Impaired Magnesium Protoporphyrin IX Methyltransferase (ChlM) Impedes Chlorophyll Synthesis and Plant Growth in Rice

Magnesium protoporphyrin IX methyltransferase (ChlM) catalyzes the formation of magnesium protoporphyrin IX monomethylester (MgPME) from magnesium protoporphyrin IX (MgP) in the chlorophyll synthesis pathway. However, no ChlM gene has yet been identified and studied in monocotyledonous plants. In this study, a spontaneous mutant, yellow-green leaf 18 (ygl18), was isolated from rice (Oryza sativa). This mutant showed yellow-green leaves, decreased chlorophyll level, and climate-dependent growth differences. Map-based cloning of this mutant identified the YGL18 gene LOC_Os06g04150. YGL18 is expressed in green tissues, especially in leaf organs, where it functions in chloroplasts. YGL18 showed an amino-acid sequence similarity to that of ChlM from different photosynthetic organisms. In vitro enzymatic assays demonstrated that YGL18 performed ChlM enzymatic activity, but ygl18 had nearly lost all ChlM activity. Correspondingly, the substrate MgP was largely accumulated while the product MgPME was reduced in ygl18 leaves. YGL18 is required for light-dependent and photoperiod-regulated chlorophyll synthesis. The retarded growth of ygl18 mutant plants was caused by the high light intensity. Moreover, the higher light intensity and longer exposure in high light intensity even made the ygl18 plants be more susceptible to death. Based on these results, it is suggested that YGL18 plays essential roles in light-related chlorophyll synthesis and light intensity–involved plant growth

Impaired Thymic Selection and Abnormal Antigen-Specific T Cell Responses in Foxn1Δ/Δ Mutant Mice

Foxn1(Δ/Δ) mutant mice have a specific defect in thymic development, characterized by a block in TEC differentiation at an intermediate progenitor stage, and blocks in thymocyte development at both the DN1 and DP cell stages, resulting in the production of abnormally functioning T cells that develop from an atypical progenitor population. In the current study, we tested the effects of these defects on thymic selection.We used Foxn1(Δ/Δ); DO11 Tg and Foxn1(Δ/Δ); OT1 Tg mice as positive selection and Foxn1(Δ/Δ); MHCII I-E mice as negative selection models. We also used an in vivo system of antigen-specific reactivity to test the function of peripheral T cells. Our data show that the capacity for positive and negative selection of both CD4 and CD8 SP thymocytes was reduced in Foxn1(Δ/Δ) mutants compared to Foxn1(+/Δ) control mice. These defects were associated with reduction of both MHC Class I and Class II expression, although the resulting peripheral T cells have a broad TCR Vβ repertoire. In this deficient thymic environment, immature CD4 and CD8 SP thymocytes emigrate from the thymus into the periphery. These T cells had an incompletely activated profile under stimulation of the TCR signal in vitro, and were either hypersensitive or hyporesponsive to antigen-specific stimulation in vivo. These cell-autonomous defects were compounded by the hypocellular peripheral environment caused by low thymic output.These data show that a primary defect in the thymic microenvironment can cause both direct defects in selection which can in turn cause indirect effects on the periphery, exacerbating functional defects in T cells

Adaptive Sliding Mode Disturbance Observer and Deep Reinforcement Learning Based Motion Control for Micropositioners

The motion control of high-precision electromechanitcal systems, such as micropositioners, is challenging in terms of the inherent high nonlinearity, the sensitivity to external interference, and the complexity of accurate identification of the model parameters. To cope with these problems, this work investigates a disturbance observer-based deep reinforcement learning control strategy to realize high robustness and precise tracking performance. Reinforcement learning has shown great potential as optimal control scheme, however, its application in micropositioning systems is still rare. Therefore, embedded with the integral differential compensator (ID), deep deterministic policy gradient (DDPG) is utilized in this work with the ability to not only decrease the state error but also improve the transient response speed. In addition, an adaptive sliding mode disturbance observer (ASMDO) is proposed to further eliminate the collective effect caused by the lumped disturbances. The micropositioner controlled by the proposed algorithm can track the target path precisely with less than 1 μm error in simulations and actual experiments, which shows the sterling performance and the accuracy improvement of the controller

Deletion of peripheral TCR Vβ5.1 and Vβ11 CD4⁺ T cell clones after backcrossing <i>Foxn1</i>^Δ/Δ mice onto the BALB/c genetic background.

<p>Deletion of peripheral TCR Vβ5.1 and Vβ11 CD4⁺ T cell clones after backcrossing <i>Foxn1</i>^Δ/Δ mice onto the BALB/c genetic background.</p

<i>Foxn1^Δ/Δ</i> peripheral T cells have abnormal responses to SEA <i>in vivo</i>.

<p>A and B, showing kinetic response of Vβ3 and Vβ11 T cells to SEA <i>in vivo</i>. <i>Foxn1^+/</i>^Δ and <i>Foxn1</i>^Δ/Δ mice were retro-orbitally injected with SEA 1 µg per mouse, and the percentages of Vβ3 and Vβ11 were measured in peripheral blood T cells on the indicated day. Y values show the ratio of percentages of Vβ3⁺ and Vβ11⁺ cell in individual day relative to day 0 (before injection of SEA). C and D, the response of transferred Ly5.1⁺ cells to SEA in <i>Foxn1</i>^Δ/Δ mice. Sorted Ly5.1 T cells at 4×10⁶ per mouse were transferred into <i>Foxn1</i>^Δ/Δ mice. One day later, the percentage of Vβ3 was measured as day 0 and then SEA 1 µg per mouse was injected. The percentage of Vβ3 was continuously measured on the indicated days after injection of SEA and shown as the ratio of the percentage relative to day 0. The results shown were the average from two or three individual experiments.</p

TCR Vβ usage in the peripheral T cells of <i>Foxn1^Δ/Δ</i> mutant mice.

<p>The peripheral cells from spleen and LNs were screened with TCR Vβ usage. The result shown was average volume from at least 5 individual samples. A and B show the percentage of expression of TCR Vβs on CD4 and CD8 T cells.</p

Positive selection for CD8 Tg T cells was partially reduced in <i>Foxn1^Δ/Δ</i> mice.

<p><i>Foxn1</i>^Δ/Δ;OT1 and <i>Foxn1</i>^Δ<i>/</i>Δ;OT1 Tg mice were generated by mating <i>Foxn1</i>^Δ/Δ mice with OT1 CD8 TCR Tg mice, and the CD8 Tg cells were analyzed in thymocytes (A, B, C and D) and splenocytes (E, F, G and H). A, representative profile of CD4 and CD8 expression on thymocytes (top panel), and expression of Vα2 and Vβ5 on gated CD8 SP thymocytes (bottom panel). B, percentage of CD8 SP thymocytes in individual OT1 Tg and non-Tg mice; C, individual analysis of the percentage of Vα2⁺ and Vβ5⁺ cell on gated CD8 SP thymocytes; D, total number of thymic cells from individual OT1 Tg and non-Tg mice. E, F, G and H show the same analyses performed on splenotytes. (*, p<0.05).</p