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Endometrial cancer is the most common gynecologic malignancy. It is the fourth most common cancer in women in the United States after breast, lung, and colorectal cancers. Risk factors are related to excessive unopposed exposure of the endometrium to estrogen, including unopposed estrogen therapy, early menarche, late menopause, tamoxifen therapy, nulliparity, infertility or failure to ovulate, and polycystic ovary syndrome. Additional risk factors are increasing age, obesity, hypertension, diabetes mellitus, and hereditary nonpolyposis colorectal cancer. The most common presentation for endometrial cancer is postmenopausal bleeding. The American Cancer Society recommends that all women older than 65 years be informed of the risks and symptoms of endometrial cancer and advised to seek evaluation if symptoms occur. There is no evidence to support endometrial cancer screening in asymptomatic women. Evaluation of a patient with suspected disease should include a pregnancy test in women of childbearing age, complete blood count, and prothrombin time and partial thromboplastin time if bleeding is heavy. Most guidelines recommend either transvaginal ultrasonography or endometrial biopsy as the initial study. The mainstay of treatment for endometrial cancer is total hysterectomy with bilateral salpingo-oophorectomy. Radiation and chemotherapy can also play a role in treatment. Low- to medium-risk endometrial hyperplasia can be treated with nonsurgical options. Survival is generally defined by the stage of the disease and histology, with most patients at stage I and II having a favorable prognosis. Controlling risk factors such as obesity, diabetes, and hypertension could play a role in the prevention of endometrial cancer.

Phylogenomics, the use of large-scale data matrices in phylogenetic analyses, has been viewed as the ultimate solution to the problem of resolving difficult nodes in the tree of life. However, it has become clear that analyses of these large genomic data sets can also result in conflicting estimates of phylogeny. Here, we use the early divergences in Neoaves, the largest clade of extant birds, as a \"model system\" to understand the basis for incongruence among phylogenomic trees. We were motivated by the observation that trees from two recent avian phylogenomic studies exhibit conflicts. Those studies used different strategies: 1) collecting many characters [∼42 mega base pairs (Mbp) of sequence data] from 48 birds, sometimes including only one taxon for each major clade; and 2) collecting fewer characters (∼0.4 Mbp) from 198 birds, selected to subdivide long branches. However, the studies also used different data types: the taxon-poor data matrix comprised 68% non-coding sequences whereas coding exons dominated the taxon-rich data matrix. This difference raises the question of whether the primary reason for incongruence is the number of sites, the number of taxa, or the data type. To test among these alternative hypotheses we assembled a novel, large-scale data matrix comprising 90% non-coding sequences from 235 bird species. Although increased taxon sampling appeared to have a positive impact on phylogenetic analyses the most important variable was data type. Indeed, by analyzing different subsets of the taxa in our data matrix we found that increased taxon sampling actually resulted in increased congruence with the tree from the previous taxon-poor study (which had a majority of non-coding data) instead of the taxon-rich study (which largely used coding data). We suggest that the observed differences in the estimates of topology for these studies reflect data-type effects due to violations of the models used in phylogenetic analyses, some of which may be difficult to detect. If incongruence among trees estimated using phylogenomic methods largely reflects problems with model fit developing more \"biologically-realistic\" models is likely to be critical for efforts to reconstruct the tree of life.

Hyponatremia and hypernatremia are common findings in the inpatient and outpatient settings. Sodium disorders are associated with an increased risk of morbidity and mortality. Plasma osmolality plays a critical role in the pathophysiology and treatment of sodium disorders. Hyponatremia and hypernatremia are classified based on volume status (hypovolemia, euvolemia, and hypervolemia). Sodium disorders are diagnosed by findings from the history, physical examination, laboratory studies, and evaluation of volume status. Treatment is based on symptoms and underlying causes. In general, hyponatremia is treated with fluid restriction (in the setting of euvolemia), isotonic saline (in hypovolemia), and diuresis (in hypervolemia). A combination of these therapies may be needed based on the presentation. Hypertonic saline is used to treat severe symptomatic hyponatremia. Medications such as vaptans may have a role in the treatment of euvolemic and hypervolemic hyponatremia. The treatment of hypernatremia involves correcting the underlying cause and correcting the free water deficit.

