Drivers of diversification in freshwater gastropods vary over deep time.

Unravelling the drivers of species diversification through geological time is of crucial importance for our understanding of long-term evolutionary processes. Numerous studies have proposed different sets of biotic and abiotic controls of speciation and extinction rates, but typically they were inferred for a single, long geological time frame. However, whether the impact of biotic and abiotic controls on diversification changes over time is poorly understood. Here, we use a large fossil dataset, a multivariate birth-death model and a comprehensive set of biotic and abiotic predictors, including a new index to quantify tectonic complexity, to estimate the drivers of diversification for European freshwater gastropods over the past 100 Myr. The effects of these factors on origination and extinction are estimated across the entire time frame as well as within sequential time windows of 20 Myr each. Our results find support for temporal heterogeneity in the factors associated with changes in diversification rates. While the factors impacting speciation and extinction rates vary considerably over time, diversity-dependence and topography are consistently important. Our study highlights that a high level of heterogeneity in diversification rates is best captured by incorporating time-varying effects of biotic and abiotic factors.

[Management of joint empyema]. / Management von Gelenkempyemen.

Joint empyema, also known as septic arthritis, is a severe disease associated with considerable morbidity and mortality. Failing to initiate immediate treatment can result in irreversible joint destruction within a short time. The knee joint is most frequently involved, followed by the shoulder and hip joints. Small joints are rarely affected. Typical risk factors include immunosuppression, renal insufficiency, diabetes mellitus and previous joint interventions. An early targeted diagnostic work-up and initiation of therapeutic steps is crucial to avoid irreversible joint destruction. Joint aspiration for diagnostic purposes is essential and should be performed immediately when a septic arthritis is suspected. An important differential diagnosis is metabolic arthritis (gout and chondrocalcinosis), which typically presents in a similar way. A differentiation from septic arthritis is important as metabolic arthritis requires a completely different treatment. After confirming the diagnosis, treatment consisting of a surgical procedure combined with antibiotics is initiated. In most cases an arthroscopic intervention is sufficient. In severe cases the arthroscopy needs to be repeated. An arthrotomy must be carried out only rarely. A pre-emptive antibiotic treatment is initially administered and is later adjusted according to the resistogram. This article gives an overview on the pathophysiology, diagnostics and general management of joint empyema.

An Exploratory Study on the Complexity and Machine Learning Predictability of Stock Market Data.

This paper shows if and how the predictability and complexity of stock market data changed over the last half-century and what influence the M1 money supply has. We use three different machine learning algorithms, i.e., a stochastic gradient descent linear regression, a lasso regression, and an XGBoost tree regression, to test the predictability of two stock market indices, the Dow Jones Industrial Average and the NASDAQ (National Association of Securities Dealers Automated Quotations) Composite. In addition, all data under study are discussed in the context of a variety of measures of signal complexity. The results of this complexity analysis are then linked with the machine learning results to discover trends and correlations between predictability and complexity. Our results show a decrease in predictability and an increase in complexity for more recent years. We find a correlation between approximate entropy, sample entropy, and the predictability of the employed machine learning algorithms on the data under study. This link between the predictability of machine learning algorithms and the mentioned entropy measures has not been shown before. It should be considered when analyzing and predicting complex time series data, e.g., stock market data, to e.g., identify regions of increased predictability.

Interpolating Strange Attractors via Fractional Brownian Bridges.

We present a novel method for interpolating univariate time series data. The proposed method combines multi-point fractional Brownian bridges, a genetic algorithm, and Takens' theorem for reconstructing a phase space from univariate time series data. The basic idea is to first generate a population of different stochastically-interpolated time series data, and secondly, to use a genetic algorithm to find the pieces in the population which generate the smoothest reconstructed phase space trajectory. A smooth trajectory curve is hereby found to have a low variance of second derivatives along the curve. For simplicity, we refer to the developed method as PhaSpaSto-interpolation, which is an abbreviation for phase-space-trajectory-smoothing stochastic interpolation. The proposed approach is tested and validated with a univariate time series of the Lorenz system, five non-model data sets and compared to a cubic spline interpolation and a linear interpolation. We find that the criterion for smoothness guarantees low errors on known model and non-model data. Finally, we interpolate the discussed non-model data sets, and show the corresponding improved phase space portraits. The proposed method is useful for interpolating low-sampled time series data sets for, e.g., machine learning, regression analysis, or time series prediction approaches. Further, the results suggest that the variance of second derivatives along a given phase space trajectory is a valuable tool for phase space analysis of non-model time series data, and we expect it to be useful for future research.

