Search

Polypharmacy in older adults increases the risk of adverse drug reactions (ADRs), but studying this relationship is complex. In real-world data, the high number of medications, coupled with rare drug combinations, results in high-dimensional datasets that are difficult to analyze using conventional statistical methods. This study applies horseshoe and lasso regression for analyzing rare events in polypharmacy contexts, focusing on severe ADRs such as falls and bleedings. These regression models are executed on a multi-center dataset compiling 7175 cases from the ADRED project to detect potential ADR-associated drugs among 100 most common drugs in emergency department admissions. Positive predictors are classified by using 50% and 90% credibility intervals. This study demonstrates that regression models with horseshoe or lasso priors are effective for analyzing ADRs, providing a comprehensive consideration of multiple factors in large, sparse datasets and improving signal detection in polypharmacy, addressing a significant challenge in pharmacovigilance. Both priors yielded consistent and clinically meaningful results. The horseshoe regression resulted in fewer potential positive predictors overall, which could make it suitable as a diagnostic tool. While these regressions generate valuable information, there are still challenges in setting appropriate thresholds for determining and interpreting the positive results. [ABSTRACT FROM AUTHOR]

Abstract Polypharmacy in older adults increases the risk of adverse drug reactions (ADRs), but studying this relationship is complex. In real-world data, the high number of medications, coupled with rare drug combinations, results in high-dimensional datasets that are difficult to analyze using conventional statistical methods. This study applies horseshoe and lasso regression for analyzing rare events in polypharmacy contexts, focusing on severe ADRs such as falls and bleedings. These regression models are executed on a multi-center dataset compiling 7175 cases from the ADRED project to detect potential ADR-associated drugs among 100 most common drugs in emergency department admissions. Positive predictors are classified by using 50% and 90% credibility intervals. This study demonstrates that regression models with horseshoe or lasso priors are effective for analyzing ADRs, providing a comprehensive consideration of multiple factors in large, sparse datasets and improving signal detection in polypharmacy, addressing a significant challenge in pharmacovigilance. Both priors yielded consistent and clinically meaningful results. The horseshoe regression resulted in fewer potential positive predictors overall, which could make it suitable as a diagnostic tool. While these regressions generate valuable information, there are still challenges in setting appropriate thresholds for determining and interpreting the positive results.

Katok [Lyapunov exponents, entropy and periodic points of diffeomorphisms. Publ. Math. Inst. Hautes Études Sci. 51 (1980), 137–173] conjectured that every $C^{2}$ diffeomorphism f on a Riemannian manifold has the intermediate entropy property, that is, for any constant $c \in [0, h_{\mathrm {top}}(f))$ , there exists an ergodic measure $\mu $ of f satisfying $h_{\mu }(f)=c$. In this paper, we obtain a conditional intermediate metric entropy property and two conditional intermediate Birkhoff average properties for basic sets of flows that characterize the refined roles of ergodic measures in the invariant ones. In this process, we establish a 'multi-horseshoe' entropy-dense property and use it to get the goal combined with conditional variational principles. We also obtain the same result for singular hyperbolic attractors. [ABSTRACT FROM AUTHOR]

Racehorses are susceptible to underrun heel hoof conformation. Racehorses are often shod with nails placed toward the heel. It is unknown if palmar nails restrict or alter hoof deformation in a manner that could promote the development of underrun heel conformation over time with repeated loading. To determine how the addition of palmar nails affects heel deformation during limb loading, hoof expansion and hoof wall deformations were quantified using rosette strain gauges and kinematic markers during in the vitro limb loading of cadaveric limbs that simulated midstance for walk, trot, and canter loads. Nail treatments used to attach a horseshoe to the hoof included: toe nails (T), toe and quarter nails (TQ), and toe, quarter, and heel nails (TQH). The effects of nail treatment on heel expansion and hoof wall deformations were assessed using repeated measures analysis of variance (p < 0.05). Nails placed palmar to the quarters of the hoof decreased heel expansion (p < 0.001). Heel nails resulted in the largest changes in hoof wall principal strain directions distally. The application of nails palmar to the hoof quarters alters hoof wall deformation during limb loading. The continued loading of the hoof with palmer nails could alter hoof conformation over time.

Spike‐and‐slab and horseshoe regressions are arguably the most popular Bayesian variable selection approaches for linear regression models. However, their performance can deteriorate if outliers and heteroskedasticity are present in the data, which are common features in many real‐world statistics and machine learning applications. This work proposes a Bayesian nonparametric approach to linear regression that performs variable selection while accounting for outliers and heteroskedasticity. Our proposed model is an instance of a Dirichlet process scale mixture model with the advantage that we can derive the full conditional distributions of all parameters in closed‐form, hence producing an efficient Gibbs sampler for posterior inference. Moreover, we present how to extend the model to account for heavy‐tailed response variables. The model's performance is tested against competing algorithms on synthetic and real‐world datasets. [ABSTRACT FROM AUTHOR]

