Two chromosome-level genome assemblies of Rhodiola shed new light on genome evolution in rapid radiation and evolution of the biosynthetic pathway of salidroside.

Rhodiola L. is a genus that has undergone rapid radiation in the mid-Miocene and may represent a typic case of adaptive radiation. Many species of Rhodiola have also been widely used as an important adaptogen in traditional medicines for centuries. However, a lack of high-quality chromosome-level genomes hinders in-depth study of its evolution and biosynthetic pathway of secondary metabolites. Here, we assembled two chromosome-level genomes for two Rhodiola species with different chromosome number and sexual system. The assembled genome size of R. chrysanthemifolia (2n = 14; hermaphrodite) and R. kirilowii (2n = 22; dioecious) were of 402.67 and 653.62 Mb, respectively, with approximately 57.60% and 69.22% of transposable elements (TEs). The size difference between the two genomes was mostly due to proliferation of long terminal repeat-retrotransposons (LTR-RTs) in the R. kirilowii genome. Comparative genomic analysis revealed possible gene families responsible for high-altitude adaptation of Rhodiola, including a homolog of plant cysteine oxidase 2 gene of Arabidopsis thaliana (AtPCO2), which is part of the core molecular reaction to hypoxia and contributes to the stability of Group VII ethylene response factors (ERF-VII). We found extensive chromosome fusion/fission events and structural variations between the two genomes, which might have facilitated the initial rapid radiation of Rhodiola. We also identified candidate genes in the biosynthetic pathway of salidroside. Overall, our results provide important insights into genome evolution in plant rapid radiations, and possible roles of chromosome fusion/fission and structure variation played in rapid speciation.

Transfer learning for clustering single-cell RNA-seq data crossing-species and batch, case on uterine fibroids.

Due to the high dimensionality and sparsity of the gene expression matrix in single-cell RNA-sequencing (scRNA-seq) data, coupled with significant noise generated by shallow sequencing, it poses a great challenge for cell clustering methods. While numerous computational methods have been proposed, the majority of existing approaches center on processing the target dataset itself. This approach disregards the wealth of knowledge present within other species and batches of scRNA-seq data. In light of this, our paper proposes a novel method named graph-based deep embedding clustering (GDEC) that leverages transfer learning across species and batches. GDEC integrates graph convolutional networks, effectively overcoming the challenges posed by sparse gene expression matrices. Additionally, the incorporation of DEC in GDEC enables the partitioning of cell clusters within a lower-dimensional space, thereby mitigating the adverse effects of noise on clustering outcomes. GDEC constructs a model based on existing scRNA-seq datasets and then applying transfer learning techniques to fine-tune the model using a limited amount of prior knowledge gleaned from the target dataset. This empowers GDEC to adeptly cluster scRNA-seq data cross different species and batches. Through cross-species and cross-batch clustering experiments, we conducted a comparative analysis between GDEC and conventional packages. Furthermore, we implemented GDEC on the scRNA-seq data of uterine fibroids. Compared results obtained from the Seurat package, GDEC unveiled a novel cell type (epithelial cells) and identified a notable number of new pathways among various cell types, thus underscoring the enhanced analytical capabilities of GDEC. Availability and implementation: https://github.com/YuzhiSun/GDEC/tree/main.

Long-distance transport of sucrose in source leaves promotes sink root growth by the EIN3-SUC2 module.