Combining Fractional Derivatives and Machine Learning: A Review.

Fractional calculus has gained a lot of attention in the last couple of years. Researchers have discovered that processes in various fields follow fractional dynamics rather than ordinary integer-ordered dynamics, meaning that the corresponding differential equations feature non-integer valued derivatives. There are several arguments for why this is the case, one of which is that fractional derivatives inherit spatiotemporal memory and/or the ability to express complex naturally occurring phenomena. Another popular topic nowadays is machine learning, i.e., learning behavior and patterns from historical data. In our ever-changing world with ever-increasing amounts of data, machine learning is a powerful tool for data analysis, problem-solving, modeling, and prediction. It has provided many further insights and discoveries in various scientific disciplines. As these two modern-day topics hold a lot of potential for combined approaches in terms of describing complex dynamics, this article review combines approaches from fractional derivatives and machine learning from the past, puts them into context, and thus provides a list of possible combined approaches and the corresponding techniques. Note, however, that this article does not deal with neural networks, as there is already extensive literature on neural networks and fractional calculus. We sorted past combined approaches from the literature into three categories, i.e., preprocessing, machine learning and fractional dynamics, and optimization. The contributions of fractional derivatives to machine learning are manifold as they provide powerful preprocessing and feature augmentation techniques, can improve physically informed machine learning, and are capable of improving hyperparameter optimization. Thus, this article serves to motivate researchers dealing with data-based problems, to be specific machine learning practitioners, to adopt new tools, and enhance their existing approaches.

Combining Measures of Signal Complexity and Machine Learning for Time Series Analyis: A Review.

Measures of signal complexity, such as the Hurst exponent, the fractal dimension, and the Spectrum of Lyapunov exponents, are used in time series analysis to give estimates on persistency, anti-persistency, fluctuations and predictability of the data under study. They have proven beneficial when doing time series prediction using machine and deep learning and tell what features may be relevant for predicting time-series and establishing complexity features. Further, the performance of machine learning approaches can be improved, taking into account the complexity of the data under study, e.g., adapting the employed algorithm to the inherent long-term memory of the data. In this article, we provide a review of complexity and entropy measures in combination with machine learning approaches. We give a comprehensive review of relevant publications, suggesting the use of fractal or complexity-measure concepts to improve existing machine or deep learning approaches. Additionally, we evaluate applications of these concepts and examine if they can be helpful in predicting and analyzing time series using machine and deep learning. Finally, we give a list of a total of six ways to combine machine learning and measures of signal complexity as found in the literature.

Taming the Chaos in Neural Network Time Series Predictions.

Machine learning methods, such as Long Short-Term Memory (LSTM) neural networks can predict real-life time series data. Here, we present a new approach to predict time series data combining interpolation techniques, randomly parameterized LSTM neural networks and measures of signal complexity, which we will refer to as complexity measures throughout this research. First, we interpolate the time series data under study. Next, we predict the time series data using an ensemble of randomly parameterized LSTM neural networks. Finally, we filter the ensemble prediction based on the original data complexity to improve the predictability, i.e., we keep only predictions with a complexity close to that of the training data. We test the proposed approach on five different univariate time series data. We use linear and fractal interpolation to increase the amount of data. We tested five different complexity measures for the ensemble filters for time series data, i.e., the Hurst exponent, Shannon's entropy, Fisher's information, SVD entropy, and the spectrum of Lyapunov exponents. Our results show that the interpolated predictions consistently outperformed the non-interpolated ones. The best ensemble predictions always beat a baseline prediction based on a neural network with only a single hidden LSTM, gated recurrent unit (GRU) or simple recurrent neural network (RNN) layer. The complexity filters can reduce the error of a random ensemble prediction by a factor of 10. Further, because we use randomly parameterized neural networks, no hyperparameter tuning is required. We prove this method useful for real-time time series prediction because the optimization of hyperparameters, which is usually very costly and time-intensive, can be circumvented with the presented approach.

