Splenic Micronodular T-Cell/Histiocyte-Rich Large B-Cell Lymphoma: The Corticosteroid Pretreatment Hypothesis

Splenic micronodular T-cell/histiocyte-rich large B-cell lymphoma (THRLBCL) is derived from diffuse large B-cell lymphoma N.O.S., perhaps with some affinity with nodal THRLBCL. Of note, in contrast with the latter, the only lymph nodes involved in association with the splenic micronodular pattern of the disease are the splenic hilar lymph nodes. The possibility that corticosteroids, when prescribed prior to splenectomy, cause histopathological and functional modulations, apoptosis, necrosis, tissue shrinkage, which may obscure the diagnostic morphological features of this variant lymphoma and cause an underdiagnosis of this condition. The indications for glucocorticoid therapy are either related to the lymphoma itself, or else to other comorbidities, like asthma and autoimmune disorders. We propose that patients with the splenic subset of the disease are likely to have been prescribed corticosteroids prior to histopathologic examination of the involved spleen, causing disparate morphologies. However, a reviewer might accidentally dismiss the corticosteroid pretreatment which is thus overlooked. Apoptosis, induced by corticosteroids, is hypothesized as the major mechanism initiating the histopathological and functional changes in the splenic micronodular variant of the lymphoma.

The role of bFGF in preventing the shrinkage of cardiac progenitor cell-engineered conduction tissue by downregulating α-SMA expression

AIMS

Engineered conduction tissues (ECTs) fabricated from cardiac progenitor cells (CPCs) and collagen sponges were precisely targeted for the treatment of atrioventricular conduction block in our previous studies. However, obvious shrinkage and deformation of ECTs was observed during in vitro culture. According to the literature, it can be speculated that basic fibroblast growth factor (bFGF) may downregulate alpha-smooth muscle actin (α-SMA) produced by CPCs to prevent the shrinkage of CPC-engineered conduction tissues.

MAIN METHODS

In this study, culture media with or without bFGF were used for both cell culture and 3D tissue construction. The expression of α-SMA and the size change of engineered tissue were analyzed to evaluate the feasibility of adding bFGF to regulate α-SMA expression and shrinkage of constructs. In addition, cardiac-specific examinations were performed to evaluate the effect of bFGF on cardiac tissue formation.

KEY FINDINGS

Supplementation with bFGF efficiently relieved shrinkage of engineered tissue by downregulating the expression of α-SMA at both the cellular and 3D tissue levels. Moreover, bFGF had a positive influence on cardiac tissue formation in terms of cell viability, tissue organization and electrical conduction velocity.

SIGNIFICANCE

This study provides a guide for both shape control and quality improvement of CPC-engineered cardiac tissues.

To tune or not to tune, a case study of ridge logistic regression in small or sparse datasets

BACKGROUND

For finite samples with binary outcomes penalized logistic regression such as ridge logistic regression has the potential of achieving smaller mean squared errors (MSE) of coefficients and predictions than maximum likelihood estimation. There is evidence, however, that ridge logistic regression can result in highly variable calibration slopes in small or sparse data situations.

METHODS

In this paper, we elaborate this issue further by performing a comprehensive simulation study, investigating the performance of ridge logistic regression in terms of coefficients and predictions and comparing it to Firth's correction that has been shown to perform well in low-dimensional settings. In addition to tuned ridge regression where the penalty strength is estimated from the data by minimizing some measure of the out-of-sample prediction error or information criterion, we also considered ridge regression with pre-specified degree of shrinkage. We included 'oracle' models in the simulation study in which the complexity parameter was chosen based on the true event probabilities (prediction oracle) or regression coefficients (explanation oracle) to demonstrate the capability of ridge regression if truth was known.

RESULTS

Performance of ridge regression strongly depends on the choice of complexity parameter. As shown in our simulation and illustrated by a data example, values optimized in small or sparse datasets are negatively correlated with optimal values and suffer from substantial variability which translates into large MSE of coefficients and large variability of calibration slopes. In contrast, in our simulations pre-specifying the degree of shrinkage prior to fitting led to accurate coefficients and predictions even in non-ideal settings such as encountered in the context of rare outcomes or sparse predictors.