We enumerate the various laparoscopic strategies to resolve upper urinary tract (UUT) obstruction in the context of variations in anatomy and report their outcomes. Retrospective review of primary laparoscopic UUT reconstructions performed between May 2012 and May 2021. Anomalies included: malrotated kidney (MRK), horseshoe kidney (HSK), duplex kidney (DK), pure intrarenal pelvis (IRP) and mid-ureteric stenosis (MUS). Success was defined by postoperative resolution of symptoms, improvement of anterior–posterior renal pelvic diameter (APD) on US and drainage on Mag3. Complications were categorised by Clavien–Dindo grading. Outcomes compared using the student's t-test with P < 0.05 considered statistically significant. Of the 214 laparoscopic primary UUT reconstructions, 37 (17.2 %) were: 13-MRK, 12-HSK, 4-DK, 4-IRP and 4-MUS. Median age at surgery was 5-years (range 0.3–15). Dismembered pyeloplasty: 8; pyeloplasty with renal sinus dissection: 8; neo-PUJ anastomosis: 8; primary ureterocalycostomy: 7; pyeloureterostomy: 2; and uretero-ureterostomy: 4. Median follow-up was 43-months (range 8–108) with a success rate of 94.5 % (35/37). Complete resolution of symptoms in 20/21 patients; improvement of hydronephrosis on US in 35/37 patients (median pre-operative APD 27 mm vs. median postoperative APD 8 mm) [ P < 0.001]; improvement of drainage on diuretic renogram in 32/34 kidneys and stable/improved DRF in 34/35 kidneys (median preoperative DRF - 45 % vs. median postoperative DRF - 47 %) [ P > 0.05]. Postoperative complications managed medically (II Clavien) included urinary tract infections – 2 patients (5 %), stent-related symptoms in 2 (5 %) and umbilical port site collection in 1 patient (3 %). Recurrent pelvi–ureteric junction obstruction PUJO occurred in one patient (3 %) requiring redo surgery (IIIb Clavien), renal stones in 1 (3 %) which resolved with ESWL (IIIb Clavien); in 1 (3 %) patient with a HSK there was complete loss of ipsilateral kidney function but this was managed conservatively up to date (I Clavien). Laparoscopic transperitoneal approach allows the prompt recognition of in-situ anatomical variants. UUT obstruction in such settings calls for a variety of strategies with excellent outcomes. [ABSTRACT FROM AUTHOR]

Objective: To deliver a case report showing that robotic pyeloplasty in a patient with a horseshoe kidney is not only successful but also potentially superior to laparoscopic surgery. To the best of our knowledge, this is the first case report of its kind in the United Kingdom. Method: PubMed was used to do a literature search. We have excluded papers that were written in foreign languages, or were paediatric case studies. Results: Horseshoe kidneys are the commonest congenital abnormality of the renal and are often associated with pelvic-ureteric junction obstruction (PUJO) – in the order of 30%. Minimally invasive surgery is the gold standard for management of PUJO. With the advancement of the Da Vinci robot, this case report presents a patient undergoing pyeloplasty in a horseshoe kidney with PUJO on the left side, using a robotic technique. We performed a robotic pyeloplasty on a 32-year-old woman, with a horseshoe kidney. We felt this is a case worth discussion, giving the alteration in the surgical technique in conjunction with the anatomical abnormalities, and the lack of similar reported cases in the literature. We propose that in some cases, the robotic operative technique is superior to standard laparoscopic technique. Although there is an increased cost when using the Da Vinci robot, this may be offset by the 3D visualisation, enhanced dexterity, tremor filtering and movement scaling, increased range of motion, as well as the reduction of operative time, hospital stay, blood loss, complications, and indeed patient satisfaction. In addition to the benefits of robotic surgery itself, we demonstrate that robotic surgery in this particular case was preferable to other techniques, given the anatomical exclusivity of a horseshoe kidney. Conclusion: We propose that in some cases, the robotic operative technique is superior to other minimal access techniques in urological surgery. Level of Evidence: 4 [ABSTRACT FROM AUTHOR]

We show that if f : R → R is a continuous transitive map and γ : [ 0 , 1 ] → R is a nonconstant curve having finite total variation, then the total variation of f n ∘ γ tends to infinity exponentially as n → ∞ . A similar result is also proved for a Devaney chaotic map on a graph G. [ABSTRACT FROM AUTHOR]

For a non-conformal repeller $\Lambda $ of a $C^{1+\alpha }$ map f preserving an ergodic measure $\mu $ of positive entropy, this paper shows that the Lyapunov dimension of $\mu $ can be approximated gradually by the Carathéodory singular dimension of a sequence of horseshoes. For a $C^{1+\alpha }$ diffeomorphism f preserving a hyperbolic ergodic measure $\mu $ of positive entropy, if $(f, \mu)$ has only two Lyapunov exponents $\unicode{x3bb} _u(\mu)>0>\unicode{x3bb} _s(\mu)$ , then the Hausdorff or lower box or upper box dimension of $\mu $ can be approximated by the corresponding dimension of the horseshoes $\{\Lambda _n\}$. The same statement holds true if f is a $C^1$ diffeomorphism with a dominated Oseledet's splitting with respect to $\mu $. [ABSTRACT FROM AUTHOR]

Hoof and leg problems in racehorses can cause serious injuries and decrease their value. Although therapeutic shoeing using special horseshoes can increase the effectiveness of veterinary care, it is labor-intensive and burdensome for farriers. A three-dimensional (3D) printed horseshoe fabricated by additive manufacturing has high design flexibility for use in special horseshoes. However, the mechanical properties of 3D printed plastics for use as horseshoes remain unclear. In this study, a proposed 3D printed plastic was subjected to degradation tests under the simulated equine growth environment, and changes in strength during the period of use were investigated. It was found that the strength of polylactic acid and polycarbonate, which are commonly used for 3D printing, was not significantly affected by the environment.

