Susceptibility of sperm chromatin to acid denaturation in situ: A study in endogenous FSH-deprived adult male bonnet monkeys (Macaca radiata)

Acid denaturation of calf thymus DNA in vitro followed by acridine orange (AO) binding induced a 112% increase in the emission of red, a 58% decrease in green, and a consequential decrease in the ratio of green:red fluorescences from 1.7 to 0.9. This metachromatic property of AO on binding to DNA following acid denaturation was utilized to study the susceptibility of normal and ovine follicle-stimulating hormone (oFSH) actively immunized bonnet monkey spermatozoa voided throughout the year. For analyses, the scattergram generated by the emission of red and green fluorescences by 10,000 AO-bound sperm from each semen sample was divided into 4 quadrant zones representing percentage cells fluorescing high green-low red (Q1), high green-high red (Q2), low green-low red (Q3) and low green-high red. (Q4). Normal monkey sperm obtained during the months of July-December exhibited 76, 13, and 11% cells in Q2, Q3, and Q4 quadrants, respectively. However, during January-June, when the females of the species are markedly subfertile, noncycling, and amenorrhoeic, the spermatozoa ejaculated by the male monkeys exhibited 38, 39, and 23% sperm in Q2, Q3, and Q4, respectively, the differences being highly significant (p < .01-.001). FSH deprivation induced significant shifts in fluorescence emissions, from respective controls, with 39, 33, and 28% cells in Q2, Q3, and Q4, respectively, during July-December, and 15, 48, and 37% sperm in Q2, Q3, and Q4 quadrants, respectively, during January-June. It is postulated that the altered kinetics of germ cell transformations and the deficient spermiogenesis observed earlier following FSH deprivation in these monkeys may have induced the enhanced susceptibility to acid denaturation in sperm.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Evaluation of mechanical losses in a linear motor pressure wave generator

A moving magnet linear motor compressor or pressure wave generator (PWG) of 2 cc swept volume with dual opposed piston configuration has been developed to operate miniature pulse tube coolers. Prelimnary experiments yielded only a no-load cold end temperature of 180 K. Auxiliary tests and the interpretation of detailed modeling of a PWG suggest that much of the PV power has been lost in the form of blow-by at piston seals due to large and non-optimum clearance seal gap between piston and cylinder. The results of experimental parameters simulated using Sage provide the optimum seal gap value for maximizing the delivered PV power.

Queuing of concurrent movement plans by Basal Ganglia

How the brain converts parallel representations of movement goals into sequential movements is not known. We tested the role of basal ganglia (BG) in the temporal control of movement sequences by a convergent approach involving inactivation of the BG by muscimol injections into the caudate nucleus of monkeys and assessing behavior of Parkinson's disease patients, performing a modified double-step saccade task. We tested a critical prediction of a class of competitive queuing models that explains serial behavior as the outcome of a selection of concurrently activated goals. In congruence with these models, we found that inactivation or impairment of the BG unmasked the parallel nature of goal representations such that a significantly greater extent of averaged saccades, curved saccades, and saccade sequence errors were observed. These results suggest that the BG perform a form of competitive queuing, holding the second movement plan in abeyance while the first movement is being executed, allowing the proper temporal control of movement sequences.

Classification calibration dimension for general multiclass losses

We study consistency properties of surrogate loss functions for general multiclass classification problems, defined by a general loss matrix. We extend the notion of classification calibration, which has been studied for binary and multiclass 0-1 classification problems (and for certain other specific learning problems), to the general multiclass setting, and derive necessary and sufficient conditions for a surrogate loss to be classification calibrated with respect to a loss matrix in this setting. We then introduce the notion of \emph{classification calibration dimension} of a multiclass loss matrix, which measures the smallest `size' of a prediction space for which it is possible to design a convex surrogate that is classification calibrated with respect to the loss matrix. We derive both upper and lower bounds on this quantity, and use these results to analyze various loss matrices. In particular, as one application, we provide a different route from the recent result of Duchi et al.\ (2010) for analyzing the difficulty of designing `low-dimensional' convex surrogates that are consistent with respect to pairwise subset ranking losses. We anticipate the classification calibration dimension may prove to be a useful tool in the study and design of surrogate losses for general multiclass learning problems.

Extension of TSVM to multi-class and hierarchical text classification problems With general losses

Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.