CONCLUSIONS

Applying tuned ridge regression in small or sparse datasets is problematic as it results in unstable coefficients and predictions. In contrast, determining the degree of shrinkage according to some meaningful prior assumptions about true effects has the potential to reduce bias and stabilize the estimates.

The 'un-shrunk' partial correlation in Gaussian graphical models

BACKGROUND

In systems biology, it is important to reconstruct regulatory networks from quantitative molecular profiles. Gaussian graphical models (GGMs) are one of the most popular methods to this end. A GGM consists of nodes (representing the transcripts, metabolites or proteins) inter-connected by edges (reflecting their partial correlations). Learning the edges from quantitative molecular profiles is statistically challenging, as there are usually fewer samples than nodes ('high dimensional problem'). Shrinkage methods address this issue by learning a regularized GGM. However, it remains open to study how the shrinkage affects the final result and its interpretation.

RESULTS

We show that the shrinkage biases the partial correlation in a non-linear way. This bias does not only change the magnitudes of the partial correlations but also affects their order. Furthermore, it makes networks obtained from different experiments incomparable and hinders their biological interpretation. We propose a method, referred to as 'un-shrinking' the partial correlation, which corrects for this non-linear bias. Unlike traditional methods, which use a fixed shrinkage value, the new approach provides partial correlations that are closer to the actual (population) values and that are easier to interpret. This is demonstrated on two gene expression datasets from Escherichia coli and Mus musculus.

CONCLUSIONS

GGMs are popular undirected graphical models based on partial correlations. The application of GGMs to reconstruct regulatory networks is commonly performed using shrinkage to overcome the 'high-dimensional problem'. Besides it advantages, we have identified that the shrinkage introduces a non-linear bias in the partial correlations. Ignoring this type of effects caused by the shrinkage can obscure the interpretation of the network, and impede the validation of earlier reported results.

A SHRINKAGE PRINCIPLE FOR HEAVY-TAILED DATA: HIGH-DIMENSIONAL ROBUST LOW-RANK MATRIX RECOVERY

This paper introduces a simple principle for robust statistical inference via appropriate shrinkage on the data. This widens the scope of high-dimensional techniques, reducing the distributional conditions from sub-exponential or sub-Gaussian to more relaxed bounded second or fourth moment. As an illustration of this principle, we focus on robust estimation of the low-rank matrix Θ* from the trace regression model Y = Tr(Θ*⊤ X) + ϵ. It encompasses four popular problems: sparse linear model, compressed sensing, matrix completion and multi-task learning. We propose to apply the penalized least-squares approach to the appropriately truncated or shrunk data. Under only bounded 2+δ moment condition on the response, the proposed robust methodology yields an estimator that possesses the same statistical error rates as previous literature with sub-Gaussian errors. For sparse linear model and multi-task regression, we further allow the design to have only bounded fourth moment and obtain the same statistical rates. As a byproduct, we give a robust covariance estimator with concentration inequality and optimal rate of convergence in terms of the spectral norm, when the samples only bear bounded fourth moment. This result is of its own interest and importance. We reveal that under high dimensions, the sample covariance matrix is not optimal whereas our proposed robust covariance can achieve optimality. Extensive simulations are carried out to support the theories.

A morphovolumetric analysis of aneurysm sac evolution after elective endovascular abdominal aortic repair

OBJECTIVE

Abdominal aortic aneurysm (AAA) sac shrinkage after endovascular aortic repair (EVAR) has been regarded as positive marker of EVAR success durability. The purpose of this study was to describe the morphovolumetric changes of the AAA sac during follow-up after elective EVAR and to analyze sac shrinkage-related variables.