This article studies the time-varying parameter (TVP) regression model in which the regression coefficients are random walk latent states with timedependent conditional variances. This TVPmodel is flexible to accommodate a wide variety of time variation patterns but requires effective shrinkage on the state variances to avoid over-fitting. A Bayesian shrinkage prior is proposed based on reparameterization that translates the variance shrinkage problem into a variable shrinkage one in a conditionally linear regression with fixed coefficients. The proposed prior allows strong shrinkage for the state variances while maintaining the flexibility to accommodate local signals. A Bayesian estimation method is developed that employs the ancilarity-sufficiency interweaving strategy to boost sampling efficiency. Simulation study and an empirical application to forecast inflation rate illustrate the benefits of the proposed approach. [ABSTRACT FROM AUTHOR]

This article studies a time series binary probit model in which the underlying latent variable depends on its lag and exogenous regressors. The regression coefficients for the latent variable are allowed to vary over time to capture possible model instability. Bayesian shrinkage priors are applied to automatically differentiate fixed and truly time-varying coefficients and thus avoid unnecessary model complexity. I develop an MCMC algorithm for model estimation that exploits parameter blocking to boost sampling efficiency. An efficient Monte Carlo approximation based on the Kalman filter is developed to improve the numerical stability for computing the predictive likelihood of the binary outcome. Benefits of the proposed model are illustrated in a simulation study and an application to forecast economic recessions. [ABSTRACT FROM AUTHOR]

AbstractIn this paper, we construct a Bayesian hierarchical model with global-local shrinkage priors for the regression coefficients, which includes the horseshoe prior and normal-gamma prior. This model is used for high-dimensional quantile regression models with dichotomous response data. We have developed an efficient sampling algorithm to generate posterior samplings for making posterior inference. We use a location-scale mixture representation of the asymmetric Laplace distribution. We assess the performance of the proposed methods through Monte Carlo simulations and two real-data applications in terms of parameter estimation and variable selection. Numerical results demonstrate that the proposed methods perform comparably with existing Bayesian methods under a variety of scenarios. [ABSTRACT FROM AUTHOR]

Hoof and leg problems in racehorses can cause serious injuries and decrease their value. Although therapeutic shoeing using special horseshoes can increase the effectiveness of veterinary care, it is labor-intensive and burdensome for farriers. A three-dimensional (3D) printed horseshoe fabricated by additive manufacturing has high design flexibility for use in special horseshoes. However, the mechanical properties of 3D printed plastics for use as horseshoes remain unclear. In this study, a proposed 3D printed plastic was subjected to degradation tests under the simulated equine growth environment, and changes in strength during the period of use were investigated. It was found that the strength of polylactic acid and polycarbonate, which are commonly used for 3D printing, was not significantly affected by the environment. [ABSTRACT FROM AUTHOR]

Case series summary: A retrospective multicenter case series of renal fusion anomalies in cats was investigated. The aim of this study was to describe the imaging characteristics (radiography, ultrasonography and CT) of renal ectopia and fusion in cats. A total of 13 feline patients (median age 9 years) were included in this multicentric retrospective study. Ultrasound was available in 12/13 cases, radiographs in 4/13 cases and CT in 3/13 cases. Of the 13 cases, seven were left to right fusions, four were right to left fusions, one was on the midline and one was in the pelvic inlet. Adopting a human classification system, there were five lump kidneys, four disc kidneys, one horseshoe kidney, one caudal ectopia, one L-shaped kidney and one pelvic kidney. In 2/13 cases, additional congenital malformations were noted, including an azygous continuation of the caudal vena cava and a peritoneal-pericardial diaphragmatic hernia. Relevance and novel information: This study provides further description of the imaging findings in feline patients with fused renal ectopia. The morphologic characteristics of the fused kidneys in cats appear similar to what is published in the human literature. Renal fusion might be an incidental finding in cats, but further investigations are necessary to determine their clinical relevance. [ABSTRACT FROM AUTHOR]

Let X be a dendrite and let f : X → X be a continuous map that has an infinite minimal set M in X. In the article we obtain conditions on the structure of a dendrite X and the set M, under which f has an arc horseshoe, and, hence, f has a positive topological entropy. We show that this result is not correct both for continuous maps with an empty set of periodic points, and for continuous maps with a non-empty set of periodic points on finite graphs. [ABSTRACT FROM AUTHOR]

In the urban underground transportation systems, especially, in case of mechanized tunneling, tunnel boring machine (TBM) of circular shape is mostly used for tunneling advancement. However, circular-shaped TBM particularly of large diameter have large waste of utilization area that is, small space utilization ratio. With the advancement in the machine manufacturing industries, non-circular-shaped TBM is now used, whose cross section allows to use the underground space efficiently to improve space utilization ratio. Despite the significance of this issue, there has not been much prior research reported in the literature for designing and analyzing underground-excavations/tunnels having horseshoe-shaped cross sections in anisotropic–heterogeneous clay. In the present study, peripheral stability analysis of real horseshoe-shaped unlined tunnels in saturated clay with direction reliant and linearly varying undrained shear strength has been performed using lower bound limit analysis coupled with finite elements and second-order cone programming. For a range of material properties and cover depth of tunnel, the stability charts for unlined tunnel have been generated in this study, which will serve as a useful tool for engineering practitioners. It has also been demonstrated that the underground excavations with horseshoe-shaped cross section is more stable as compared to that with equivalent circular-shaped cross section for the same value of utilization area. [ABSTRACT FROM AUTHOR]

Pelviureteric junction obstruction, also known as ureteropelvic junction obstruction, is a congenital narrowing of the urinary excretory tract at the junction between the renal pelvis and the ureter and is a common cause of congenital pelvicalyceal dilatation. The outcome is variable, from spontaneous resolution to renal parenchymal function loss in cases of untreated high-grade obstruction. Abnormalities in renal ascent, rotation and vascularity can be associated with pelviureteric junction obstruction and easily overlooked radiologically. In this pictorial review, we explore the anatomical, radiological and surgical correlations of pelviureteric junction obstruction in the context of a normal kidney and a spectrum of renal abnormalities, including hyper-rotation (also known as renal malrotation), failed renal ascent, fusion anomalies and accessory crossing renal vessels. For each scenario, we provide technical tips on how to identify the altered anatomy at the first ultrasound assessment and correlation with scintigraphic, cross-sectional and postoperative imaging where appropriate. A detailed ultrasound protocol specifically to assess and characterise pelviureteric junction obstruction in paediatric patients is also offered. [ABSTRACT FROM AUTHOR]

