactions, whose structure reveals the most important functional mechanisms. For complex systems, these reaction networks are not known a priori and cannot be efficiently computed with ab initio methods; therefore, an important goal is to estimate effective reaction networks from observations, such as time series of the main species. Reaction networks estimated with standard machine learning techniques such as least-squares regression may fit the observations but will typically contain spurious reactions. Here we extend the sparse identification of nonlinear dynamics (SINDy) method to vector-valued ansatz functions, each describing a particular reaction process. The resulting sparse tensor regression method "reactive SINDy" is able to estimate a parsimonious reaction network. We illustrate that a gene regulation network can be correctly estimated from observed time series.

PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models.

Markov (state) models (MSMs) and related models of molecular kinetics have recently received a surge of interest as they can systematically reconcile simulation data from either a few long or many short simulations and allow us to analyze the essential metastable structures, thermodynamics, and kinetics of the molecular system under investigation. However, the estimation, validation, and analysis of such models is far from trivial and involves sophisticated and often numerically sensitive methods. In this work we present the open-source Python package PyEMMA ( http://pyemma.org ) that provides accurate and efficient algorithms for kinetic model construction. PyEMMA can read all common molecular dynamics data formats, helps in the selection of input features, provides easy access to dimension reduction algorithms such as principal component analysis (PCA) and time-lagged independent component analysis (TICA) and clustering algorithms such as k-means, and contains estimators for MSMs, hidden Markov models, and several other models. Systematic model validation and error calculation methods are provided. PyEMMA offers a wealth of analysis functions such that the user can conveniently compute molecular observables of interest. We have derived a systematic and accurate way to coarse-grain MSMs to few states and to illustrate the structures of the metastable states of the system. Plotting functions to produce a manuscript-ready presentation of the results are available. In this work, we demonstrate the features of the software and show new methodological concepts and results produced by PyEMMA.

[Erythropoiesis stimulating agents]. / Wachstumsfaktoren - Erythropoetine.

Since the 90's, human erythropoietin is produced recombinantly and used clinically. There are various products from different suppliers, which differ primarily in their production but not in their half-life or effectiveness. 2001 genetically modified darbepoetin alpha was launched, which is characterized by an approximately three times longer half-life. A further extension of the half-life to 130 hours is achieved with the current continuous erythropoietin receptor activator (CERA), which therefore must be applied only once or twice a month. The indication for epoetin therapy is primarily for the symptomatic renal anemia and chemotherapy-associated anemia. Corrections of low hemoglobin levels in asymptomatic patients are not allowed. The generally recommended hemoglobin target range is 10-12 g/dl. Hb values > 13 g/dl should be avoided because they are associated with significant adverse effects and do not improve patient survival.

Short-term increase of glucose concentration in PDS results in extensive removal and high glycation level of vital proteins during continuous ambulatory peritoneal dialysis.

BACKGROUND: The effect of clearance of so-called middle- and high-molecular weight proteins on clinical outcome of patients treated by peritoneal dialysis is still a matter of debate. In our present study, we investigated the impact of short-time alteration of the glucose concentration and the osmolarity of the peritoneal dialysis solution (PDS) on protein removal. METHODS: Peritoneal dialysis liquids (PDL) were collected from 19 well-characterized continuous ambulatory peritoneal dialysis (CAPD) patients treated with two types of PDS: Baxter (n = 10) and Fresenius (n = 9). The patients were treated with two different glucose concentration of each PDS in 4-h cycles. The depletion of the six interfering high-abundant proteins from the PDL samples was performed with the Multiple Affinity Removal LC Column-Human 6. The resulting protein fractions were analysed by 2D gel electrophoresis, differential in gel electrophoresis, mass spectrometry and 2D western blot. RESULTS: Proteomics investigation of the PDL fractions after depletion allowed the identification of 198 polypeptides of 424 excised spots. These polypeptides equates to 48 non-redundant proteins. Comparative analyses of 2D gel electrophoresis protein pattern revealed a clear correlation between protein removal and PDS glucose concentration and osmolarity. An increase for 4 h in the PDS osmolarity (with 43-51 mosmol/L) resulted qualitatively in 18-23% more protein removal in PDL. Moreover, 2D western blot analyses of the protein glycation pattern showed that the short-time increase in PDS glucose concentration (45-50 mM) resulted in significant alteration of the advanced glycosylation end products (AGEs) pattern. CONCLUSIONS: The data presented in this study demonstrate a clear correlation between the short-time changes in glucose concentration and osmolarity of the PDS, and the augmentation of the protein removal and the appearance of AGEs during CAPD.