An Efficient Probe for Rapid Detection of Cyanide in Water at Parts per Billion Levels and Naked-Eye Detection of Endogenous Cyanide

A new molecular probe based on an oxidized bis-indolyl skeleton has been developed for rapid and sensitive visual detection of cyanide ions in water and also for the detection of endogenously bound cyanide. The probe allows the naked-eye detection of cyanide ions in water with a visual color change from red to yellow ((max)=80nm) with the immediate addition of the probe. It shows high selectivity towards the cyanide ion without any interference from other anions. The detection of cyanide by the probe is ratiometric, thus making the detection quantitative. A Michael-type addition reaction of the probe with the cyanide ion takes place during this chemodosimetric process. In water, the detection limit was found to be at the parts per million level, which improved drastically when a neutral micellar medium was employed, and it showed a parts-per-billion-level detection, which is even 25-fold lower than the permitted limits of cyanide in water. The probe could also efficiently detect the endogenously bound cyanide in cassava (a staple food) with a clear visual color change without requiring any sample pretreatment and/or any special reaction conditions such as pH or temperature. Thus the probe could serve as a practical naked-eye probe for in-field experiments without requiring any sophisticated instruments.

Regioselective Deiodination of Iodothyronamines, Endogenous Thyroid Hormone Derivatives, by Deiodinase Mimics

Iodothyronine deiodinases (IDs) are mammalian selenoenzymes that play an important role in the activation and inactivation pound of thyroid hormones. It is known that iodothyronamines (TnAMs), produced by the decarboxylation of thyroid hormones, act as substrates for deiodinases. To understand whether decarboxylation alters the rate and/or regioselectivity of deiodination by using synthetic deiodinase mimics, we studied the deiodination of different iodothyronamines. The triiodo derivative 3,3',5-triiodothyronamine (T3AM) is deiodinated at the inner ring by naphthyl-based deiodinase mimics, which is similar to the deiodination of 3,3',5-triiodothyronine (T3). However, T3AM under-goes much slower deiodination than T3. Detailed experimental and theoretical investigations suggest that T3AM forms a weaker halogen bond with selenium donors than T3. Kinetic studies and single-crystal X-ray structures of T3 and T3AM reveal that intermolecular I center dot center dot center dot I interactions may play an important role in deiodination. The formation of hydrogen- and halogen-bonding assemblies, which leads to the formation of a dimeric species of T3 in solution, facilitates the interactions between the selenium and iodine atoms. In contrast, T3AM, which does not have I center dot center dot I interactions, undergoes much slower deiodination.

Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses

The problem of bipartite ranking, where instances are labeled positive or negative and the goal is to learn a scoring function that minimizes the probability of mis-ranking a pair of positive and negative instances (or equivalently, that maximizes the area under the ROC curve), has been widely studied in recent years. A dominant theoretical and algorithmic framework for the problem has been to reduce bipartite ranking to pairwise classification; in particular, it is well known that the bipartite ranking regret can be formulated as a pairwise classification regret, which in turn can be upper bounded using usual regret bounds for classification problems. Recently, Kotlowski et al. (2011) showed regret bounds for bipartite ranking in terms of the regret associated with balanced versions of the standard (non-pairwise) logistic and exponential losses. In this paper, we show that such (non-pairwise) surrogate regret bounds for bipartite ranking can be obtained in terms of a broad class of proper (composite) losses that we term as strongly proper. Our proof technique is much simpler than that of Kotlowski et al. (2011), and relies on properties of proper (composite) losses as elucidated recently by Reid and Williamson (2010, 2011) and others. Our result yields explicit surrogate bounds (with no hidden balancing terms) in terms of a variety of strongly proper losses, including for example logistic, exponential, squared and squared hinge losses as special cases. An important consequence is that standard algorithms minimizing a (non-pairwise) strongly proper loss, such as logistic regression and boosting algorithms (assuming a universal function class and appropriate regularization), are in fact consistent for bipartite ranking; moreover, our results allow us to quantify the bipartite ranking regret in terms of the corresponding surrogate regret. We also obtain tighter surrogate bounds under certain low-noise conditions via a recent result of Clemencon and Robbiano (2011).

Mycobacterium tuberculosis has diminished capacity to counteract redox stress induced by elevated levels of endogenous superoxide

