GHCU, a Molecular Chaperone, Regulates Leaf Curling by Modulating the Distribution of KNGH1 in Cotton

Leaf shape is considered to be one of the most significant agronomic traits in crop breeding. However, the molecular basis underlying leaf morphogenesis in cotton is still largely unknown. In this study, through genetic mapping and molecular investigation using a natural cotton mutant cu with leaves curling upward, the causal gene GHCU is successfully identified as the key regulator of leaf flattening. Knockout of GHCU or its homolog in cotton and tobacco using CRISPR results in abnormal leaf shape. It is further discovered that GHCU facilitates the transport of the HD protein KNOTTED1-like (KNGH1) from the adaxial to the abaxial domain. Loss of GHCU function restricts KNGH1 to the adaxial epidermal region, leading to lower auxin response levels in the adaxial boundary compared to the abaxial. This spatial asymmetry in auxin distribution produces the upward-curled leaf phenotype of the cu mutant. By analysis of single-cell RNA sequencing and spatiotemporal transcriptomic data, auxin biosynthesis genes are confirmed to be expressed asymmetrically in the adaxial-abaxial epidermal cells. Overall, these findings suggest that GHCU plays a crucial role in the regulation of leaf flattening through facilitating cell-to-cell trafficking of KNGH1 and hence influencing the auxin response level

Activation of Pedunculopontine Tegmental Nucleus Alleviates the Pain Induced by the Lesion of Midbrain Dopaminergic Neurons

The loss of midbrain dopaminergic (DA) neurons is the fundamental pathological feature of Parkinson’s disease (PD). PD causes chronic pain in two-thirds of patients. Recent studies showed that the activation of the pedunculopontine tegmental nucleus (PPTg) can effectively relieve inflammatory pain and neuropathic pain. The PPTg is located in the pontomesencephalic tegmentum, a target of deep brain stimulation (DBS) treatment in PD, and is involved in motor control and sensory integration. To test whether the lesion of midbrain DA neurons induced pain hypersensitivity, and whether the chemogenetic activation of the PPTg could modulate the pain, the AAV-hM3Dq receptor was transfected and expressed into the PPTg neurons of 6-hydroxydopamine-lesioned mice. In this study, von Frey, open field, and adhesive tape removal tests were used to assess animals’ pain sensitivity, locomotor activity, and sensorimotor function and somatosensory perception, respectively. Here, we found that the lesion of midbrain DA neurons induced a minor deficit in voluntary movement but did not affect sensorimotor function and somatosensory perception in the tape removal test. The results showed that lesion led to pain hypersensitivity, which could be alleviated both by levodopa and by the chemogenetic activation of the PPTg. Activating the PPTg may be a potential therapeutic strategy to relieve pain phenotypes in PD

Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication

Abstract Background Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy. Methods Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and survival prognostication based on 8 immunotherapy transcriptomic cohorts and 30 The Cancer Genome Atlas (TCGA) pan-cancer datasets. Moreover, potential targets for immunotherapy were identified based on 17 CRISPR datasets and validated via in vivo and in vitro experiments. Results The assessment of LM was confirmed to possess a substantial relationship with immunotherapy resistance in 2 immunotherapy scRNA-seq cohorts. Based on large-scale pan-cancer data, there exists a notably adverse correlation between LM.SIG and anti-tumor immunity as well as imbalance infiltration of immune cells, whereas a positive association was observed between LM.SIG and pro-tumorigenic signaling. Utilizing this signature, the ML model predicted immunotherapy response and prognosis with an AUC of 0.73/0.80 in validation sets and 0.70/0.87 in testing sets respectively. Notably, LM.SIG exhibited superior predictive performance across various cancers compared to published signatures. Subsequently, CRISPR screening identified LDHA as a pan-cancer biomarker for estimating immunotherapy response and survival probability which was further validated using immunohistochemistry (IHC) and spatial transcriptomics (ST) datasets. Furthermore, experiments demonstrated that LDHA deficiency in pancreatic cancer elevated the CD8+ T cell antitumor immunity and improved macrophage antitumoral polarization, which in turn enhanced the efficacy of immunotherapy. Conclusions We unveiled the tight correlation between LM and resistance to immunotherapy and further established the pan-cancer LM.SIG, holds the potential to emerge as a competitive instrument for the selection of patients suitable for immunotherapy

Additional file 1 of Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication

Supplementary Material 1: Figure S1. AUC value of LM.SIG in three independent testing cohorts. Figure S2. Bar plot depicting the AUC values of LM.SIG and other melanoma‑specific signatures in the SKCM cohort (Hugo 2016 + Van Allen 2015). Figure S3. The association between LM.SIG-related risk score and OS of patients in each TCGA pan-cancer dataset (all p < 0.05). Figure S4. The expression of LDHA in GSE115978 and GSE123813 datasets. Figure S5. The level of lactate in sh-LDHA PDOs. The mRNA (A) and protein (B) levels of LDHA in sh-LDHA PDOs. (C) The level of lactate in sh-LDHA PDOs. (ns, not significant; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001) Figure S6. IHC staining showing the expression of LDHA, CD8, CD163 and Ki-67 among sh-NC + anti-IgG, sh-NC + anti-PD1, sh-LDHA + anti-IgG and sh-LDHA + anti-PD1 groups (scale bar: 200 μm)

ET White Paper: To Find the First Earth 2.0

We propose to develop a wide-field and ultra-high-precision photometric survey mission, temporarily named "Earth 2.0 (ET)". This mission is designed to measure, for the first time, the occurrence rate and the orbital distributions of Earth-sized planets. ET consists of seven 30cm telescopes, to be launched to the Earth-Sun's L2 point. Six of these are transit telescopes with a field of view of 500 square degrees. Staring in the direction that encompasses the original Kepler field for four continuous years, this monitoring will return tens of thousands of transiting planets, including the elusive Earth twins orbiting solar-type stars. The seventh telescope is a 30cm microlensing telescope that will monitor an area of 4 square degrees toward the galactic bulge. This, combined with simultaneous ground-based KMTNet observations, will measure masses for hundreds of long-period and free-floating planets. Together, the transit and the microlensing telescopes will revolutionize our understandings of terrestrial planets across a large swath of orbital distances and free space. In addition, the survey data will also facilitate studies in the fields of asteroseismology, Galactic archeology, time-domain sciences, and black holes in binaries.Comment: 116 pages,79 figure