When meta‐analyzing heterogeneous bodies of literature, meta‐regression can be used to account for potentially relevant between‐studies differences. A key challenge is that the number of candidate moderators is often high relative to the number of studies. This introduces risks of overfitting, spurious results, and model non‐convergence. To overcome these challenges, we introduce Bayesian Regularized Meta‐Analysis (BRMA), which selects relevant moderators from a larger set of candidates by shrinking small regression coefficients towards zero with regularizing (LASSO or horseshoe) priors. This method is suitable when there are many potential moderators, but it is not known beforehand which of them are relevant. A simulation study compared BRMA against state‐of‐the‐art random effects meta‐regression using restricted maximum likelihood (RMA). Results indicated that BRMA outperformed RMA on three metrics: BRMA had superior predictive performance, which means that the results generalized better; BRMA was better at rejecting irrelevant moderators, and worse at detecting true effects of relevant moderators, while the overall proportion of Type I and Type II errors was equivalent to RMA. BRMA regression coefficients were slightly biased towards zero (by design), but its residual heterogeneity estimates were less biased than those of RMA. BRMA performed well with as few as 20 studies, suggesting its suitability as a small sample solution. We present free open source software implementations in the R‐package pema (for penalized meta‐analysis) and in the stand‐alone statistical program JASP. An applied example demonstrates the use of the R‐package. [ABSTRACT FROM AUTHOR]

In the network approach to psychopathology, psychological constructs are conceptualized as networks of interacting components (e.g., the symptoms of a disorder). In this network view, interest is on the degree to which symptoms influence each other, both directly and indirectly. These direct and indirect influences are often captured with centrality indices, however, the estimation method often used with these networks, the frequentist graphical LASSO (GLASSO), has difficulty estimating (uncertainty in) these measures. Bayesian estimation might provide a solution, as it is better suited to deal with bias in the sampling distribution of centrality indices. This study therefore compares estimation of symptom networks with Bayesian GLASSO- and Horseshoe priors to estimation using the frequentist GLASSO using extensive simulations. Results showed that the Bayesian GLASSO performed better than the Horseshoe, and that the Bayesian GLASSO outperformed the frequentist GLASSO with respect to bias in edge weights, centrality measures, correlation between estimated and true partial correlations, and specificity. Sensitivity was better for the frequentist GLASSO, but performance of the Bayesian GLASSO is usually close. With respect to uncertainty in the centrality measures, the Bayesian GLASSO shows good coverage for strength and closeness centrality, but uncertainty in betweenness centrality is estimated less well. [ABSTRACT FROM AUTHOR]

Estimating demand for large assortments of differentiated goods requires the specification of a demand system that is sufficiently flexible. However, flexible models are highly parameterized so estimation requires appropriate forms of regularization to avoid overfitting. In this paper, we study the specification of Bayesian shrinkage priors for pairwise product substitution parameters. We use a log-linear demand system as a leading example. Log-linear models are parameterized by own and cross-price elasticities, and the total number of elasticities grows quadratically in the number of goods. Traditional regularized estimators shrink regression coefficients towards zero which can be at odds with many economic properties of price effects. We propose a hierarchical extension of the class of global-local priors commonly used in regression modeling to allow the direction and rate of shrinkage to depend on a product classification tree. We use both simulated data and retail scanner data to show that, in the absence of a strong signal in the data, estimates of price elasticities and demand predictions can be improved by imposing shrinkage to higher-level group elasticities rather than zero. [ABSTRACT FROM AUTHOR]

Abstract Background Prediction and classification algorithms are commonly used in clinical research for identifying patients susceptible to clinical conditions such as diabetes, colon cancer, and Alzheimer’s disease. Developing accurate prediction and classification methods benefits personalized medicine. Building an excellent predictive model involves selecting the features that are most significantly associated with the outcome. These features can include several biological and demographic characteristics, such as genomic biomarkers and health history. Such variable selection becomes challenging when the number of potential predictors is large. Bayesian shrinkage models have emerged as popular and flexible methods of variable selection in regression settings. This work discusses variable selection with three shrinkage priors and illustrates its application to clinical data such as Pima Indians Diabetes, Colon cancer, ADNI, and OASIS Alzheimer’s real-world data. Methods A unified Bayesian hierarchical framework that implements and compares shrinkage priors in binary and multinomial logistic regression models is presented. The key feature is the representation of the likelihood by a Polya-Gamma data augmentation, which admits a natural integration with a family of shrinkage priors, specifically focusing on Horseshoe, Dirichlet Laplace, and Double Pareto priors. Extensive simulation studies are conducted to assess the performances under different data dimensions and parameter settings. Measures of accuracy, AUC, brier score, L1 error, cross-entropy, and ROC surface plots are used as evaluation criteria comparing the priors with frequentist methods as Lasso, Elastic-Net, and Ridge regression. Results All three priors can be used for robust prediction on significant metrics, irrespective of their categorical response model choices. Simulation studies could achieve the mean prediction accuracy of 91.6% (95% CI: 88.5, 94.7) and 76.5% (95% CI: 69.3, 83.8) for logistic regression and multinomial logistic models, respectively. The model can identify significant variables for disease risk prediction and is computationally efficient. Conclusions The models are robust enough to conduct both variable selection and prediction because of their high shrinkage properties and applicability to a broad range of classification problems.