METHODS

This is a single-center, retrospective, observational cohort study from a tertiary referral university hospital. All patients treated with EVAR between January 2013 and December 2018 were identified. Inclusion criteria were elective EVAR for AAA, preoperative computed tomography angiography within 6 months before EVAR and at least one postoperative computed tomography angiography during the follow-up, using a standardized protocol. Aneurysm sac shrinkage was defined as diameter decrease of 1 cm or more, volume shrinkage threshold was identified by a 16% decrease compared with the preoperative value. Primary outcomes were early (≤30 days) and late survival, and freedom from aneurysm-related mortality (ARM), and aortic reintervention.

RESULTS

There were 149 of the 325 patients (45.8%) who met the inclusion criteria: 133 (89.3%) were male and 16 (10.7%) female. The mean age was 74 ± 7 years (range, 55-87 years); the median AAA diameter was 56 mm (interquartile range, 50.0-61.2 mm) and the median volume was 138.8 cm³ (range, 99.0-178.3 cm³). Primary technical success was achieved in 145 patients (97.3%). The in-hospital mortality rate was 1.3%. The median follow-up was 42 months (interquartile range, 22.5-58.0 months). Both AAA diameter and volume decreased (P = .001 and P = .035, respectively) compared with preoperative measurements. Diameter shrinkage was adjudicated in 27 patients (18.1%), volume shrinkage was observed in 42 patients (28.2%). A Cox regression analysis demonstrated an association between the AAA diameter shrinkage and the preoperative diameter (P = .002; hazard ratio, 1.03; 95% confidence interval [CI], 1.011-1.052). The presence of a persistent endoleak predicted the absence of volume shrinkage (P = .001; hazard ratio, 7.75; 95% CI, 2.282-26.291). The estimated freedom from ARM was 97.5 ± 1.0% (95% CI, 93-99) at 12 months, and 96 ± 2% (95% CI, 90-98) at both 36 and 60 months. Aortic reintervention during the follow-up period was necessary in 7 patients (4.7%). ARM was only observed in the group characterized by the concomitant absence of diameter and volume shrinkage.

CONCLUSIONS

Volumetric analysis showed to have higher sensitivity than the simple two-dimensional measurement of the diameter to study AAA sac changes after EVAR. Although no predictor was found to be associated with AAA volume shrinkage, ARM occurred only in the group of AAAs with the absence of volume shrinkage.

Myosin sensitivity to thermal denaturation explains differences in water loss and shrinkage during cooking in muscles of distinct fibre types

The effect of thermal protein denaturation on the structure and quality of muscles of different fibre types is not well understood. Unaged masseter (100% type I fibres) and cutaneous trunci (93% type II fibres) muscles (N = 10) were assessed for their characteristics, protein denaturation, cooking loss, Warner- Bratzler shear force (WBSF) and shrinkage after heating at 50 °C - 85 °C with a rate of 5 °C/ min. Raw masseter had a higher pH, collagen and water content, shorter sarcomere, comparable fibre diameter, and shorter and wider fragments upon homogenization, than cutaneous trunci. In cutaneous trunci, at 55 °C - 60 °C, the lower transition temperature of myosin and the greater cumulative enthalpy resulted in greater cooking loss in muscle cuboids, and greater transverse, longitudinal and volume shrinkage in fibres and fibre fragments, than in masseter. Protein denaturation explained 71% variability in fibre fragment volume and 58% in cooking loss of both muscles, as well as 47% variability in WBSF of masseter.

Penalization and shrinkage methods produced unreliable clinical prediction models especially when sample size was small

OBJECTIVES

When developing a clinical prediction model, penalization techniques are recommended to address overfitting, as they shrink predictor effect estimates toward the null and reduce mean-square prediction error in new individuals. However, shrinkage and penalty terms ('tuning parameters') are estimated with uncertainty from the development data set. We examined the magnitude of this uncertainty and the subsequent impact on prediction model performance.

STUDY DESIGN AND SETTING

This study comprises applied examples and a simulation study of the following methods: uniform shrinkage (estimated via a closed-form solution or bootstrapping), ridge regression, the lasso, and elastic net.

