Isolation, immunolocalization, and sperm-association of three proteins of 18, 25, and 29 kilodaltons secreted by the mouse epididymis.

Three murine epididymal secretory proteins have been characterized by their site of synthesis, sperm association, and tissue localization by use of polyclonal antisera and immunochemistry. Mouse epididymal protein 7 (MEP 7) was localized initially within the supranuclear regions of some principal epithelial cells in the proximal corpus while other cells remained unstained. In the mid-proximal corpus, all principal cells and stereocilia were stained, and luminal staining increased from corpus to cauda. Some clear cells in the distal corpus and cauda also showed immunoperoxidase staining. Sequential extraction of caudal spermatozoa indicated that MEP 7 was predominantly loosely associated with spermatozoa and that only a small amount of MEP 7 required detergent to extract it from spermatozoa. Examination of other rodent caudal fluids revealed a related protein in rat caudal fluid of 32 kDa, and amino acid sequence analysis of MEP 7 showed a 68% sequence similarity with rat proteins AEG and D/E. MEP 9 immunolocalized within the cytoplasm of all principal cells of the distal caput. In a transition zone between the distal caput and the corpus, some principal cells were stained while others were not. Distal to the corpus, the principal cell staining gradually decreased. In the distal caput and proximal corpus, large heavily stained droplets associated with spermatozoa were seen in the lumen. The staining intensity of these droplets also decreased from corpus to cauda. The clear cells of the distal corpus and cauda did not stain with the antibody to MEP 9. Sequential extraction of caudal spermatozoa showed that some MEP 9 was extractable under low-salt conditions, whereas extraction with 0.1% Triton X-100 was required to remove all MEP 9, indicating it was firmly associated with spermatozoa. The antibody to MEP 9 cross-reacted with a 25-kDa protein present in rat caudal fluid. MEP 10 was localized within the cytoplasm of the principal cells, the stereocilia, and the lumen of the epididymis at the junction of the distal caput and corpus. In the distal corpus, a large number of clear cells were stained, but very few of these cells stained in the cauda. MEP 10 dissociated completely from caudal spermatozoa under low-salt conditions, indicating that it was not firmly bound to spermatozoa. The antiserum to MEP 10 cross-reacted with proteins present in rat and guinea pig caudal fluid. The related rat protein migrated at approximately 20 kDa. Amino acid sequence analysis of MEP 10 revealed an 86% sequence similarity with rat proteins B and C.(ABSTRACT TRUNCATED AT 400 WORDS)     

ON MISSING ENTRIES IN CLADISTIC ANALYSIS

Abstract The exact algorithms of two commonly used parsimony programs, Hennig86 by J. S. Farris and PAUP by D. Swofford, sometimes produce different solutions, and sometimes produce resolutions that are not supported by the data being analysed. The discrepancies apparently involve the treatment of missing entries, which can currently represent unknown data, inapplicable character and/or polymorphic taxa. Each of those potential sources of ambiguity is logically (if not computationally) different; with regard to binary characters, unknown data could be either 0 or 1, inapplicable characters are neither 0 nor 1 and polymorphisms are both 0 and 1. Resolutions that cannot be supported by any possible combination of known state attributions should either be flagged as such or suppressed entirely.     

Seminal transferrin and spermatogenic capability in the bull

The objective of this study was to determine the relationship between seminal transferrin and sperm output in ejaculates from mature dairy bulls. Caudal sperm reserves in mature Holstein bulls (n = 15) were depleted by 8 successive ejaculations during a 50-70-min period (depletion phase). Bulls were then ejaculated 6 times per week for a period of 4 weeks (6X phase). Weekly sperm output (WSO) and weekly transferrin output (WTfO) were the sums of sperm and transferrin levels in 6 ejaculates taken in 1 week of the study. Mean WSO ranged from 20.7 billion to 39.6 billion and mean WTfO ranged from 334 micrograms to 1872 micrograms among the bulls. Regression analysis of sperm and transferrin levels in ejaculates collected during the depletion phase indicated that approximately 40% of seminal transferrin was not related to sperm output and probably was from accessory fluids. A relationship between total seminal transferrin and total sperm in ejaculate was observed (p less than 0.01, r = 0.54). This relationship was stronger when the transferrin was corrected for accessory fluid contribution (p less than 0.01, r = 0.65). The relationship between WSO and WTfO corrected for accessory fluid transferrin contribution (cWTfO) was significant (p less than 0.01, r = 0.64). The relationship between WSO and cWTfO can be interpreted to reflect the relationship between actual testicular sperm production and transferrin from testicular or epididymal origin.     

Secreted proteins from rat Sertoli cells.