In most plants, sucrose, a major storage sugar, is transported into sink organs to support their growth. This key physiological process is dependent on the function of sucrose transporters. Sucrose export from source tissues is predominantly controlled through the activity of SUCROSE TRANSPORTER 2 (SUC2), required for the loading of sucrose into the phloem of Arabidopsis plants. However, how SUC2 activity is controlled to support root growth remains unclear. Glucose is perceived via the function of HEXOKINASE 1 (HXK1), the only known nuclear glucose sensor. HXK1 negatively regulates the stability of ETHYLENE-INSENSITIVE3 (EIN3), a key ethylene/glucose interaction component. Here we show that HXK1 functions upstream of EIN3 in the regulation of root sink growth mediated by glucose signaling. Furthermore, the transcription factor EIN3 directly inhibits SUC2 activity by binding to the SUC2 promoter, regulating glucose signaling linked to root sink growth. We demonstrate that these molecular components form a HXK1-EIN3-SUC2 module integral to the control of root sink growth. Also, we demonstrate that with increasing age, the HXK1-EIN3-SUC2 module promotes sucrose phloem loading in source tissues thereby elevating sucrose levels in sink roots. As a result, glucose signaling mediated-sink root growth is facilitated. Our findings thus establish a direct molecular link between the HXK1-EIN3-SUC2 module, the source-to sink transport of sucrose and root growth.

Chromosome-level genome provides insight into the evolution and conservation of the threatened goral (Naemorhedus goral).

BACKGROUND: Gorals Naemorhedus resemble both goats and antelopes, which prompts much debate about the intragenus species delimitation and phylogenetic status of the genus Naemorhedus within the subfamily Caprinae. Their evolution is believed to be linked to the uplift of the Qinghai-Tibet Plateau (QTP). To better understand its phylogenetics, the genetic information is worth being resolved. RESULTS: Based on a sample from the eastern margin of QTP, we constructed the first reference genome for Himalayan goral Naemorhedus goral, using PacBio long-read sequencing and Hi-C technology. The 2.59 Gb assembled genome had a contig N50 of 3.70 Mb and scaffold N50 of 106.66 Mb, which anchored onto 28 pseudo chromosomes. A total of 20,145 protein-coding genes were predicted in the assembled genome, of which 99.93% were functionally annotated. Phylogenetically, the goral was closely related to muskox on the mitochondrial genome level and nested into the takin-muskox clade on the genome tree, rather than other so-called goat-antelopes. The cladogenetic event among muskox, takin and goral occurred sequentially during the late Miocene (~ 11 - 5 Mya), when the QTP experienced a third dramatic uplift with consequent profound changes in climate and environment. Several chromosome fusions and translocations were observed between goral and takin/muskox. The expanded gene families in the goral genome were mainly related to the metabolism of drugs and diseases, so as the positive selected genes. The Ne of goral continued to decrease since ~ 1 Mya during the Pleistocene with active glaciations. CONCLUSION: The high-quality goral genome provides insights into the evolution and valuable information for the conservation of this threatened group.

Yak genome database: a multi-omics analysis platform.

BACKGROUND: The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data. DESCRIPTION: The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database. CONCLUSION: This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.

Acute hospitalizations after proton therapy versus intensity-modulated radiotherapy for locally advanced non-small cell lung cancer in the durvalumab era.

INTRODUCTION: It was hypothesized that use of proton beam therapy (PBT) in patients with locally advanced non-small cell lung cancer treated with concurrent chemoradiation and consolidative immune checkpoint inhibition is associated with fewer unplanned hospitalizations compared with intensity-modulated radiotherapy (IMRT). METHODS: Patients with locally advanced non-small cell lung cancer treated between October 2017 and December 2021 with concurrent chemoradiation with either IMRT or PBT ± consolidative immune checkpoint inhibition were retrospectively identified. Logistic regression was used to assess the association of radiation therapy technique with 90-day hospitalization and grade 3 (G3+) lymphopenia. Competing risk regression was used to compare G3+ pneumonitis, G3+ esophagitis, and G3+ cardiac events. Kaplan-Meier method was used for progression-free survival and overall survival. Inverse probability treatment weighting was applied to adjust for differences in PBT and IMRT groups. RESULTS: Of 316 patients, 117 (37%) received PBT and 199 (63%) received IMRT. The PBT group was older (p < .001) and had higher Charlson Comorbidity Index scores (p = .02). The PBT group received a lower mean heart dose (p < .0001), left anterior descending artery V15 Gy (p = .001), mean lung dose (p = .008), and effective dose to immune circulating cells (p < .001). On inverse probability treatment weighting analysis, PBT was associated with fewer unplanned hospitalizations (adjusted odds ratio, 0.55; 95% CI, 0.38-0.81; p = .002) and less G3+ lymphopenia (adjusted odds ratio, 0.55; 95% CI, 0.37-0.81; p = .003). There was no difference in other G3+ toxicities, progression-free survival, or overall survival. CONCLUSIONS: PBT is associated with fewer unplanned hospitalizations, lower effective dose to immune circulating cells and less G3+ lymphopenia compared with IMRT. Minimizing dose to lymphocytes may be warranted, but prospective data are needed.

