Trends in the earnings gender gap among dentists,physicians, and lawyers

Background

The authors examined the factors associated with sex differences in earnings for 3 professional occupations.

Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning

Humans are capable of acquiring multiple types of information presented in the same information stream. It has been suggested that at least two parallel learning processes are important during learning of sequential patterns—statistical learning and rule‐based learning. Yet, the neurophysiological underpinnings of these parallel learning processes are not fully understood. To differentiate between the simultaneous mechanisms at the single trial level, we apply a temporal EEG signal decomposition approach together with sLORETA source localization method to delineate whether distinct statistical and rule‐based learning codes can be distinguished in EEG data and can be related to distinct functional neuroanatomical structures. We demonstrate that concomitant but distinct aspects of information coded in the N2 time window play a role in these mechanisms: mismatch detection and response control underlie statistical learning and rule‐based learning, respectively, albeit with different levels of time‐sensitivity. Moreover, the effects of the two learning mechanisms in the different temporally decomposed clusters of neural activity also differed from each other in neural sources. Importantly, the right inferior frontal cortex (BA44) was specifically implicated in visuomotor statistical learning, confirming its role in the acquisition of transitional probabilities. In contrast, visuomotor rule‐based learning was associated with the prefrontal gyrus (BA6). The results show how simultaneous learning mechanisms operate at the neurophysiological level and are orchestrated by distinct prefrontal cortical areas. The current findings deepen our understanding on the mechanisms of how humans are capable of learning multiple types of information from the same stimulus stream in a parallel fashion.     

Glass‐Transition‐, Melting‐, and Decomposition Temperatures of Tailored Polyacrylates and Polymethacrylates: General Trends and Structure–Property Relationships

The glass‐transition‐, melting, and onset decomposition temperatures of a series of tailored polymethacrylates and polyacrylates are systematically investigated. Application fields of the investigated polymers include coatings, adhesives, textile, paper, cosmetics, electronics, lubricants, fuel additives, and oil‐field or construction chemicals. The present study focuses on linear alkyl, branched alkyl, and amino, as well as ether polymethacrylates and polyacrylates. Novel polymers are introduced with branched C9, C13, C17, and C21 ester, Lupragen, or glyco­pyranoside ester groups. The thermal characteristics of the novel polymers are analyzed and placed into the context of the thermal data of known polymers fitting into the homologous series. General trends providing a comprehensive and concise overview of the determined thermal properties are derived. Structure–property relationships are established and a detailed physicochemical rationale is provided. The study may even allow for a rapid empirical estimation of thermal data of not yet assessed polymer systems.

     

Preservation of Bacterial DNA by Human Dentin

Introduction

The capacity of dentin and collagen to bind DNA and protect against spontaneous and nuclease-induced degradation was evaluated individually and by the incubation of DNA with nuclease-producing bacteria in a mixed culture.

Methods

Extracted Fusobacterium nucleatum DNA was incubated with dentin shavings or collagen for 90 minutes. The DNA-bound substrates were incubated in different media (water, sera, and DNase I) for up to 3 months. Amplifiable DNA was released from dentin using EDTA,or from collagen using proteinase K, and evaluated by polymerase chain reaction (PCR). The stability of dentin-bound DNA was also assessed in a mixed culture (Parvimonas micra and Pseudoramibacter alactolyticus) containing a DNase-producing species, Prevotella intermedia. Samples were analyzed for amplifiable DNA.

Results

In water, dentin-bound DNA was recoverable by PCR at 3 months compared with no detectable DNA after 4 weeks in controls (no dentin). DNA bound to collagen was detectable by PCR after 3 months of incubation in water. In 10% human sera, amplifiable DNA was detectable at 3 months when dentin bound and in controls (no dentin). In mixed bacterial culture, dentin-bound DNA was recoverable throughout the experimental period (3 months), compared with no recoverable F. nucleatum DNA within 24 hours in controls (no dentin).

Conclusions

There is a strong binding affinity between DNA and dentin, and between DNA and serum proteins or collagen. These substrates preserve DNA against natural decomposition and protect DNA from nuclease activity, factors that may confound molecular analysis of the endodontic microbiota yet favor paleomicrobiological studies of ancient DNA.     

Phase-Field Modeling of Chemoelastic Binodal/Spinodal Relations and Solute Segregation to Defects in Binary Alloys

Microscopic phase-field chemomechanics (MPFCM) is employed in the current work to model solute segregation, dislocation-solute interaction, spinodal decomposition, and precipitate formation, at straight dislocations and configurations of these in a model binary solid alloy. In particular, (i) a single static edge dipole, (ii) arrays of static dipoles forming low-angle tilt (edge) and twist (screw) grain boundaries, as well as at (iii) a moving (gliding) edge dipole, are considered. In the first part of the work, MPFCM is formulated for such an alloy. Central here is the MPFCM model for the alloy free energy, which includes chemical, dislocation, and lattice (elastic), contributions. The solute concentration-dependence of the latter due to solute lattice misfit results in a strong elastic influence on the binodal (i.e., coexistence) and spinodal behavior of the alloy. In addition, MPFCM-based modeling of energy storage couples the thermodynamic forces driving (Cottrell and Suzuki) solute segregation, precipitate formation and dislocation glide. As implied by the simulation results for edge dislocation dipoles and their configurations, there is a competition between (i) Cottrell segregation to dislocations resulting in a uniform solute distribution along the line, and (ii) destabilization of this distribution due to low-dimensional spinodal decomposition when the segregated solute content at the line exceeds the spinodal value locally, i.e., at and along the dislocation line. Due to the completely different stress field of the screw dislocation configuration in the twist boundary, the segregated solute distribution is immediately unstable and decomposes into precipitates from the start.     

Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters

Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic–intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise.Cells transduce extracellular information through signal transduction pathways that often exhibit complex nonlinear behaviors. Commonly, receptor–ligand interactions initiate signals that diverge into parallel pathways and then converge onto common downstream elements. These branches can have different dose dependencies creating complicated dose–response characteristics, including biphasic properties (1–3). In such systems, the complexity of the network creates difficulty in identifying the sources of cell response variability, even if the topology is known. However, despite the challenges, characterizing the fidelity of biochemical networks could help identify new biochemical noise regulation mechanisms that would further our understanding of cellular decision-making processes (4). Therefore, although biological noise at the gene expression level is relatively well characterized (5–11), to fully understand the origins of cell decision heterogeneity we require novel experimental and mathematical methods to quantify signaling pathway noise.Prior efforts to understand biochemical noise have primarily focused on the utilization of the equivalent dual-reporter technique. This method involves the single-cell measurement of two distinguishable fluorescent reporter proteins under statistically equivalent conditions (e.g., identical promoters, equivalent integration sites, etc.; Fig. 1A) (8, 9, 12). The lack of correlation between reporter expression within a cell is thought to result from stochastic chemical kinetics that randomly and independently affect both reporters, and is referred to as intrinsic noise. The remaining reporter variability originates from the factors that simultaneously affect both reporters equally within an individual cell but vary from cell to cell, and is referred to as extrinsic noise. The extrinsic factors can include the expression levels of RNA polymerase, ribosome number, cell size, or cell cycle stage, all thought to affect both reporters similarly within a cell. The advantage of the equivalent dual-reporter method is the separation of intrinsic noise from extrinsic noise in an experimentally measurable way. This method has been extended to analyze signaling networks; however, it requires simultaneous measurement of two reporters per signaling node of interest (13). This can quickly become experimentally intractable as the system size increases.Open in a separate windowFig. 1.(A) Schematic of the equivalent dual-reporter method. Two genes that encode for two distinguishable and statistically equivalent fluorescent reporters (X and Y) can conceptually be reformulated as a four-node branch motif. S can represent the cellular genetic background, L can represent the overall activity of the gene expression machinery in a given cell, and X and Y can represent the expression levels of the reporters. Thus, extrinsic noise is introduced in the segment S → L, and intrinsic noise is introduced in the segments downstream of L. (B) Simulated results for the reporters given in A. Each point corresponds to the expression level of both reporters in a single cell. Extrinsic noise causes points to spread out along the diagonal Y = X whereas intrinsic noise causes the points to additionally spread out in the direction orthogonal to this line. For an isotropic interpretation see Fig. S1. (C) A region of interest (ROI, dashed rectangle) for decomposition is selected from a larger complex intracellular signaling system. The components within the ROI can then be further simplified to a four-node motif comprising a ligand S that binds to its native receptor, which sends a signal to a signaling intermediary, the receptor complex L. The signal from S then propagates down two parallel branches to the readouts X and Y. We denote the factor that causes coordinated fluctuations in the reporters X and Y as the trunk noise, whereas the noise uniquely contributed by each branch is termed the branch noise. (D) Simulated results for individual cells expressing the readouts (X and Y) given in C under five input levels as denoted by the distinct colors. The means of the readout for each input level are indicated by the circles and fitted by regression to form a basis for decomposition. The trunk noise adds noise along the basis, and each branch noise will add noise parallel to its corresponding axis and orthogonal to the axis associated with the other branch.Expanding on the success of the equivalent dual-reporter method, nonequivalent dual reporters have found success characterizing sources of cell-to-cell variability. For instance, by comparing a reporter in a signaling pathway of interest to a reporter of a constitutively expressed gene, one can separate pathway-specific noise from general gene expression noise (14, 15). Alternatively, multiple reporters placed within a serial gene expression network can facilitate decomposition of the noise propagation (6). More recently, a single-reporter variation of the original dual-reporter method enabled the decomposition of the intrinsic noise into memory and stochastic terms based upon their separate timescales (16). However, the methods described above frequently use custom-designed networks whose structure is known a priori, which allows for the construction of a specific mathematical framework. Thus, although dual-reporter methods and its variations have yielded important scientific insights, these methods routinely require reporter genes to be inserted into cells which can hamper efforts to rapidly characterize a variety of signaling networks. Furthermore, these reporter methods are limited to the analysis of biological noise at the gene expression level. Therefore, despite substantial advances in the characterization of gene expression noise, we still lack tools needed to understand noise in intracellular signaling.Here, we present a mathematical generalization of the equivalent dual-reporter method that enables decomposition of signaling network noise using nonequivalent dual reporters. These reporters do not need to be genetically encoded, thus increasing the scope of systems that can be analyzed. Using this framework, we were able to quantify the relative noisiness of both the downstream mitogen activated protein kinase (MAPK) and NF-κB signaling pathways. We also show that this methodology can be used to identify previously unappreciated feedback mechanisms affecting both MAPK and NF-κB pathways. Overall, this methodology is revealing and experimentally facile to implement in a system where detailed knowledge of the topology is unavailable.     

Explaining Differentials in Subsidy Levels Among Hospital Ownership Types in Germany

German hospitals receive subsidies for investment costs by federal states. Theoretically, these subsidies have to cover the whole investment volume, but in fact, only 50–60% are covered. Balance sheet data show that public hospitals exhibit higher levels of subsidies compared with for‐profit hospitals. In this study, I examine the sources of this disparity by decomposing the differential in a so‐called facilitation ratio, that is, the ratio of subsidies to tangible fixed assets, revealing to which extent assets are funded by subsidies. The question of interest is whether the differential can be attributed to observable hospital‐specific and federal state‐specific characteristics or to unobservable factors. Copyright © 2016 John Wiley & Sons, Ltd