RESULTS

In a particular model development data set, penalization methods can be unreliable because tuning parameters are estimated with large uncertainty. This is of most concern when development data sets have a small effective sample size and the model's Cox-Snell R2 is low. The problem can lead to considerable miscalibration of model predictions in new individuals.

CONCLUSION

Penalization methods are not a 'carte blanche'; they do not guarantee a reliable prediction model is developed. They are more unreliable when needed most (i.e., when overfitting may be large). We recommend they are best applied with large effective sample sizes, as identified from recent sample size calculations that aim to minimize the potential for model overfitting and precisely estimate key parameters.

Photopolymerization shrinkage-stress reduction in polymer-based dental restoratives by surface modification of fillers

OBJECTIVES

This research explores the use of polymer brushes for surface treatment of fillers used in polymer-based dental restoratives with focus on shrinkage stress reduction. The influence of interfacial reactive groups on shrinkage stress is explored.

METHODS

Oligomers of varying lengths and with varying number of reactive groups along the length were synthesized by modifying commercial oligomers. Surface of silica fillers (OX50) was treated with methylaminopropyltrimethoxysilane and this was further reacted with the synthesized oligomers to obtain a series of polymer brushes on the surface. Fillers modified with γ-methacryloxypropyltrimethoxysilane were used as a control. Filler surface treatment was confirmed using diffuse reflectance spectroscopy and thermogravimetric analysis. Fillers were added at 30 wt % to a resin made of BisGMA/TEGDMA and polymerization kinetics, shrinkage stress, volumetric shrinkage, flexural strength and modulus, viscosity were measured.

RESULTS

Composites with polymer brush functionalized fillers showed up to a 30 % reduction in shrinkage stress as compared to the control, with no reduction in flexural strength and modulus. Shrinkage stress reduced with increasing length of the polymer brush and increased with increase in number of reactive groups along the length of the polymer brush.

SIGNIFICANCE

The interface between inorganic fillers and an organic polymer matrix has been utilized to reduce shrinkage stress in a composite with no compromise in mechanical properties. This study gives insights into the stress development mechanism at the interface.

Shrinkage of specimens after CO2 laser cordectomy: an objective intraoperative evaluation

PURPOSE

The margin status after CO₂ laser cordectomy for glottic carcinoma may influence prognosis. There are no studies assessing the possible bias due to anatomic changes of the specimens for shrinkage. The authors evaluated the intraoperative shrinkage of specimens immediately after transoral CO₂ laser microsurgery (CO₂ TOLMS) to improve the understanding and the interpretation of surgical margins.

METHODS

This is a prospective study involving a consecutive cohort of 23 patients (19 males, 4 females, mean age 69.9 years, range 42-83 years) with early glottic carcinoma treated by CO₂ TOLMS from February 2017 to April 2019. The anteroposterior shrinkage of the specimen, of the tumor, and of the anterior and posterior margins was measured intraoperatively with a cross table reticle glass micrometer ruler, inserted into the eyepiece of the surgical microscope.

RESULTS

The mean shrinkage of the mucosal specimen from intralaryngeal measurement to post-resection measurement was 3.8 ± 0.3 mm, resulting in an average loss of 29% of the anteroposterior length (p < 0.01). The anteroposterior length of both the tumor and the margins after resection significantly decreased, but the shrinkage of the anterior and posterior margins was significantly greater than the shrinkage of the tumor (49% versus 20% and 45% versus 20%, p < 0.01).

CONCLUSION

The present study demonstrates significant shrinkage of specimens after CO₂ TOLMS, especially in the anteroposterior length of the vocal cords, and justifies the good oncological results for specimens with close and single positive superficial margins. Follow-up versus a second surgical look policy could be safely suggested in cases of close superficial and single positive superficial margins.