High-dimensional feature selection arises in many areas of modern science.For example, in genomic research we want to find the genes that can be used toseparate tissues of different classes (e.g. cancer and normal) from tens ofthousands of genes that are active (expressed) in certain tissue cells. To thisend, we wish to fit regression and classification models with a large number offeatures (also called variables, predictors). In the past decade, penalizedlikelihood methods for fitting regression models based on hyper-LASSOpenalization have received increasing attention in the literature. However,fully Bayesian methods that use Markov chain Monte Carlo (MCMC) are still inlack of development in the literature. In this paper we introduce an MCMC(fully Bayesian) method for learning severely multi-modal posteriors oflogistic regression models based on hyper-LASSO priors (non-convex penalties).Our MCMC algorithm uses Hamiltonian Monte Carlo in a restricted Gibbs samplingframework; we call our method Bayesian logistic regression with hyper-LASSO(BLRHL) priors. We have used simulation studies and real data analysis todemonstrate the superior performance of hyper-LASSO priors, and to investigatethe issues of choosing heaviness and scale of hyper-LASSO priors.

It has long been recognized that the so-called 'Oriental horseshoe' encountered by Western travellers and military personnel in the Middle East, including Iran, differed from the standard European, rim-like horseshoe in consisting of a thin plate of metal secured to the base of the horse's hoof. This study examines the literary and historical evidence for the Oriental horseshoe considering a range of Late Antique and mediaeval Islamic, as well as later sources. The efficacy of the Oriental horseshoe and its iconographic representation are examined. Examples in Western collections and the experiences of 19111 and early 20111 century military officers are described, attesting to the important differences between the European and Oriental-style of horseshoe. This important piece of material culture, which is almost never discussed in treatments of equine husbandry or military history in the Near East. deserves consideration by anyone interested in the management and deployment of cavalry in ancient and premodern Iran. [ABSTRACT FROM AUTHOR]

In this paper, the peripheral stability of a horseshoe-shaped tunnel in undrained clay with linearly increasing and directionally dependent strength is studied using the lower-bound theorem of plastic analysis coupled with finite-element formulation and second-order cone programming. The present analysis computes required supporting pressure for a tunnel constructed in isotropic/anisotropic normally consolidated (NC)/lightly overconsolidated (LOC) clay with linearly varying undrained strength across the depth, and isotropic/anisotropic heavily overconsolidated (HOC) clay whose undrained strength remains constant throughout the depth. Dimensionless stability charts have been produced for expressing the undrained stability of horseshoe tunnels in terms of anisotropic and heterogeneous parameters, tunnel cover depth, and normalized overburden pressure. The combined influence of these parameters on the peripheral stability of tunnels and associated failure mechanisms have also been examined and discussed. Further, a few analyses were done to examine the advantage of a horseshoe-shaped cross section in comparison with a circular cross section. [ABSTRACT FROM AUTHOR]

Copyright of Norba: Revista de Arte is the property of Servicio de Publicaciones de la Universidad de Extremadura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The supernumerary kidney is a rare anomaly characterized by the presence of an extra kidney. Obstructive cystic dysplasia occurs secondary to outflow tract obstruction. We present the case of a 10-year-old girl with recurrent urinary tract infection in whom evaluation revealed obstructive cystic dysplasia of the left kidney with ipsilateral vesicoureteric reflux and right supernumerary kidney. The history was significant for surgery for Ladd bands and spontaneous closure of an atrial septal defect. While ultrasound showed an empty left renal fossa, dimercaptosuccinic acid scan showed solitary right kidney with focal photopenic areas in the lower pole suggesting pyelonephritis. Contrast-enhanced computed tomography revealed right fused supernumerary kidney with focal nephronia and shrunken left kidney. The left ureter inserted ectopically into the urinary bladder; micturating cystourethrography confirmed grade 2 vesicoureteric reflux. The child was managed conservatively with antibiotics. Cystic renal dysplasia and supernumerary kidneys are a rare association that requires clinical and radiological monitoring. Screening of the contralateral functioning kidney and surgical correction of any anomalies is imperative. This case highlights the need for systematic evaluation for coexisting anomalies in patients with abnormal renal ultrasonography. [ABSTRACT FROM AUTHOR]

Pharmacogenetic variability in drug metabolism leads to patient vulnerability to side effects and to therapeutic failure. Our purpose was to introduce a systematic statistical methodology to estimate quantitative dose adjustments based on pharmacokinetic differences in pharmacogenetic subgroups, addressing the concerns of sparse data, incomplete information on phenotypic groups, and heterogeneity of study design. Data on psychotropic drugs metabolized by the cytochrome P450 enzyme CYP2C19 were used as a case study. CYP2C19 activity scores were estimated, while statistically assessing the influence of methodological differences between studies, and used to estimate dose adjustments in genotypic groups. Modeling effects of activity scores in each substance as a population led to prudential predictions of adjustments when few data were available ('shrinkage'). The best results were obtained with the regularized horseshoe, an innovative Bayesian approach to estimate coefficients viewed as a sample from two populations. This approach was compared to modeling the population of substance as normally distributed, to a more traditional "fixed effects" approach, and to dose adjustments based on weighted means, as in current practice. Modeling strategies were able to assess the influence of study parameters and deliver adjustment levels when necessary, extrapolated to all phenotype groups, as well as their level of uncertainty. In addition, the horseshoe reacted sensitively to small study sizes, and provided conservative estimates of required adjustments. [ABSTRACT FROM AUTHOR]

The horseshoe kidney (HSK) is a common renal abnormality mostly asymptomatic. This may be linked to chromosomal and organ anomalies. A 27-year-old male patient presented with mild recurrent lower abdominal pain associated with dysuria. No history of renal disease. Laboratory investigations revealed red blood cells (RBC), white blood cells (WBC), and bacterial growth in the urine. A CT urogram showed an HSK with a unilateral left-sided ureter. The patient was diagnosed with a urinary tract infection (UTI) and managed with regular follow-up. This report describes a rare case of an HSK with a unilateral left-sided, typically implanted ureter and highlights the radiological findings and management. Asymptomatic HSKs may present with or without associated anomalies. UTI is a common asymptomatic presentation. An HSK with a unilateral left-sided normally implanted ureter is rare. The present case of HSK was associated with recurrent UTI, which was managed accordingly., (Copyright: © Saudi Medical Journal.)

