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Choristoneura metasequoiacola Liu, 1983 is an important caterpillar species that specifically infests the leaves and branches of Metasequoia glyptostroboides Hu & W. C. Cheng 1948 with short larval infestations, long-term dormancy, and has a limited distribution in Lichuan, Hubei, China. The complete mitochondria genome of C. metasequoiacola was determined by using Illumina NovaSeq, and analyzed based on previously annotated sibling species. In total, we obtained mitochondria genome with 15,128 bp in length, circular in shape with a double-stranded closed ring structure, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, and an AT-rich region. Of which the nucleotide composition was highly A + T biased, accounting for 81.98% of the whole mitogenome. Thirteen protein-coding genes (PCGs) were 11,142 bp; Twenty-two tRNA genes and AT-rich region were 1,472 and 199 bp, respectively. Phylogenetically, the relationship between Choristoneura spp. (containing C. metasequoiacola) and Adoxophyes spp. was closer than any other two genera from Tortricidae, and the relationship between C. metasequoiacola and C.murinana was the closest among nine sibling species from that genus, which helps to explain species evolution within the family Tortricidae.

RORγt is known to instruct the differentiation of T helper 17 (TH17) cells that mediate the pathogenesis of autoimmune diseases. However, it remains unknown whether RORγt plays a distinct role in the differentiation and effector function of TH17 cells. Here, we show that mutation of RORγt lysine-256, a ubiquitination site, to arginine (K256R) separates the RORγt role in these two functions. Preventing ubiquitination at K256 via arginine substitution does not affect RORγt-dependent thymocyte development, and TH17 differentiation in vitro and in vivo, however, greatly impaired the pathogenesis of TH17 cell-mediated experimental autoimmune encephalomyelitis (EAE). Mechanistically, K256R mutation impairs RORγt to bind to and activate Runx1 expression critical for TH17-mediated EAE. Thus, RORγt regulates the effector function of TH17 cells in addition to TH17 differentiation. This work informs the development of RORγt-based therapies that specifically target the effector function of TH17 cells responsible for autoimmunity.

Steroid nuclear receptor coactivator 2 (SRC2) is a member of a family of transcription coactivators. While SRC1 inhibits the differentiation of regulatory T cells (Tregs) critical for establishing immune tolerance, we show here that SRC2 stimulates Treg differentiation. SRC2 is dispensable for the development of thymic Tregs, whereas naive CD4+ T cells from mice deficient of SRC2 specific in Tregs (SRC2fl/fl/Foxp3YFP-Cre) display defective Treg differentiation. Furthermore, the aged SRC2fl/fl/Foxp3YFP-Cre mice spontaneously develop autoimmune phenotypes including enlarged spleen and lung inflammation infiltrated with IFNγ-producing CD4+ T cells. SRC2fl/fl/Foxp3YFP-Cre mice also develop severer experimental autoimmune encephalomyelitis (EAE) due to reduced Tregs. Mechanically, SRC2 recruited by NFAT1 binds to the promoter and activates the expression of Nr4a2, which then stimulates Foxp3 expression to promote Treg differentiation. Members of SRC family coactivators thus play distinct roles in Treg differentiation and are potential drug targets for controlling immune tolerance.

Robot manipulation is increasingly poised to interact with humans in co-shared workspaces. Despite increasingly robust manipulation and control algorithms, failure modes continue to exist whenever models do not capture the dynamics of the unstructured environment. To obtain longer-term horizons in robot automation, robots must develop introspection and recovery abilities. We contribute a set of recovery policies to deal with anomalies produced by external disturbances as well as anomaly classification through the use of non-parametric statistics with memoized variational inference with scalable adaptation. A recovery critic stands atop of a tightly-integrated, graph-based online motion-generation and introspection system that resolves a wide range of anomalous situations. Policies, skills, and introspection models are learned incrementally and contextually in a task. Two task-level recovery policies: re-enactment and adaptation resolve accidental and persistent anomalies respectively. The introspection system uses non-parametric priors along with Markov jump linear systems and memoized variational inference with scalable adaptation to learn a model from the data. Extensive real-robot experimentation with various strenuous anomalous conditions is induced and resolved at different phases of a task and in different combinations. The system executes around-the-clock introspection and recovery and even elicited self-recovery when misclassifications occurred., Comment: 33 pages, 28 figures. Supplemental info, code, and videos found at: http://www.juanrojas.net/re_enact_adapt/

Doppler techniques used in blood flow velocity estimation rely on the assumption that the phase of the envelope‐detected echo signals changes linearly with depth. However, the random spatial distribution of scatterers makes it inadequate. Correlation searching techniques utilize time shifts to remedy this drawback, but the probability of the correct maximum detection is also low under certain measurement conditions. In this study, a more sensitive and simpler means of velocity estimation has been proposed. This method tracks a segment of the echo footprints by means of the least‐sum‐squared difference from the consecutive RF echo signals. Since a squared difference measure is used to extract the moving information, the detection results are sensitive to the locally large differences, no matter how large the amplitudes are here, and the probability of finding a correct match by this method is highly increased. A detailed computer simulation evaluated the interdependencies of the window size, the pulse dura...