Using an added liquid to suppress drying defects in hard particle coatings

HYPOTHESIS

Lateral accumulation and film defects during drying of hard particle coatings is a common problem, typically solved using polymeric additives and surface active ingredients, which require further processing of the dried film. Capillary suspensions with their tunable physical properties, devoid of polymers, offer new pathways in producing uniform and defect free particulate coatings.

EXPERIMENTS

We investigated the effect of small amounts of secondary liquid on the coating's drying behavior. Stress build-up and weight loss in a temperature and humidity controlled drying chamber were simultaneously measured. Changes in the coating's reflectance and height profile over time were related with the weight loss and stress curve.

FINDINGS

Capillary suspensions dry uniformly without defects. Lateral drying is inhibited by the high yield stress, causing the coating to shrink to an even height. The bridges between particles prevent air invasion and extend the constant drying period. The liquid in the lower layers is transported to the interface via corner flow within surface pores, leading to a partially dry layer near the substrate while the pores above are still saturated. Using capillary suspensions for hard particle coatings results in more uniform, defect free films with better printing characteristics, rendering high additive content obsolete.

Evaluating drying feature differences between ginger slices and splits during microwave-vacuum drying by hyperspectral imaging technique

This study aimed to investigate the difference between ginger slices (vertically cut) and splits (horizontally cut) during microwave-vacuum drying (MVD) procedures. MVD ginger slices showed a higher shrinkage rate and a higher hardness value, with a more porous structure of the surface layer. MVD ginger splits had higher rehydration rates at the first 15 min of the rehydration. Nine optimal wavelengths were selected by regression coefficients (RC) from the partial least squares regression (PLSR) model based on the raw data. A simplified PLSR model based on optimal wavelengths showed a good performance with a coefficient of determination in prediction (Rp2) of 0.973 and a root mean square error in prediction (RMSEP) of 4.63%. Texture features of grey level co-occurrence matrix (GLCM) of moisture prediction maps demonstrated a more uniform moisture distribution in MVD ginger slices than that in splits in the original geometry.

Sacrificial 3D printing of shrinkable silicone elastomers for enhanced feature resolution in flexible tissue scaffolds

Silicone implants and scaffolds are emerging as potential replacement of flexible tissues, cosmetic and biomedical device implants due to their bioinert and flexible characteristics. The state-of-the-art direct-write silicone three-dimensional (3D) printers however cannot easily 3D print structures with sub-millimeter dimensions because of high viscosity and long curing times of their prepolymers. In the present study, a template-assisted 3D printing of ordered porous silicone constructs is demonstrated. The sacrificial molds were fabricated by low-cost and well-accessible material extrusion 3D printers. The 3D printed molds represent interconnected tortuous high specific surface area porous architectures based on triply periodic minimal surfaces (TPMS) in which the silicone prepolymer is cast and cured. We engineered silicone prepolymer with additives allowing on-demand structural shrinkage upon solvent treatment. This enabled 3D printing at a larger scale compatible with extrusion 3D printer resolution followed by isotropic shrinkage. This procedure led to a volumetric shrinkage of up to ~70% in a highly controllable manner. In this way, pore sizes in the order of 500-600 µm were obtained. The porous constructs were characterized with full strain recovery under extreme compressive deformations of up to 85% of the initial scaffold length. We further demonstrated the ability to infill cell-laden hydrogels such as gelatin methacryloyl (GelMA) into the interconnected pores while maintaining the cell viability of ~90%.

Bayesian sparse multiple regression for simultaneous rank reduction and variable selection

We develop a Bayesian methodology aimed at simultaneously estimating low-rank and row-sparse matrices in a high-dimensional multiple-response linear regression model. We consider a carefully devised shrinkage prior on the matrix of regression coefficients which obviates the need to specify a prior on the rank, and shrinks the regression matrix towards low-rank and row-sparse structures. We provide theoretical support to the proposed methodology by proving minimax optimality of the posterior mean under the prediction risk in ultra-high dimensional settings where the number of predictors can grow sub-exponentially relative to the sample size. A one-step post-processing scheme induced by group lasso penalties on the rows of the estimated coefficient matrix is proposed for variable selection, with default choices of tuning parameters. We additionally provide an estimate of the rank using a novel optimization function achieving dimension reduction in the covariate space. We exhibit the performance of the proposed methodology in an extensive simulation study and a real data example.

