University of Massachusetts Amherst

About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.

Increasing insulin resistance is associated with a decrease in Leydig cell testosterone secretion in men.

Abstract: Insulin resistance is associated with low testosterone (T) levels in men, the mechanism of which is unclear. Thus, the aim of this study was to evaluate the hypothalamic-pituitary-gonadal axis in men with a spectrum of insulin sensitivity. Twenty-one men (aged 25-65 yr) had a glucose tolerance test and assessment of insulin sensitivity using a hyperinsulinemic-euglycemic clamp. Insulin sensitivity, expressed as the M value (milligrams per kilograms(-1) per minute(-1)), was calculated from the glucose disposal rate during the final 30 min of the clamp. Eighteen subjects had blood sampling every 10 min for 12 h to assess LH pulsatility. Hypogonadism was then induced with a GnRH antagonist, followed by sequential stimulation testing with GnRH (750 ng/kg, iv) and human chorionic gonadotropin (hCG; 1000 IU, im) to assess pituitary and testicular responsiveness, respectively. Nine subjects had normal glucose tolerance, nine had impaired glucose tolerance, and three had diabetes mellitus. There was a positive relationship between M and T levels (r = 0.46; P < 0.05). No relationship was seen between M and parameters of LH secretion, including mean LH levels, LH pulse amplitude, LH pulse frequency, and LH response to exogenous GnRH administration. In contrast, a strong correlation was observed between M and the T response to hCG (r = 0.73; P < 0.005). Baseline T levels correlated with the increase in T after hCG administration (r = 0.47; P < 0.05). During the clamp, T levels increased from a baseline level of 367 +/- 30 to 419 +/- 38 ng/dl during the last 30 min (P < 0.05). From these data we conclude that insulin resistance is associated with a decrease in Leydig cell T secretion in men. Additional studies are required to determine the mechanism of this effect.

Combining classifiers in text categorization

Abstract: Three different types of classifiers were investigatedin the context of a text categorization problem in the medical domain: the automatic assignment of ICD9 codes to dictated inpatient discharge summaries. K-nearest-neighbor, relevance feedback, and Bayesian independence classifiers were applied individually and in combination. A coknbination of different classifiers produced better results than any single type of classifier. For this specific medical categorization problem, new query formulation and weighting methods used in the k-nearest-neighbor classifier improved performance.

Evaluation of clonal herbs of Lamiaceae species for management of diabetes and hypertension.

Abstract: In the current study, we screened 7 clonal lines from single seed phenotypes of Lamiaceae family for the inhibition of alpha-amylase, alpha-glucosidase and angiotensin converting enzyme (ACE) inhibitory activity. Water extracts of oregano had the highest alpha-glucosidase inhibition activity (93.7%), followed by chocolate mint (85.9%) and lemon balm (83.9%). Sage (78.4 %), and three different clonal lines of rosemary: rosemary LA (71.4%), rosemary 6 (68.4%) and rosemary K-2 (67.8%) also showed significant alpha-glucosidase inhibitory activity. The alpha-glucosidase inhibitory activity of the extracts was compared to selected specific phenolics detected in the extracts using HPLC. Catechin had the highest alpha-glucosidase inhibitiory activity (99.6 %) followed by caffeic acid (91.3 %), rosmarinic acid (85.1%) and resveratrol (71.1 %). Catechol (64.4%), protocatechuic acid (55.7%) and quercetin (36.9%) also exhibited significant alpha-glucosidase inhibitory activity. Results suggested that alpha-glucosidase inhibitory activity of the clonal extracts correlated to the phenolic content, antioxidant activity and phenolic profile of the extracts. The clonal extracts of the herbs and standard phenolics tested in this study did not have any effect on the alpha-amylase activity. We also investigated the ability of the clonal extracts to inhibit rabbit lung angiotensin I-converting enzyme (ACE). The water extracts of rosemary, rosemary LA had the highest ACE inhibitory activity (90.5%), followed by lemon balm (81.9%) and oregano (37.4 %). Lower levels of ACE inhibition were observed with ethanol extracts of oregano (18.5 %) and lemon balm (0.5 %). Among the standard phenolics only resveratrol (24.1 %), hydroxybenzoic acid (19.3 %) and coumaric acid (2.3 %) had ACE inhibitory activity.

Efficiently inducing features of conditional random fields

Abstract: Conditional Random Fields (CRFs) are undirected graphical models, a special case of which correspond to conditionally-trained finite state machines. A key advantage of CRFs is their great flexibility to include a wide variety of arbitrary, non-independent features of the input. Faced with this freedom, however, an important question remains: what features should be used? This paper presents an efficient feature induction method for CRFs. The method is founded on the principle of iteratively constructing feature conjunctions that would significantly increase conditional log-likelihood if added to the model. Automated feature induction enables not only improved accuracy and dramatic reduction in parameter count, but also the use of larger cliques, and more freedom to liberally hypothesize atomic input variables that may be relevant to a task. The method applies to linear-chain CRFs, as well as to more arbitrary CRF structures, such as Relational Markov Networks, where it corresponds to learning clique templates, and can also be understood as supervised structure learning. Experimental results on named entity extraction and noun phrase segmentation tasks are presented.

Genomic evidence for the Pleistocene and recent population history of Native Americans

Abstract: How and when the Americas were populated remains contentious. Using ancient and modern genome-wide data, we found that the ancestors of all present-day Native Americans, including Athabascans and Amerindians, entered the Americas as a single migration wave from Siberia no earlier than 23 thousand years ago (ka) and after no more than an 8000-year isolation period in Beringia. After their arrival to the Americas, ancestral Native Americans diversified into two basal genetic branches around 13 ka, one that is now dispersed across North and South America and the other restricted to North America. Subsequent gene flow resulted in some Native Americans sharing ancestry with present-day East Asians (including Siberians) and, more distantly, Australo-Melanesians. Putative "Paleoamerican" relict populations, including the historical Mexican Pericues and South American Fuego-Patagonians, are not directly related to modern Australo-Melanesians as suggested by the Paleoamerican Model.