The horseshoe effect is a phenomenon that has long intrigued ecologists. The effect was commonly thought to be an artifact of dimensionality reduction, and multiple techniques were developed to unravel this phenomenon and simplify interpretation. Here, we provide evidence that horseshoes arise as a consequence of distance metrics that saturate-a familiar concept in other fields but new to microbial ecology. This saturation property loses information about community dissimilarity, simply because it cannot discriminate between samples that do not share any common features. The phenomenon illuminates niche differentiation in microbial communities and indicates species turnover along environmental gradients. Here we propose a rationale for the observed horseshoe effect from multiple dimensionality reduction techniques applied to simulations, soil samples, and samples from postmortem mice. An in-depth understanding of this phenomenon allows targeting of niche differentiation patterns from high-level ordination plots, which can guide conventional statistical tools to pinpoint microbial niches along environmental gradients. IMPORTANCE The horseshoe effect is often considered an artifact of dimensionality reduction. We show that this is not true in the case for microbiome data and that, in fact, horseshoes can help analysts discover microbial niches across environments.

Racehorses are susceptible to underrun heel hoof conformation. Racehorses are often shod with nails placed toward the heel. It is unknown if palmar nails restrict or alter hoof deformation in a manner that could promote the development of underrun heel conformation over time with repeated loading. To determine how the addition of palmar nails affects heel deformation during limb loading, hoof expansion and hoof wall deformations were quantified using rosette strain gauges and kinematic markers during in the vitro limb loading of cadaveric limbs that simulated midstance for walk, trot, and canter loads. Nail treatments used to attach a horseshoe to the hoof included: toe nails (T), toe and quarter nails (TQ), and toe, quarter, and heel nails (TQH). The effects of nail treatment on heel expansion and hoof wall deformations were assessed using repeated measures analysis of variance (p < 0.05). Nails placed palmar to the quarters of the hoof decreased heel expansion (p < 0.001). Heel nails resulted in the largest changes in hoof wall principal strain directions distally. The application of nails palmar to the hoof quarters alters hoof wall deformation during limb loading. The continued loading of the hoof with palmer nails could alter hoof conformation over time.

The Zero Kilometer Point is an important route for andong horses in Yogyakarta City. The renovation and replacement of road material with andesite can cause horses to slip because the horseshoes have not been adjusted to the new road material. If neglected, it can harm the horses and its owners, reducing the tourism industry in Yogyakarta. On the other hand, horseshoes demand is still met by small and medium enterprises (SME) without a well-standardized system. After doing technical testing to the existing horseshoe design, several alternative solutions were obtained for horseshoe redesign (1) by adding rubber pads and (2) serrated without rubber pads. Based on analysis and testing, it was found that horseshoe with the addition of rubber by 40% was able to increase the friction value to 0.54 or 10% from the initial condition. Besides improving the productivity and quality of SME horseshoe products, several solutions should be considered, including (1) change the layout design of SME by implementing 5S lean six sigma principles and (2) apply new methods/technology to maintain the standardization of horseshoe product. Implementation of both solutions will guarantee not only the quality product but also SME production. It is hoped that all the improvements that have been made will increase the quantity and quality of horseshoe products. Then it will also be able to improve the image of Yogyakarta City as a tourist city.

Pankaj Garg,1,2 Baljit Kaur,3 Konica Singla,2 Geetha R Menon,4 Vipul D Yagnik5 1Department of Colorectal Surgery, Indus International Hospital, Mohali, India; 2Department of Colorectal Surgery, Garg Fistula Research Institute (GFRI), Haryana, India; 3Department of Radiology, SSRD Imaging Centre, Chandigarh, India; 4Department of Biostatistics, Indian Council of Medical Research, New Delhi, India; 5Department of Surgical Gastroenterology, Nishtha Surgical Hospital and Research Centre, Patan, Gujarat, IndiaCorrespondence: Pankaj GargGarg Fistula Research Institute (GFRI), H.no- 1042, Sector-15, Panchkula, Haryana, 134113, IndiaFax +91 9501522000Email drgargpankaj@yahoo.comPurpose: In some anal fistulas, the internal/primary opening cannot be located even after examination and assessment on MRI or transrectal ultrasound. The efficacy of a simple new protocol to manage such therapeutically challenging fistulas was tested.Patients and Methods: All anal fistula patients operated consecutively over 7 years were included in the study. A simple two-step protocol was followed for fistulas in which the internal opening was not locatable after clinical examination and MRI assessment. First, the MRI was reassessed. The site where the fistula was closest to the internal sphincter was noted. It was assumed that the internal-opening was located at that position and the fistula was treated accordingly. Second, in horseshoe anal fistulas with no apparent internal opening, it was assumed that the internal opening was located in the midline. Low fistulas were treated by fistulotomy and high fistulas by a sphincter-sparing procedure. Incontinence was evaluated by objective incontinence scores (Vaizey scores).Results: A total of 757 patients were operated (median follow-up-33 months). Of these, 57 patients were excluded due to short or inadequate follow-up. In 154/700 (22%) patients, the internal opening could not be located while in 546/700 (78%), the internal opening was found. Both the groups were similar in all parameters. In the “internal-opening found” group, the fistula healed completely in 486/546 (89%) and in the ‘internal-opening not found group’, the fistula healed in 140/156 (90.9%) (p=1.01). The objective continence scores did not change significantly after surgery in both the groups.Conclusion: This new protocol seems effective as a high cure rate could be achieved in ‘internal-opening not found’ fistulas which was comparable to fistula healing in the ‘internal-opening found’ group.Keywords: anal fistula, internal opening, horseshoe, MRI, recurrence, fistula-in-ano