Modelling of moisture migration during convective drying of pineapple slice considering non-isotropic shrinkage and variable transport properties

The present work aims to develop a 3-dimensional finite element (FE) model to analyze moisture migration during drying of pineapple ring considering moisture dependent diffusion coefficient (D) and mass transfer coefficient (h_m) along with radial and longitudinal shrinkage. Pineapple rings were dried at 70 °C temperature and 0.6 m/s air velocity to study the moisture loss and shrinkage kinetics during drying. Thickness, outer radius and inner radius of hollow cylindrical pineapple slices were reduced by 79.3%, 32.2%, and 51.2%, respectively due to the occurrence of shrinkage during drying. Non-linear regression analysis showed the quadratic model to best fitted to the experimental moisture ratio data for explaining the shrinkage phenomenon in pineapple slice during drying. Shrinkage was accommodated into FE modelling using the arbitrary lagrange-eulerian method. Consideration of variable D showed better agreement with the experimental data than consideration of constant D, however constant and variable h_m predicted similar results. Incorporation of shrinkage phenomena during modelling led to prediction of more accurate result showing 0.06% deviation from experimental curve, but neglecting the shrinkage resulted in a 17% deviation. Hence, model developed with consideration of shrinkage along with variable D and h_m presented best fit with experimental drying curve. Developed model allowed the visualization of spatial moisture profile within the sample during drying, which would be useful for estimating the correct drying time, optimizing and designing of drying process.

Bis(4-methyl phenyl)iodonium as an alternative component to diphenyliodonium in camphorquinone-based ternary initiating systems

OBJECTIVE

To evaluate the influence of different co-initiators (diphenyliodonium hexafluorophosphate - DPI - and bis(4-methyl phenyl)iodonium hexafluorophosphate - BPI) on chemical and mechanical properties of resins.

METHODS

Nine experimental resins (50% Bis-GMA and 50% TEGDMA, w/w) with 60 wt% filler particles were formulated. The initiating system used was camphorquinone (CQ-1 mol%) and ethyl dimethylaminobenzoate (EDAB-2 mol%). Experimental groups were established according to DPI and BPI quantities (0.25, 0.5, 0.75, and 1 mol%). The control group was a resin containing only CQ-EDAB. Light transmission through the resin during polymerisation was analysed with a UV-vis spectrophotometer. Real-time polymerisation of the systems was evaluated using an FTIR spectrometer. Real-time polymerisation shrinkage strain was evaluated, and the flexural strength and modulus of materials were obtained by 3-point bending. Experimental groups were statistically analysed by Analysis of Variance and Tukey's test (α = 0.05). Dunnett's test was applied to compare experimental groups with control.

RESULTS

Light transmission rapidly increased initially for resins containing DPI or BPI. After 30 s cure, the irradiance on the lower surface of resin specimens was similar for all groups. After 10 s of light irradiation, groups containing DPI and BPI had higher conversion than the control. However, conversion after 120 s post-irradiation was similar for all groups. The rate of polymerisation, shrinkage strain, and the maximum strain rate were higher for groups containing DPI/BPI. The use of iodonium salts increased the flexural strength and flexural moduli of resins.

SIGNIFICANCE

DPI and BPI increased resin reactivity similarly. Increased rate of polymerization influenced light transmission through the resin in the first seconds of polymerisation and increased resin shrinkage and rate of shrinkage, as well as flexural strength and moduli.

State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues

BACKGROUND

How to select variables and identify functional forms for continuous variables is a key concern when creating a multivariable model. Ad hoc 'traditional' approaches to variable selection have been in use for at least 50 years. Similarly, methods for determining functional forms for continuous variables were first suggested many years ago. More recently, many alternative approaches to address these two challenges have been proposed, but knowledge of their properties and meaningful comparisons between them are scarce. To define a state of the art and to provide evidence-supported guidance to researchers who have only a basic level of statistical knowledge, many outstanding issues in multivariable modelling remain. Our main aims are to identify and illustrate such gaps in the literature and present them at a moderate technical level to the wide community of practitioners, researchers and students of statistics.