Risk of extrapelvine vascular injuries in osteosynthesis with gliding hip screws.

BACKGROUND: Dynamic hip screw (DHS) osteosynthesis represents one of the most frequently performed fixation methods in orthopedic practice. The purpose of this study was to determine the potential risk of vascular damage by DHS side-plate screws (PS) and plunging instruments for individual femoral vessels and screw positions. METHODS: In ten hemipelvic/leg specimens mounted with a large femur distractor, a DHS system with a four-hole side-plate was inserted. PS were inserted in 3 consecutive courses with different inclinations in the frontal plane of 0° (group 1), - 30° posterior (group 2) and + 30° anterior (group 3) in relation to the side-plate's surface, resulting in 120 PS positions. After screw tightening, the soft tissues on the medial side of the femur were dissected and investigated for vascular compromise; in each course, the effect of overshot instruments within a range of 50 mm beyond the side-plate's surface was also tested. RESULTS: Totally, 37/120 screw positions (31%) revealed potential vascular compromise which comprised of 15/120 (13%) direct hits by screw tips and 22/120 (18%) potential impacts by plunging instruments. The deep femoral artery system (DFA) was significantly (p = 0.007) most often affected but no significant differences for individual vascular structures were seen. Direct vascular impacts occurred significantly more often (p = 0.0047) in screws with 0° inclination compared to + 30° inclination (p = 0.017). Significant differences among individual screw positions were only found in group - 30° with direct vessel contacts (p = 0.038). CONCLUSIONS: The DFA system is significantly more at risk while significant preference of a certain vessel is missing. Our data indicate that more than 30% of 120 screw positions in DHS osteosynthesis revealed a potential danger of vascular compromise, when surgical principles are denied in hip fracture fixation. CLINICAL RELEVANCE: Though vascular complications are infrequently encountered in DHS osteosynthesis they have to be considered as a potential complication when surgical principles are not followed in this anatomic area.

Tectonics, climate, and the rise and demise of continental aquatic species richness hotspots.

Continental aquatic species richness hotspots are unevenly distributed across the planet. In present-day Europe, only two centers of biodiversity exist (Lake Ohrid on the Balkans and the Caspian Sea). During the Neogene, a wide variety of hotspots developed in a series of long-lived lakes. The mechanisms underlying the presence of richness hotspots in different geological periods have not been properly examined thus far. Based on Miocene to Recent gastropod distributions, we show that the existence and evolution of such hotspots in inland-water systems are tightly linked to the geodynamic history of the European continent. Both past and present hotspots are related to the formation and persistence of long-lived lake systems in geological basins or to isolation of existing inland basins and embayments from the marine realm. The faunal evolution within hotspots highly depends on warm climates and surface area. During the Quaternary icehouse climate and extensive glaciations, limnic biodiversity sustained a severe decline across the continent and most former hotspots disappeared. The Recent gastropod distribution is mainly a geologically young pattern formed after the Last Glacial Maximum (19 ky) and subsequent formation of postglacial lakes. The major hotspots today are related to long-lived lakes in preglacially formed, permanently subsiding geological basins.

Stress fractures of the femoral neck in runners: a review.

A systematic review, following strict inclusion criteria, identified 32/48 low and 16/48 high-performance runners with stress fractures of the femoral neck. Surgical treatment was performed in 33/48 cases and was significantly higher (p = 0.009) in high-performance runners. Among the 28/48 runners who resumed running, there were significantly more lower-performance runners (23/32) than higher-performing runners (5/16) (p = 0.012) and significantly more non-displaced (22/30) than displaced fractures (6/18) (p = 0.014). Complicated cases showed significantly less favourable follow-up results (p = 0.036). A significantly shorter (p = 0.032) diagnostic time for evaluation occurred with a previous history of a stress fracture or a relevant comorbidity. Stress fractures of the femoral neck represent an incisive incident for runners, and early consideration in the differential diagnosis of hip pain is required to avoid potential long-term sequelae and suboptimal function.

Converging nuclear magnetic shielding calculations with respect to basis and system size in protein systems.