Autosomal dominant polycystic kidney disease (ADPKD) with concomitant horseshoe kidney is an extremely rare entity. In this case, we report a 45-year-old male patient with ADPKD and a horseshoe kidney who demonstrated hypertension, urological complications and discomfort symptoms such as pain, breathing difficulties and abdominal meteorism. After preoperative assessment and planning, the patient underwent nephrectomy. Bilateral nephrectomy without dividing the isthmus was performed successfully. The isthmus, which had complicated vasculature and was full of cysts, remained intact avoiding severe bleeding and infection. The postoperative course was uneventful. Keeping the isthmus intact in such cases is a challenge for the surgeon. The rarity of polycystic horseshoe kidney in combination with the altered abdominal anatomy requires the proper preoperative strategy in order to avoid intraoperative complications.

Objectives: Extreme horseshoe anal fistulas are rare, and there are little data on the diagnosis and management of these fistulas. Materials and Methods: Patients with horseshoe anal fistula, in which the fistula tract encircled more than 75% of the anal circumference were included in the study. All patients were assessed by a preoperative magnetic resonance imaging (MRI). The patients were managed by a sphincter-sparing procedure. The continence was evaluated by an objective continence scoring system (Vaizey's scores). Results: 1059 anal fistula patients were operated on over 7-years with a median follow-up of 36 months (range: 5–79 months). There were 47/1059 (4.4%) patients with extreme horseshoe anal fistulas. In 4/47 patients, the fistulas were complete circumanal (encircling anal canal completely). The mean age was 39.5 ± 10.9 years, M/F-41/6. The fistula was supralevator in 12/47 (25.5%), had an associated abscess in 28/47 (59.6%), and was recurrent in 33/47 (70.2%) patients. The tracts were intersphincteric in 27/47, transsphincteric in 2/47, and both (intersphincteric and transsphincteric) in 18/47 patients. All patients (n = 47) were managed by a sphincter-sparing procedure. Four patients were lost to follow-up. The fistula healed completely in 34/43 (79%) patients. There was no significant difference between preoperative and postoperative Vaizey's continence scores 0.031 ± 0.17 and 0.033 ± 0.18 respectively (P=0.90, Mann–Whitney U-test). Conclusion: Extreme horseshoe fistulas are rare, with an incidence of about 4% (in a referral practice). The missed diagnosis of circumferential tracts could lead to a recurrence. MRI was pivotal to confirm the diagnosis. Proper identification and management of internal opening and adequate drainage of all tracts were crucial for successfully treating extreme horseshoe fistulas.

Background: Prediction and classification algorithms are commonly used in clinical research for identifying patients susceptible to clinical conditions such as diabetes, colon cancer, and Alzheimer's disease. Developing accurate prediction and classification methods benefits personalized medicine. Building an excellent predictive model involves selecting the features that are most significantly associated with the outcome. These features can include several biological and demographic characteristics, such as genomic biomarkers and health history. Such variable selection becomes challenging when the number of potential predictors is large. Bayesian shrinkage models have emerged as popular and flexible methods of variable selection in regression settings. This work discusses variable selection with three shrinkage priors and illustrates its application to clinical data such as Pima Indians Diabetes, Colon cancer, ADNI, and OASIS Alzheimer's real-world data.Methods: A unified Bayesian hierarchical framework that implements and compares shrinkage priors in binary and multinomial logistic regression models is presented. The key feature is the representation of the likelihood by a Polya-Gamma data augmentation, which admits a natural integration with a family of shrinkage priors, specifically focusing on Horseshoe, Dirichlet Laplace, and Double Pareto priors. Extensive simulation studies are conducted to assess the performances under different data dimensions and parameter settings. Measures of accuracy, AUC, brier score, L1 error, cross-entropy, and ROC surface plots are used as evaluation criteria comparing the priors with frequentist methods as Lasso, Elastic-Net, and Ridge regression.Results: All three priors can be used for robust prediction on significant metrics, irrespective of their categorical response model choices. Simulation studies could achieve the mean prediction accuracy of 91.6% (95% CI: 88.5, 94.7) and 76.5% (95% CI: 69.3, 83.8) for logistic regression and multinomial logistic models, respectively. The model can identify significant variables for disease risk prediction and is computationally efficient.Conclusions: The models are robust enough to conduct both variable selection and prediction because of their high shrinkage properties and applicability to a broad range of classification problems. [ABSTRACT FROM AUTHOR]

An important task in drug development is to identify patients, which respond better or worse to an experimental treatment. Identifying predictive covariates, which influence the treatment effect and can be used to define subgroups of patients, is a key aspect of this task. Analyses of treatment effect heterogeneity are however known to be challenging, since the number of possible covariates or subgroups is often large, while samples sizes in earlier phases of drug development are often small. In addition, distinguishing predictive covariates from prognostic covariates, which influence the response independent of the given treatment, can often be difficult. While many approaches for these types of problems have been proposed, most of them focus on the two‐arm clinical trial setting, where patients are given either the treatment or a control. In this article we consider parallel groups dose‐finding trials, in which patients are administered different doses of the same treatment. To investigate treatment effect heterogeneity in this setting we propose a Bayesian hierarchical dose–response model with covariate effects on dose–response parameters. We make use of shrinkage priors to prevent overfitting, which can easily occur, when the number of considered covariates is large and sample sizes are small. We compare several such priors in simulations and also investigate dependent modeling of prognostic and predictive effects to better distinguish these two types of effects. We illustrate the use of our proposed approach using a Phase II dose‐finding trial and show how it can be used to identify predictive covariates and subgroups of patients with increased treatment effects. [ABSTRACT FROM AUTHOR]

