Rhodium-Catalyzed Asymmetric Conjugate Addition of Arylboronic Acids to Nitroalkenes Using Olefin–Sulfoxide Ligands

An efficient rhodium/olefin–sulfoxide catalyzed asymmetric conjugate addition of organoboronic acids to a variety of nitroalkenes has been developed, where 2-methoxy-1-naphthyl sulfinyl functionalized olefin ligands have shown to be highly effective and are applicable to a broad scope of aryl, alkyl, and heteroaryl nitroalkenes

Adsorption Equilibrium, Kinetics, and Thermodynamic Studies of Cefpirome Sulfate by Using Macroporous Resin

The adsorption thermodynamics, kinetics, and isotherm parameters of cefpirome sulfate in aqueous solution on macroporous resin (XAD-16) were studied. Using static equilibrium tests, the fitting of resin adsorption data were calculated by the isothermal adsorption model. The fitting results show that Freundlich equation can adequately fit the adsorption isotherm. Meanwhile, the derived adsorption constants and their temperature dependencies from Freundlich isotherm had been used to calculate the corresponding thermodynamic quantities, such as the free energy of adsorption, heat, and entropy of adsorption. The thermodynamic data indicated that XAD-16 resin adsorption of cefpirome sulfate in aqueous solution was a spontaneous exothermic process, which was characterized by physical adsorption. The influences of initial concentration, bed height, and residence time on the breakthrough curve were examined by dynamic tests and the optimal parameters were defined

Behavioral results.

<p>The averaged accuracy (A) and reaction time (B) for each repetition during initial acquisition and reversal were plotted, separately for reward and punishment conditions. Error bars indicate one standardized error (SE). The scatter plots show the correlation of performance (accuracy) between reward and punishment during initial acquisition (C) and subsequent reversal learning (D).</p

Brain activation associated with the inhibition of old contingency and the expression of new behaviors (correct reversal > correct acquisition).

<p>Significant activation for reward (A), punishment (B) and their conjunction (C), are overlaid on axial slices of the group mean structural image. All activations were thresholded by using cluster detection statistics, with a height threshold of z>2.3 and a cluster probability of P<0.05, corrected for whole-brain multiple comparisons.</p

Common Neural Mechanisms Underlying Reversal Learning by Reward and Punishment

<div><p>Impairments in flexible goal-directed decisions, often examined by reversal learning, are associated with behavioral abnormalities characterized by impulsiveness and disinhibition. Although the lateral orbital frontal cortex (OFC) has been consistently implicated in reversal learning, it is still unclear whether this region is involved in negative feedback processing, behavioral control, or both, and whether reward and punishment might have different effects on lateral OFC involvement. Using a relatively large sample (N = 47), and a categorical learning task with either monetary reward or moderate electric shock as feedback, we found overlapping activations in the right lateral OFC (and adjacent insula) for reward and punishment reversal learning when comparing correct reversal trials with correct acquisition trials, whereas we found overlapping activations in the right dorsolateral prefrontal cortex (DLPFC) when negative feedback signaled contingency change. The right lateral OFC and DLPFC also showed greater sensitivity to punishment than did their left homologues, indicating an asymmetry in how punishment is processed. We propose that the right lateral OFC and anterior insula are important for transforming affective feedback to behavioral adjustment, whereas the right DLPFC is involved in higher level attention control. These results provide insight into the neural mechanisms of reversal learning and behavioral flexibility, which can be leveraged to understand risky behaviors among vulnerable populations.</p></div

Experimental design.

<p>(A) Trial structure and feedback schedule. Participants were presented with an abstract image and had up to 1 s to make a category judgment (left or right key). Under the reward condition, they received 1 point for a correct response but otherwise nothing; under the punishment condition, they received a moderate shock for each wrong response but otherwise nothing. Under both conditions, they also received information feedback (blue frame for correct responses and red frame for wrong responses). The feedback lasted for 0.7 s, which was followed by a fixation cross for an average ISI of 3 s (taken from an exponential distribution ranging from 2.5 to 7.8 s). (B) Reversal learning paradigm. Trials were presented in mini-blocks of 4 images (two new images as acquisition trials and two old images from the last block as reversal trials) that were repeated 5 times. To prevent subjects from being able to predict reversals, the new images might be repeated an additional 0,1, 2 or 3 times before the contingency was reversed. The images were then phased out of the experiment after 5 post-reversal repetitions. We compared the first error (1E) between reversal and acquisition to examine the neural regions involved in the detection of contingency change. In contrast, we compared the correct trials during repetition 2 to 5 (2–5C) between reversal and acquisition to examine the neural regions involved in the expression of new behaviors under the interference of old behaviors.</p

ROI results.

<p>Percentage signal change in the right OFC (A), the right DLPFC (B), the lingual gyrus (C) and the precuneus (D), is plotted as a function of learning stage (1E vs. 2–5C), learning condition (reward vs. punishment) and reversal (learning vs. reversal). Error bars indicated with-subject standard error. 1E: first error; 2–5C: correct trials during repetitions 2 to 5.</p

Brain regions associated with contingency change detection (1^st reversal error >1^st acquisition error).

<p>Significant activation for reward (A), punishment (B) and their conjunction (C), are rendered onto a population-averaged surface atlas using multi-fiducial mapping<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082169#pone.0082169-VanEssen1" target="_blank">[88]</a>. All activations were thresholded by using cluster detection statistics, with a height threshold of z>2.3 and a cluster probability of P<0.05, corrected for whole-brain multiple comparisons.</p

Neural response to punishment compared to no reward.

<p>Significant activation for in the lateral OFC and insula (A), the DLPFC (D), as well as in ACC and bilateral insula, are overlaid on coronal slices of the group mean structural image. All activations were thresholded by using cluster detection statistics, with a height threshold of z>2.3 and a cluster probability of P<0.05, corrected for whole-brain multiple comparisons. The right OFC and right DLPFC ROIs showing common reversal effect for reward and punishment are shown in white color, on panel A and D respectively. Their left homologues were defined by a left-right flipping. Percentage signal change in the left (B) and right (C) OFC, the left (E) and right (F) DLPFC, is plotted as a function of learning stage (1E vs. 2–5E), feedback type (no reward vs. punishment). Error bars indicated with-subject standard error. 1E: first error; 2–5E: error trials during repetitions 2 to 5.</p

Direct Synthesis of 7 nm-Thick Zinc(II)–Benzimidazole–Acetate Metal–Organic Framework Nanosheets

Direct Synthesis of 7 nm-Thick Zinc(II)–Benzimidazole–Acetate Metal–Organic Framework Nanosheet