METHODS

We briefly discuss general issues in building descriptive regression models, strategies for variable selection, different ways of choosing functional forms for continuous variables and methods for combining the selection of variables and functions. We discuss two examples, taken from the medical literature, to illustrate problems in the practice of modelling.

RESULTS

Our overview revealed that there is not yet enough evidence on which to base recommendations for the selection of variables and functional forms in multivariable analysis. Such evidence may come from comparisons between alternative methods. In particular, we highlight seven important topics that require further investigation and make suggestions for the direction of further research.

CONCLUSIONS

Selection of variables and of functional forms are important topics in multivariable analysis. To define a state of the art and to provide evidence-supported guidance to researchers who have only a basic level of statistical knowledge, further comparative research is required.

Residual polymerization stresses in human premolars generated with Class II composite restorations

The objective of this study was to assess the influence of filling techniques on residual polymerization stresses in resin composite restorations of the tooth. Flat planes were ground in buccal enamel surfaces of extracted human premolars, followed by preparing Class II cavities. Indentation cracks were introduced in the planes and crack lengths were measured mesio-distally (x-direction) and cervico-incisally (y-direction). Cavities were filled with a resin composite and an adhesive using three methods; one with bulk filling and two with differing incremental filling techniques. The x- and y-tensile stresses were calculated from crack lengths measured repeatedly over 360 min after filling. Elastic modulus and polymerization shrinkage of the composite were also measured. Filling technique and time after fillings were statistically significant only for the y-stress. The incremental techniques generated smaller stresses than the bulk filling. The stresses developed for 60 min after filling, while the modulus and the shrinkage stopped developing within 10 min and 2 min after irradiation, respectively. The incremental technique, in which the proximal portion of the cavity was filled first, was effective in decreasing the residual tensile stress generated by the polymerization of resin composite.

Bayesian constraint relaxation

Prior information often takes the form of parameter constraints. Bayesian methods include such information through prior distributions having constrained support. By using posterior sampling algorithms, one can quantify uncertainty without relying on asymptotic approximations. However, sharply constrained priors are not necessary in some settings and tend to limit modelling scope to a narrow set of distributions that are tractable computationally. We propose to replace the sharp indicator function of the constraint with an exponential kernel, thereby creating a close-to-constrained neighbourhood within the Euclidean space in which the constrained subspace is embedded. This kernel decays with distance from the constrained space at a rate depending on a relaxation hyperparameter. By avoiding the sharp constraint, we enable use of off-the-shelf posterior sampling algorithms, such as Hamiltonian Monte Carlo, facilitating automatic computation in a broad range of models. We study the constrained and relaxed distributions under multiple settings and theoretically quantify their differences. Application of the method is illustrated through several novel modelling examples.

The quest for stable biomimetic repair of teeth: Technology of resin-bonded composites

The rationale leading to the present generation of resin composites is surveyed. There are many sub-classes such as flowable materials with specialized clinical indications. But a simplistic categorization of resin-composite materials is inappropriate. It is better to appreciate the factors that have driven recent developments. These include the search for low shrinkage composites and for greater depth of cure. Other necessary features are good handling behavior and sufficient strength for load-bearing situations. The esthetic challenge is for materials with superior and life-like optical properties and it is important to identify products that are good in every critical property. Nanotechnology has led to certain improvements, but the possibilities and limitations of nanoparticles must be appreciated. In all these developments, the structure and properties of the host tissues are a challenge and inspiration. Thus materials that can emulate the features of enamel and dentin are the goal of biomimetic design.