Ab initio chemical shielding calculations greatly facilitate the interpretation of nuclear magnetic resonance (NMR) chemical shifts in biological systems, but the large sizes of these systems requires approximations in the chemical models used to represent them. Achieving good convergence in the predicted chemical shieldings is necessary before one can unravel how other complex structural and dynamical factors affect the NMR measurements. Here, we investigate how to balance trade-offs between using a better basis set or a larger cluster model for predicting the chemical shieldings of the substrates in two representative examples of protein-substrate systems involving different domains in tryptophan synthase: the N-(4'-trifluoromethoxybenzoyl)-2-aminoethyl phosphate (F9) ligand which binds in the α active site, and the 2-aminophenol quinonoid intermediate formed in the ß active site. We first demonstrate that a chemically intuitive three-layer, locally dense basis model that uses a large basis on the substrate, a medium triple-zeta basis to describe its hydrogen-bonding partners and/or surrounding van der Waals cavity, and a crude basis set for more distant atoms provides chemical shieldings in good agreement with much more expensive large basis calculations. Second, long-range quantum mechanical interactions are important, and one can accurately estimate them as a small-basis correction to larger-basis calculations on a smaller cluster. The combination of these approaches enables one to perform density functional theory NMR chemical shift calculations in protein systems that are well-converged with respect to both basis set and cluster size.

Comparison between minimally invasive, percutaneous osteosynthesis and locking plate osteosynthesis in 3-and 4-part proximal humerus fractures.

BACKGROUND: The ideal method for the surgical treatment of proximal humeral fractures has not yet been found. We therefore conducted a retrospective matched-pair analysis and compared osteosynthesis with open reduction and internal fixation and that with an angular stable plate with minimally invasive, closed reduction, percutaneous fixation with the Humerusblock. METHODS: During a study period of 3 years, we matched 30 patients treated with angular stable plates (group 1) for age, gender, fracture type and handedness (dominant or nondominant) to 30 patients treated using the Humerusblock (group 2). At a minimal follow-up of 24 months, clinical evaluation included the Constant-Murley score, the UCLA score and the Simple Shoulder Test. Subjective pain was evaluated using the VAS pain scale. Patients were asked to rate their subjective satisfaction of final outcome as excellent, good, satisfied or dissatisfied. RESULTS: The mean CMS, UCLA score and SST differed significantly between groups 1 and 2 (60.9 vs 71.9, p < 0.01), (25.1 vs 29.5, p < 0.01) and (8.1 vs 9.4, p < 0.05), respectively. The VAS pain score was significantly lower in group 2 than in group 1 (1.2 vs 2.4; p < 0.01). The mean abduction (109.7° vs 133.7°; p < 0.01) and anterior flexion (128.3° vs 145.7°; p < 0.01) were significantly worse in group 1. The mean operation time was significantly shorter in group 2 (117.3 vs 72.1, p < 0.01). Complications occurred in 30 % (group 1) and 23 % (group 2) of patients. CONCLUSIONS: In this study, the functional outcome is superior in the Humerusblock group. However, the general outcome after surgical treatment of 3-and 4-part fractures is moderate, and the complication rate has to be considered, even though it can be lowered with the use of minimally invasive implants.

Protonation states of the tryptophan synthase internal aldimine active site from solid-state NMR spectroscopy: direct observation of the protonated Schiff base linkage to pyridoxal-5'-phosphate.

The acid-base chemistry that drives catalysis in pyridoxal-5'-phosphate (PLP)-dependent enzymes has been the subject of intense interest and investigation since the initial identification of PLP's role as a coenzyme in this extensive class of enzymes. It was first proposed over 50 years ago that the initial step in the catalytic cycle is facilitated by a protonated Schiff base form of the holoenzyme in which the linking lysine ε-imine nitrogen, which covalently binds the coenzyme, is protonated. Here we provide the first (15)N NMR chemical shift measurements of such a Schiff base linkage in the resting holoenzyme form, the internal aldimine state of tryptophan synthase. Double-resonance experiments confirm the assignment of the Schiff base nitrogen, and additional (13)C, (15)N, and (31)P chemical shift measurements of sites on the PLP coenzyme allow a detailed model of coenzyme protonation states to be established.

Population bottleneck triggering millennial-scale morphospace shifts in endemic thermal-spring melanopsids.