Pediatric liver failure patients frequently develop multiple organ failure and require continuous renal replacement therapy (CRRT) as part of supportive therapy in the pediatric intensive care unit. While many centers employ no anticoagulation for fear of bleeding complications, balanced coagulation disturbance predisposes these patients to clotting as well as bleeding, making maintenance of longer circuit life to deliver adequate dialysis clearance challenging. Regional citrate anticoagulation (RCA) is an attractive option as it avoids systemic anticoagulation, but since citrate metabolism is impaired in liver failure, concerns about toxicity has limited its use. Pediatric data on RCA with liver failure is very scarce. We aimed to establish safety and efficacy of RCA in pediatric liver failure patients on CRRT. Retrospective review of pediatric patients with liver failure receiving CRRT over 30 months. Demographic data and CRRT related data were collected by chart review. Citrate accumulation (CA) was defined as total calcium (mg/dl) /ionized calcium (mmol/L) ratio >2.5 for > 48 hours. Efficacy was assessed by filter life. Safety was assessed by frequency of adverse events ((AEs) defined as bleeding, hemodynamic instability, arrhythmias). Fifty-one patients (median age 3.5 (IQR 0.75-14.2) years) received 861 CRRT days; 70% experienced at least one episode of CA, only 37% were recorded as such in the medical record. AE rate was 93/1000 CRRT days and did not differ between CA days and others. Median filter life was 66 hours (IQR 29-74); 63% filters lasted longer than 48 hrs. Though common, CA was not associated with increased AEs on in pediatric liver failure patients on CRRT receiving RCA. Filter life was adequate. RCA appears an effective anticoagulation for CRRT in pediatric liver failure. Application of a structured definition would increase recognition of CA to allow timely intervention.

It has long been appreciated that analyses of genomic data (e.g., whole genome sequencing or sequence capture) have the potential to reveal the tree of life, but it remains challenging to move from sequence data to a clear understanding of evolutionary history, in part due to the computational challenges of phylogenetic estimation using genome-scale data. Supertree methods solve that challenge because they facilitate a divide-and-conquer approach for large-scale phylogeny inference by integrating smaller subtrees in a computationally efficient manner. Here, we combined information from sequence capture and whole-genome phylogenies using supertree methods. However, the available phylogenomic trees had limited overlap so we used taxon-rich (but not phylogenomic) megaphylogenies to weave them together. This allowed us to construct a phylogenomic supertree, with support values, that included 707 bird species (~7% of avian species diversity). We estimated branch lengths using mitochondrial sequence data and we used these branch lengths to estimate divergence times. Our time-calibrated supertree supports radiation of all three major avian clades (Palaeognathae, Galloanseres, and Neoaves) near the Cretaceous-Paleogene (K-Pg) boundary. The approach we used will permit the continued addition of taxa to this supertree as new phylogenomic data are published, and it could be applied to other taxa as well.

Drivers in negative emotional states, such as anger or sadness, are prone to perform bad at driving, decreasing overall road safety for all road users. Recent advances in affective computing, however, allow for the detection of such states and give us tools to tackle the connected problems within automotive user interfaces. We see potential in building a system which reacts upon possibly dangerous driver states and influences the driver in order to drive more safely. We compare different interaction approaches for an affective automotive interface, namely Ambient Light, Visual Notification, a Voice Assistant, and an Empathic Assistant. Results of a simulator study with 60 participants (30 each with induced sadness/anger) indicate that an emotional voice assistant with the ability to empathize with the user is the most promising approach as it improves negative states best and is rated most positively. Qualitative data also shows that users prefer an empathic assistant but also resent potential paternalism. This leads us to suggest that digital assistants are a valuable platform to improve driver emotions in automotive environments and thereby enable safer driving.