We study the dynamics of the three-dimensional quadratic diffeomorphism using a concept first introduced 30 years ago for the Frenkel--Kontorova model of condensed matter physics: the antiintegrable (AI) limit. At the traditional AI limit, orbits of a map degenerate to sequences of symbols and the dynamics is reduced to the shift operator, a pure form of chaos. Under nondegeneracy conditions, a contraction mapping argument can show that infinitely many AI states continue to orbits of the deterministic map. For the 3D quadratic map, the AI limit that we study is a quadratic correspondence whose branches, a pair of one-dimensional maps, introduce symbolic dynamics on two symbols. The AI states, however, are nontrivial orbits of this correspondence. The character of these orbits depends on whether the quadratic takes the form of an ellipse, a hyperbola, or a pair of lines. Using contraction arguments, we find parameter domains for each case such that each symbol sequence corresponds to a unique AI state. In some parameter domains, sufficient conditions are then found for each such AI state to continue away from the limit becoming an orbit of the original 3D map. Numerical continuation methods extend these results, allowing computation of bifurcations to obtain orbits with horseshoe-like structures and intriguing self-similarity. We conjecture that pairs of periodic orbits in saddle-node and period-doubling bifurcations have symbol sequences that differ in exactly one position. [ABSTRACT FROM AUTHOR]

We give a brief survey on the dynamics of vector fields with singularities. The aim of this survey is not to list all results in this field, but only to introduce some results from several viewpoints and some technics. [ABSTRACT FROM AUTHOR]

Antarctica plays a key role in the hydrological cycle of the Earth’s climate system, with an ice sheet that is the largest block of ice that reserves Earth’s 90% of total ice volume and 70% of fresh water. Furthermore, the sustainability of the region is an important concern due to the challenges posed by melting glaciers that preserve the Earth’s heat balance by interacting with the Southern Ocean. Therefore, the monitoring of glaciers based on advanced deep learning approaches offers vital outcomes that are of great importance in revealing the effects of global warming. In this study, recent deep learning approaches were investigated in terms of their accuracy for the segmentation of glacier landforms in the Antarctic Peninsula. For this purpose, high-resolution orthophotos were generated based on UAV photogrammetry within the Sixth Turkish Antarctic Expedition in 2022. Segformer, DeepLabv3+ and K-Net deep learning methods were comparatively analyzed in terms of their accuracy. The results showed that K-Net provided efficient results with 99.62% accuracy, 99.58% intersection over union, 99.82% precision, 99.76% recall and 99.79% F1-score. Visual inspections also revealed that K-Net was able to preserve the fine details around the edges of the glaciers. Our proposed deep-learning-based method provides an accurate and sustainable solution for automatic glacier segmentation and monitoring.

Pharmacogenetic variability in drug metabolism leads to patient vulnerability to side effects and to therapeutic failure. Our purpose was to introduce a systematic statistical methodology to estimate quantitative dose adjustments based on pharmacokinetic differences in pharmacogenetic subgroups, addressing the concerns of sparse data, incomplete information on phenotypic groups, and heterogeneity of study design. Data on psychotropic drugs metabolized by the cytochrome P450 enzyme CYP2C19 were used as a case study. CYP2C19 activity scores were estimated, while statistically assessing the influence of methodological differences between studies, and used to estimate dose adjustments in genotypic groups. Modeling effects of activity scores in each substance as a population led to prudential predictions of adjustments when few data were available (‘shrinkage’). The best results were obtained with the regularized horseshoe, an innovative Bayesian approach to estimate coefficients viewed as a sample from two populations. This approach was compared to modeling the population of substance as normally distributed, to a more traditional “fixed effects” approach, and to dose adjustments based on weighted means, as in current practice. Modeling strategies were able to assess the influence of study parameters and deliver adjustment levels when necessary, extrapolated to all phenotype groups, as well as their level of uncertainty. In addition, the horseshoe reacted sensitively to small study sizes, and provided conservative estimates of required adjustments.

Objectives: Extreme horseshoe anal fistulas are rare, and there are little data on the diagnosis and management of these fistulas. Materials and Methods: Patients with horseshoe anal fistula, in which the fistula tract encircled more than 75% of the anal circumference were included in the study. All patients were assessed by a preoperative magnetic resonance imaging (MRI). The patients were managed by a sphincter-sparing procedure. The continence was evaluated by an objective continence scoring system (Vaizey's scores). Results: 1059 anal fistula patients were operated on over 7-years with a median follow-up of 36 months (range: 5–79 months). There were 47/1059 (4.4%) patients with extreme horseshoe anal fistulas. In 4/47 patients, the fistulas were complete circumanal (encircling anal canal completely). The mean age was 39.5 ± 10.9 years, M/F-41/6. The fistula was supralevator in 12/47 (25.5%), had an associated abscess in 28/47 (59.6%), and was recurrent in 33/47 (70.2%) patients. The tracts were intersphincteric in 27/47, transsphincteric in 2/47, and both (intersphincteric and transsphincteric) in 18/47 patients. All patients (n = 47) were managed by a sphincter-sparing procedure. Four patients were lost to follow-up. The fistula healed completely in 34/43 (79%) patients. There was no significant difference between preoperative and postoperative Vaizey's continence scores 0.031 ± 0.17 and 0.033 ± 0.18 respectively (P=0.90, Mann–Whitney U-test). Conclusion: Extreme horseshoe fistulas are rare, with an incidence of about 4% (in a referral practice). The missed diagnosis of circumferential tracts could lead to a recurrence. MRI was pivotal to confirm the diagnosis. Proper identification and management of internal opening and adequate drainage of all tracts were crucial for successfully treating extreme horseshoe fistulas. [ABSTRACT FROM AUTHOR]