Sertoli cell cultures were prepared from the testes of 20-day-old rats. The proteins which were secreted by the cells into the culture medium were labeled with [³H]leucine or l-[³H]fucose. The proteins were concentrated by ultrafiltration and analysed by polyacrylamide slab gel electrophoresis (PAGE) in the presence of sodium dodecyl sulfate (SDS). Autofluorography of the gels at ?70 °C showed that the rat Sertoli cells synthesized and secreted at least 7 major polypeptides. The polypeptides had molecular weights ranging from 16 000 to 140 000 D. Proteins which were secreted from cultures of testicular fibroblasts and myoid cells had electrophoretic properties on SDS-PAGE which were different from Sertoli cell secreted proteins. Addition of FSH and testosterone to the Sertoli cell cultures increased the total synthesis and secretion of [³H]leucine-labeled proteins. No qualitative changes in the proteins as a result of hormone application could be detected. However, the synthesis of a polypeptide of molecular weight 48 000 was increased relative to the other secreted peptides if the cells were maintained in FSH and testosterone. The Sertoli cell secreted proteins were shown to be glycoproteins which can bind to ConA-Sepharose and can be labeled with [³H]fucose. Tunicamycin, a specific inhibitor of N-glycosylation, inhibited the secretion of [³H]proteins by 50% but had little effect on the intracellular protein synthesis.     

Moving towards the detection of frailty with biomarkers: A population health study

Aging adults experience increased health vulnerability and compromised abilities to cope with stressors, which are the clinical manifestations of frailty. Frailty is complex, and efforts to identify biomarkers to detect frailty and pre-frailty in the clinical setting are rarely reproduced across cohorts. We developed a predictive model incorporating biological and clinical frailty measures to identify robust biomarkers across data sets. Data were from two large cohorts of older adults: “Invecchiare in Chianti (Aging in Chianti, InCHIANTI Study”) (n = 1453) from two small towns in Tuscany, Italy, and replicated in the Atherosclerosis Risk in Communities Study (ARIC) (n = 6508) from four U.S. communities. A complex systems approach to biomarker selection with a tree-boosting machine learning (ML) technique for supervised learning analysis was used to examine biomarker population differences across both datasets. Our approach compared predictors with robust, pre-frail, and frail participants and examined the ability to detect frailty status by race. Unique biomarker features identified in the InCHIANTI study allowed us to predict frailty with a model accuracy of 0.72 (95% confidence interval (CI) 0.66–0.80). Replication models in ARIC maintained a model accuracy of 0.64 (95% CI 0.66–0.72). Frail and pre-frail Black participant models maintained a lower model accuracy. The predictive panel of biomarkers identified in this study may improve the ability to detect frailty as a complex aging syndrome in the clinical setting. We propose several concrete next steps to keep research moving toward detecting frailty with biomarker-based detection methods.     

A model of the physiological basis of a multivariate phenotype that is mediated by Ca(2+) signaling and controlled by ryanodine receptor composition

Calcium-signals occur in a wide variety of tissue types - from skeletal, smooth and cardiac muscle to pancreatic and brain tissues. Ca²⁺ signals regulate diverse processes including muscle contraction, hormone secretion, neural communication and gene expression. Together these different tissues and processes form the basis of a multivariate trait. Calcium signals are characterized by Ca²⁺ transients, which are sharp increases in Ca²⁺ concentration over a short period of time. In this paper we derive and analyze a model of Ca²⁺ transients for skeletal muscle, neurons and cardiac tissue based on underlying biophysical principles. Tissue differentiation in our model and in nature comes about by varying the ryanodine receptor (RyR) channel composition of tissues. In vertebrates, there are typically three types of RyR channels (labeled RyR1, RyR2 and RyR3 in mammals and α‐RyR, cardiac-RyR and β‐RyR in birds, amphibians and fish). Different compositions of these three RyR channels generate different Ca²⁺ transient properties. There are four Ca²⁺ transient properties that we measure: maximum amplitude, duration, half duration (D₅₀) and integrated concentration. In agreement with experimental work, our results find that the addition of RyR3 amplifies Ca²⁺ transients in skeletal muscle. An important consequence of shared molecular components between tissue types in a multivariate setting is that the shared components cause individual traits of a multivariate trait to be correlated in function. Here we show how correlations in Ca²⁺ transient properties between tissues can be predicted using an underlying biophysical model.     

Estimating Treatment Effects of Longitudinal Designs using Regression Models on Propensity Scores

Summary We derive regression estimators that can compare longitudinal treatments using only the longitudinal propensity scores as regressors. These estimators, which assume knowledge of the variables used in the treatment assignment, are important for reducing the large dimension of covariates for two reasons. First, if the regression models on the longitudinal propensity scores are correct, then our estimators share advantages of correctly specified model‐based estimators, a benefit not shared by estimators based on weights alone. Second, if the models are incorrect, the misspecification can be more easily limited through model checking than with models based on the full covariates. Thus, our estimators can also be better when used in place of the regression on the full covariates. We use our methods to compare longitudinal treatments for type II diabetes mellitus.