For more than hundred years the thermal spring-fed Lake Pețea near Oradea, Romania, was studied for its highly endemic subfossil and recent fauna and flora. One point of focus was the species lineage of the melanopsid gastropod Microcolpia parreyssii, which exhibited a tremendous diversity of shapes during the earlier Holocene. As a consequence many new species, subspecies, and variety-names have been introduced over time, trying to categorize this overwhelming variability. In contrast to the varied subfossil assemblage, only a single phenotype is present today. We critically review the apparent "speciation event" implied by the taxonomy, based on the presently available information and new data from morphometric analyses of shell outlines and oxygen and carbon isotope data. This synthesis shows that one turning point in morphological evolution coincides with high accumulation of peaty deposits during a short time interval of maximally a few thousand years. The formation of a small, highly eutrophic swamp with increased input of organic matter marginalized the melanopsids and reduced population size. The presented data make natural selection as the dominating force unlikely but rather indicates genetic drift following a bottleneck effect induced by the environmental changes. This claim contrasts the "obvious trend" and shows that great morphological variability has to be carefully and objectively evaluated in order to allow sound interpretations of the underlying mechanisms.

Replacement names and nomenclatural comments for problematic species-group names in Europe's Neogene freshwater Gastropoda.

Over the last 250 years of taxonomic descriptions of freshwater gastropods a large number of primary and secondary homonyms were produced. Several of them have now been uncovered in the course of a new database project. To overcome the associated nomenclatural problems we propose 10 replacement names: Theodoxus pseudodacicus nom. nov., Theodoxus stoicai nom. nov., Viviparus deleeuwi nom. nov., Viviparus lubenescuae nom. nov., Viviparus wesselinghi nom. nov., Melanopsis anistratenkoi nom. nov., Melanopsis gearyae nom. nov., Melanopsis magyari nom. nov., Melanopsis vrcinensis nom. nov., and Pyrgula rusti nom. nov. Additionally, we discuss taxa that might become secondary homonyms because of uncertain genus attributions. The genera Melanoptychia Neumayr, 1880 and Boistelia Cossmann, 1909 are synonymized with Melanopsis Férussac, 1807 in Férussac & Férussac, 1807 based on the lack of sufficient separation criteria. Involved combinations are expounded and recombined accordingly. The nomenclatural problems regarding Melanopsis costata Fuchs, 1870 (non Olivier, 1804) and Planorbis varians Fuchs, 1870 sensu Bandel (2010) are discussed.

The fossil record of freshwater Gastropoda - a global review.

Gastropoda are an exceptionally successful group with a rich and diverse fossil record. They have conquered land and freshwater habitats multiple times independently and have dispersed across the entire globe. Since they are important constituents of fossil assemblages, they are often used for palaeoecological reconstruction, biostratigraphic correlations, and as model groups to study morphological and taxonomic evolution. While marine faunas and their evolution have been a common subject of study, the freshwater component of the fossil record has attracted much less attention, and a global overview is lacking. Here, I review the fossil record of freshwater gastropods on a global scale, ranging from their origins in the late Palaeozoic to the Pleistocene. As compiled here, the global fossil record of freshwater Gastropoda includes 5182 species in 490 genera, 44 families, and 12 superfamilies over a total of ~340 million years. Following a slow and poorly known start in the late Palaeozoic, diversity slowly increased during the Mesozoic. Diversity culminated in an all-time high in the Neogene, relating to diversification in numerous long-lived (ancient) lakes in Europe. I summarise well-documented and hypothesised freshwater colonisation events and compare the patterns found in freshwater gastropods to those in land snails. Furthermore, I discuss potential preservation and sampling biases, as well as the main drivers underlying species diversification in fresh water on a larger scale. In that context, I particularly highlight the importance of long-lived lakes as islands and archives of evolution and expand a well-known concept in ecology and evolution to a broader spectrum: scale-independent ecological opportunity.

Many roads to success: alternative routes to building an economic shell in land snails.