Nanobodies are highly valuable tools for numerous bioanalytical and biotechnical applications. Here, we report the characterization of a nanobody that binds a short peptide epitope with extraordinary affinity. Structural analysis reveals an unusual binding mode where the extended peptide becomes part of a β-sheet structure in the nanobody. This interaction relies on sequence-independent backbone interactions augmented by a small number of specificity-determining side chain contacts. Once bound, the peptide is fastened by two nanobody side chains that clamp it in a headlock fashion. Exploiting this unusual binding mode, we generated a novel nanobody-derived capture and detection system. Matrix-coupled nanobody enables the fast and efficient isolation of epitope-tagged proteins from prokaryotic and eukaryotic expression systems. Additionally, the fluorescently labeled nanobody visualizes subcellular structures in different cellular compartments. The high-affinity-binding and modifiable peptide tag of this system renders it a versatile and robust tool to combine biochemical analysis with microscopic studies.

Deep avian evolutionary relationships have been difficult to resolve as a result of a putative explosive radiation. Our study examined ~32 kilobases of aligned nuclear DNA sequences from 19 independent loci for 169 species, representing all major extant groups, and recovered a robust phylogeny from a genome-wide signal supported by multiple analytical methods. We documented well-supported, previously unrecognized interordinal relationships (such as a sister relationship between passerines and parrots) and corroborated previously contentious groupings (such as flamingos and grebes). Our conclusions challenge current classifications and alter our understanding of trait evolution; for example, some diurnal birds evolved from nocturnal ancestors. Our results provide a valuable resource for phylogenetic and comparative studies in birds.

Discrete choice models are commonly used by applied statisticians in numerous fields, such as marketing, economics, finance, and operations research. When agents in discrete choice models are assumed to have differing preferences, exact inference is often intractable. Markov chain Monte Carlo techniques make approximate inference possible, but the computational cost is prohibitive on the large datasets now becoming routinely available. Variational methods provide a deterministic alternative for approximation of the posterior distribution. We derive variational procedures for empirical Bayes and fully Bayesian inference in the mixed multinomial logit model of discrete choice. The algorithms require only that we solve a sequence of unconstrained optimization problems, which are shown to be convex. One version of the procedures relies on a new approximation to the variational objective function, based on the multivariate delta method. Extensive simulations, along with an analysis of real-world data, demonstrate that variational methods achieve accuracy competitive with Markov chain Monte Carlo at a small fraction of the computational cost. Thus, variational methods permit inference on datasets that otherwise cannot be analyzed without possibly adverse simplifications of the underlying discrete choice model. Appendices C through F are available as online supplemental materials.

The authors present an overview of lower urinary tract obstruction (LUTO) in the fetus with a particular focus on the insult to the developing renal system. Diagnostic criteria along with the challenges in estimating long-term prognosis are reviewed. A proposed prenatal LUTO disease severity classification to guide management decisions with fetal intervention to maintain or salvage in utero and neonatal pulmonary and renal function is also discussed. Stage I LUTO (mild form) is characterized by normal amniotic fluid index after 18 weeks, normal kidney echogenicity, no renal cortical cysts, no evidence of renal dysplasia, and favorable urinary biochemistries when sampled between 18 and 30 weeks; prenatal surveillance is recommended. Stage II LUTO is characterized by oligohydramnios/anhydramnios, hyperechogenic kidneys but absent renal cortical cysts or apparent signs of renal dysplasia and favorable fetal urinary biochemistry; fetal vesicoamniotic shunting (VAS) or fetal cystoscopy is indicated to prevent pulmonary hypoplasia and renal failure. Stage III LUTO is oligohydramnios/anhydramnios, hyperechogenic kidneys with cortical cysts and renal dysplasia and unfavorable fetal urinary biochemistry after serial evaluation; fetal vesicoamniotic shunt may prevent severe pulmonary hypoplasia but not renal failure. Stage IV is characterized by intrauterine fetal renal failure, defined by anhydramnios and ultrasound (US) findings suggestive of severe renal dysplasia, and is associated with death in 24 h of life or end-stage renal disease (ESRD) within the first week of life; fetal vesicoamniotic shunt and fetal cystoscopy are not indicated.