Mycobacterium tuberculosis (Mtb) has evolved protective and detoxification mechanisms to maintain cytoplasmic redox balance in response to exogenous oxidative stress encountered inside host phagocytes. In contrast, little is known about the dynamic response of this pathogen to endogenous oxidative stress generated within Mtb. Using a noninvasive and specific biosensor of cytoplasmic redox state of Mtb, we for first time discovered a surprisingly high sensitivity of this pathogen to perturbation in redox homeostasis induced by elevated endogenous reactive oxygen species (ROS). We synthesized a series of hydroquinone-based small molecule ROS generators and found that ATD-3169 permeated mycobacteria to reliably enhance endogenous ROS including superoxide radicals. When Mtb strains including multidrug-resistant (MDR) and extensively drug-resistant (XDR) patient isolates were exposed to this compound, a dose-dependent, long-lasting, and irreversible oxidative shift in intramycobacterial redox potential was detected. Dynamic redox potential measurements revealed that Mtb had diminished capacity to restore cytoplasmic redox balance in comparison with Mycobacterium smegmatis (Msm), a fast growing nonpathogenic mycobacterial species. Accordingly, Mtb strains were extremely susceptible to inhibition by ATD-3169 but not Msm, suggesting a functional linkage between dynamic redox changes and survival. Microarray analysis showed major realignment of pathways involved in redox homeostasis, central metabolism, DNA repair, and cell wall lipid biosynthesis in response to ATD-3169, all consistent with enhanced endogenous ROS contributing to lethality induced by this compound. This work provides empirical evidence that the cytoplasmic redox poise of Mtb is uniquely sensitive to manipulation in steady-state endogenous ROS levels, thus revealing the importance of targeting intramycobacterial redox metabolism for controlling TB infection. (C) 2015 The Authors. Published by Elsevier Inc.

Low thermal conductivity of endogenous manganese silicide/Si composites for thermoelectricity

Higher manganese silicide (HMS) based alloys with eutectic composition (Si-33.3 at% Mn) were prepared by arc-melting, melt-spinning and ball milling in order to evaluate the effect of microstructure on the thermal conductivity. Powder X-ray diffraction, SEM, EPMA and TEM analysis confirmed the presence of Si as a secondary phase distributed in the HMS matrix phase. Thermal properties of the samples were studied in the temperature range of 300-800 K. The microstructure refinement resulting from ball milling leads to a decrease of the thermal conductivity from 4.4 W/mK to 1.9 W/mK, whereas meltspinning is inefficient to this respect. The results show an opportunity to produce bulk higher manganese silicide alloys with reduced thermal conductivity in order to enhance its thermoelectric performance. (C) 2015 Elsevier B.V. All rights reserved.

Thermal conductivity of beta-FeSi2/Si endogenous composites formed by the eutectoid decomposition of alpha-Fe2Si5

Thermoelectric properties of semiconducting beta-FeSi2 containing a homogeneous distribution of Si secondary phase have been studied. The synthesis was carried out using arc melting followed by the densification by uniaxial hot pressing. Endogenous beta-FeSi2/Si composites were produced by the eutectoid decomposition of high-temperature alpha-Fe2Si5 phase. The aging heat treatments have been carried out at various temperatures below the equilibrium eutectoid temperature for various durations in order to tune the size of the eutectoid product. Thermal properties of the samples were studied in the temperature range of 100-350 A degrees C. The microstructural investigations support the fact that the finest microstructure generated through the eutectoid decomposition of the alpha-Fe2Si5 metastable phase is responsible of the phonon scattering. The results suggest an opportunity to produce bulk iron silicide alloys with reduced thermal conductivity in order to enhance its thermoelectric performance.

Novel PARP inhibitors sensitize human leukemic cells in an endogenous PARP activity dependent manner

Poly(ADP-ribose) polymerase (PARP) is a critical nuclear enzyme which safeguards genome stability from genotoxic insults and helps in DNA repair. Inhibition of PARP results in sustained DNA damage in cancer cells. PARP inhibitors are known to play an important role in chemotherapy as single agents in many DNA repair pathway deficient tumor cells or in combination with several other chemotherapeutic agents. In the present study, we synthesize and characterize novel pyridazine derivatives, and evaluate their potential for use as PARP inhibitors. Results show that pyridazine derivatives inhibited the PARP1 enzymatic activity at the nanomolar range and showed anti-proliferative activity in leukemic cells. Interestingly, human leukemic cell line, Nalm6, in which PARP1 and PARP2 expression as well as intrinsic PARP activity are high, showed significant sensitivity for the novel inhibitors compared to other leukemic cells. Among the inhibitors, P10 showed maximum inhibition of intrinsic PARP activity and inhibited cell proliferation in Nalm6 cells. Besides P10 also showed maximum inhibition against purified PARP1 protein, which was comparable to olaparib in our assays. Newly synthesized compounds also showed remarkable DNA trapping ability, which is a signature feature of many PARP inhibitors. Importantly, P10 also induced late S and G2/M arrest in Nalm6 cells, indicating accumulation of DNA damage. Therefore, we identify P10 as a potential PARP inhibitor, which can be developed as a chemotherapeutic agent.