Land snails exhibit an extraordinary variety of shell shapes. The way shells are constructed underlies biological and mechanical constraints that vary across gastropod clades. Here, we quantify shell geometry of the two largest groups, Stylommatophora and Cyclophoroidea, to assess the potential causes for variation in shell shape and its relative frequency. Based on micro-computed tomography scans, we estimate material efficiency through 2D and 3D generalizations of the isoperimetric ratio, quantifying the ratios between area and perimeter of whorl cross-sections (2D) and shell volume and surface (3D), respectively. We find that stylommatophorans optimize material usage through whorl overlap, which may have promoted the diversification of flat-shelled species. Cyclophoroids are bound to a circular cross-section because of their operculum; flat shells are comparatively rare. Both groups show similar solutions for tall shells, where local geometry has a smaller effect because of the double overlap between previous and current whorls. Our results suggest that material efficiency is a driving factor in the selection of shell geometry. Essentially, the evolutionary success of Stylommatophora likely roots in their higher flexibility to produce an economic shell.

Allostery and substrate channeling in the tryptophan synthase bienzyme complex: evidence for two subunit conformations and four quaternary states.

The allosteric regulation of substrate channeling in tryptophan synthase involves ligand-mediated allosteric signaling that switches the α- and ß-subunits between open (low activity) and closed (high activity) conformations. This switching prevents the escape of the common intermediate, indole, and synchronizes the α- and ß-catalytic cycles. (19)F NMR studies of bound α-site substrate analogues, N-(4'-trifluoromethoxybenzoyl)-2-aminoethyl phosphate (F6) and N-(4'-trifluoromethoxybenzenesulfonyl)-2-aminoethyl phosphate (F9), were found to be sensitive NMR probes of ß-subunit conformation. Both the internal and external aldimine F6 complexes gave a single bound peak at the same chemical shift, while α-aminoacrylate and quinonoid F6 complexes all gave a different bound peak shifted by +1.07 ppm. The F9 complexes exhibited similar behavior, but with a corresponding shift of -0.12 ppm. X-ray crystal structures show the F6 and F9 CF3 groups located at the α-ß subunit interface and report changes in both the ligand conformation and the surrounding protein microenvironment. Ab initio computational modeling suggests that the change in (19)F chemical shift results primarily from changes in the α-site ligand conformation. Structures of α-aminoacrylate F6 and F9 complexes and quinonoid F6 and F9 complexes show the α- and ß-subunits have closed conformations wherein access of ligands into the α- and ß-sites from solution is blocked. Internal and external aldimine structures show the α- and ß-subunits with closed and open global conformations, respectively. These results establish that ß-subunits exist in two global conformational states, designated open, where the ß-sites are freely accessible to substrates, and closed, where the ß-site portal into solution is blocked. Switching between these conformations is critically important for the αß-catalytic cycle.

Microfibrous substrate geometry as a critical trigger for organization, self-renewal, and differentiation of human embryonic stem cells within synthetic 3-dimensional microenvironments.

Substrates used to culture human embryonic stem cells (hESCs) are typically 2-dimensional (2-D) in nature, with limited ability to recapitulate in vivo-like 3-dimensional (3-D) microenvironments. We examined critical determinants of hESC self-renewal in poly-d-lysine-pretreated synthetic polymer-based substrates with variable microgeometries, including planar 2-D films, macroporous 3-D sponges, and microfibrous 3-D fiber mats. Completely synthetic 2-D substrates and 3-D macroporous scaffolds failed to retain hESCs or support self-renewal or differentiation. However, synthetic microfibrous geometries made from electrospun polymer fibers were found to promote cell adhesion, viability, proliferation, self-renewal, and directed differentiation of hESCs in the absence of any exogenous matrix proteins. Mechanistic studies of hESC adhesion within microfibrous scaffolds indicated that enhanced cell confinement in such geometries increased cell-cell contacts and altered colony organization. Moreover, the microfibrous scaffolds also induced hESCs to deposit and organize extracellular matrix proteins like laminin such that the distribution of laminin was more closely associated with the cells than the Matrigel treatment, where the laminin remained associated with the coated fibers. The production of and binding to laminin was critical for formation of viable hESC colonies on synthetic fibrous scaffolds. Thus, synthetic substrates with specific 3-D microgeometries can support hESC colony formation, self-renewal, and directed differentiation to multiple lineages while obviating the stringent needs for complex, exogenous matrices. Similar scaffolds could serve as tools for developmental biology studies in 3-D and for stem cell differentiation in situ and transplantation using defined humanized conditions.