A Bayesian approach to Mendelian randomization with multiple pleiotropic variants

We propose a Bayesian approach to Mendelian randomization (MR), where instruments are allowed to exert pleiotropic (i.e. not mediated by the exposure) effects on the outcome. By having these effects represented in the model by unknown parameters, and by imposing a shrinkage prior distribution that assumes an unspecified subset of the effects to be zero, we obtain a proper posterior distribution for the causal effect of interest. This posterior can be sampled via Markov chain Monte Carlo methods of inference to obtain point and interval estimates. The model priors require a minimal input from the user. We explore the performance of our method by means of a simulation experiment. Our results show that the method is reasonably robust to the presence of directional pleiotropy and moderate correlation between the instruments. One section of the article elaborates the model to deal with two exposures, and illustrates the possibility of using MR to estimate direct and indirect effects in this situation. A main objective of the article is to create a basis for developments in MR that exploit the potential offered by a Bayesian approach to the problem, in relation with the possibility of incorporating external information in the prior, handling multiple sources of uncertainty, and flexibly elaborating the basic model.

Osmotic Treatment for Quantifying Cell Wall Elasticity in the Sepal of Arabidopsis thaliana

Elastic properties of the cell wall play a key role in regulating plant growth and morphogenesis; however, measuring them in vivo remains a challenge. Although several new methods have recently become available, they all have substantial drawbacks. Here we describe a detailed protocol for osmotic treatments, which is based on the idea of releasing the turgor pressure within the cell and measuring the resulting deformation. When placed in hyperosmotic solution, cells lose water via osmosis and shrink. Confocal images of the tissue, taken before and after this treatment, are quantified using high-resolution surface projections in MorphoGraphX. The cell shrinkage observed can then be used to estimate cell wall elasticity. This allows qualitative comparisons of cell wall properties within organs or between genotypes and can be combined with mechanical simulations to give quantitative estimates of the cells' Young's moduli. We use the abaxial sepal of Arabidopsis thaliana as an easily accessible model system to present our approach, but it can potentially be used on many other plant organs. The main challenges of this technique are choosing the optimal concentration of the hyperosmotic solution and producing high-quality confocal images (with cell walls visualized) good enough for segmentation in MorphoGraphX.

Effect of ultrasound and chemical pretreatment on drying characteristics and quality attributes of hot air dried pineapple slices

Drying of food materials is a time consuming activity making the process cost and energy intensive and hence, several pretreatments are used to improve the drying rate. The present study aims to study the effect of potassium metabisulphite (KMS solution, 0.25% w/v) and ultrasound (20 and 30 min) pretreatment on hot air drying characteristics and quality of pineapple slices. The results indicated that pretreated samples provided higher drying rate, enhanced moisture diffusivity, brighter color and lower hardness than that of untreated dried sample. It was observed that KMS and ultrasound pretreatment for 20 and 30 min reduced the drying time by 23.8%, 19% and 14.3%, respectively. Further, ten thin layer drying models were applied to the experimental drying data and logarithmic model was best fitted to explain the drying behavior of pretreated and untreated samples. Additionally, the effect of shrinkage on moisture transfer mechanism was also studied. Results highlighted that instantaneous moisture diffusivity was increased during drying while shrinkage was not accounted. However, shrinkage consideration reduced the average moisture diffusivity values by 72-83%. Overall color change (13.95 ± 0.92) and browning index (36.02 ± 2.45) were found to be lowest in ultrasound (30 min) pretreated dried sample, highlighting better color stability. Scanning electron microscopy presented noticeable effects of pretreatment on alterations of microstructure of pineapple slices. It can be interpreted that KMS pretreatment was found to be more effective for improvement of drying characteristics of pineapple slices as compared to ultrasound pretreatment.

Hybrid MRI guided radiotherapy in locally advanced cervical cancer: Case report of an innovative personalized therapeutic approach

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The case report of a patient affected by locally advanced cervical MRgRT is described.

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MRgRT appears to be feasible for cervical cancer and may improve treatment quality.

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MRgRT insights are discussed focusing on adaptive response and toxicity monitoring.