Analysis of chloroplast genome characteristics and codon usage bias in 14 species of Annonaceae.

For the study of species evolution, chloroplast gene expression, and transformation, the chloroplast genome is an invaluable resource. Codon usage bias (CUB) analysis is a tool that is utilized to improve gene expression and investigate evolutionary connections in genetic transformation. In this study, we analysed chloroplast genome differences, codon usage patterns and the sources of variation on CUB in 14 Annonaceae species using bioinformatics tools. The study showed that there was a significant variation in both gene sizes and numbers between the 14 species, but conservation was still maintained. It's worth noting that there were noticeable differences in the IR/SC sector boundary and the types of SSRs among the 14 species. The mono-nucleotide repeat type was the most common, with A/T repeats being more prevalent than G/C repeats. Among the different types of repeats, forward and palindromic repeats were the most abundant, followed by reverse repeats, and complement repeats were relatively rare. Codon composition analysis revealed that all 14 species had a frequency of GC lower than 50%. Additionally, it was observed that the proteins in-coding sequences of chloroplast genes tend to end with A/T at the third codon position. Among these species, 21 codons exhibited bias (RSCU > 1), and there were 8 high-frequency (HF) codons and 5 optimal codons that were identical across the species. According to the ENC-plot and Neutrality plot analysis, natural selection had less impact on the CUB of A. muricate and A. reticulata. Based on the PR2-plot, it was evident that base G had a higher frequency than C, and T had a higher frequency A. The correspondence analysis (COA) revealed that codon usage patterns different in Annonaceae.

Characterization of decision commitment rule alterations during an auditory change detection task.

A critical component of decision making is determining when to commit to a choice. This involves stopping rules that specify the requirements for decision commitment. Flexibility of decision stopping rules provides an important means of control over decision-making processes. In many situations, these stopping rules establish a balance between premature decisions and late decisions. In this study we use a novel change detection paradigm to examine how subjects control this balance when invoking different decision stopping rules. The task design allows us to estimate the temporal weighting of sensory information for the decisions, and we find that different stopping rules did not result in systematic differences in that weighting. We also find bidirectional post-error alterations of decision strategy that depend on the type of error and effectively reduce the probability of making consecutive mistakes of the same type. This is a generalization to change detection tasks of the widespread observation of unidirectional post-error slowing in forced-choice tasks. On the basis of these results, we suggest change detection tasks as a promising paradigm to study the neural mechanisms that support flexible control of decision rules.NEW & NOTEWORTHY Flexible decision stopping rules confer control over decision processes. Using an auditory change detection task, we found that alterations of decision stopping rules did not result in systematic changes in the temporal weighting of sensory information. We also found that post-error alterations of decision stopping rules depended on the type of mistake subjects make. These results provide guidance for understanding the neural mechanisms that control decision stopping rules, one of the critical components of decision making and behavioral flexibility.

Phosphorus-Doped Hollow Tubular g-C3N4 for Enhanced Photocatalytic CO2 Reduction.

Photocatalytic CO2 reduction is a tactic for solving the environmental pollution caused by greenhouse gases. Herein, NH4H2PO4 was added as a phosphorus source in the process of the hydrothermal treatment of melamine for the first time, and phosphorus-doped hollow tubular g-C3N4 (x-P-HCN) was fabricated and used for photocatalytic CO2 reduction. Here, 1.0-P-HCN exhibited the largest CO production rate of 9.00 µmol·g-1·h-1, which was 10.22 times higher than that of bulk g-C3N4. After doping with phosphorus, the light absorption range, the CO2 adsorption capacity, and the specific surface area of the 1.0-P-HCN sample were greatly improved. In addition, the separation of photogenerated electron-hole pairs was enhanced. Furthermore, the phosphorus-doped g-C3N4 effectively activated the CO2 adsorbed on the surface of phosphorus-doped g-C3N4 photocatalysts, which greatly enhanced the CO production rate of photocatalytic CO2 reduction over that of g-C3N4.

Enhancement of visible-light-driven CO2 reduction performance using an amine-functionalized zirconium metal-organic framework.

By employing a conjugated amine-functionalized dicarboxylic ligand (H2L = 2,2'-diamino-4,4'-stilbenedicarboxylic acid, H2SDCA-NH2), we have successfully synthesized and characterized a porous and visible light responsive zirconium metal-organic framework ([Zr6O4(OH)4(L)6]·8DMF, denoted as Zr-SDCA-NH2). This Zr-MOF showed good chemical stability and broad visible light absorption with an absorption edge at about 600 nm. When used as a photocatalyst, Zr-SDCA-NH2 exhibits visible-light activity for CO2 reduction with a formate formation rate of 96.2 µmol h-1 mmolMOF-1, which is higher than the series of reported amine-functionalized Zr-MOFs. Mott-Schottky measurements, photoluminescence study and photocatalytic experiments demonstrated that the Zr6 oxo cluster through the LMCT process and the organic ligand both contributed to the CO2 photoreduction. This study indicates that the combination of amino groups and highly conjugated molecules is a feasible and simple strategy to extend light absorption of the organic ligand, which is beneficial for designing a visible light responsive MOF photocatalyst.