Development of a novel prognostic signature based on single-cell combined bulk RNA analysis in breast cancer.

BACKGROUND: Breast cancer (BC), a malignant tumor, is a significant cause of death and disability among women globally. Recent research indicates that copy number variation plays a crucial role in tumor development. In this study, we employed the Single-Cell Variational Aneuploidy Analysis (SCEVAN) algorithm to differentiate between malignant and non-malignant cells, aiming to identify genetic signatures with prognostic relevance for predicting patient survival. METHODS: We analyzed gene expression profiles and associated clinical data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Using the SCEVAN algorithm, we distinguished malignant from non-malignant cells and investigated cellular interactions within the tumor microenvironment (TME). We categorized TCGA samples based on differentially expressed genes (DEGs) between these cell types. Subsequent Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted. Additionally, we developed polygenic models for the DEGs using least absolute shrinkage and selection operator-penalized Cox regression analysis. To assess the prognostic accuracy of these characteristics, we generated Kaplan-Meier and receiver operating characteristic curves from training and validation datasets. We also monitored the expression variations of prognostic genes across the pseudotime of malignant cells. Patients were divided into high-risk and low-risk groups based on median risk scores to compare their TME and identify potential therapeutic agents. Lastly, polymerase chain reaction was used to validate seven pivotal genes. RESULTS: The SCEVAN algorithm identified distinct malignant and non-malignant cells in GSE180286. Cellchat analysis revealed significantly increased cellular communication, particularly between fibroblasts, endothelial cells and malignant cells. The DEGs were predominantly involved in immune-related pathways. TCGA samples were classified into clusters A and B based on these genes. Cluster A, enriched in immune pathways, was associated with poorer prognosis, whereas cluster B, predominantly involved in circadian rhythm pathways, showed better outcomes. We constructed a 14-gene prognostic signature, validated in a 1:1 internal TCGA cohort and external GEO datasets (GSE42568 and GSE146558). Kaplan-Meier analysis confirmed the prognostic signature's accuracy (p < 0.001). Receiver operating characteristic curve analysis demonstrated the predictive reliability of these prognostic features. Single-cell pseudotime analysis with monocle2 highlighted the distinct expression trends of these genes in malignant cells, underscoring the intratumoral heterogeneity. Furthermore, we explored the differences in TME between high- and low-risk groups and identified 16 significantly correlated drugs. CONCLUSION: Our findings suggest that the 14-gene prognostic signature could serve as a novel biomarker for forecasting the prognosis of BC patients. Additionally, the immune cells and pathways in different risk groups indicate that immunotherapy may be a crucial component of treatment strategies for BC patients.

Mining the interpretable prognostic features from pathological image of intrahepatic cholangiocarcinoma using multi-modal deep learning.

BACKGROUND: The advances in deep learning-based pathological image analysis have invoked tremendous insights into cancer prognostication. Still, lack of interpretability remains a significant barrier to clinical application. METHODS: We established an integrative prognostic neural network for intrahepatic cholangiocarcinoma (iCCA), towards a comprehensive evaluation of both architectural and fine-grained information from whole-slide images. Then, leveraging on multi-modal data, we conducted extensive interrogative approaches to the models, to extract and visualize the morphological features that most correlated with clinical outcome and underlying molecular alterations. RESULTS: The models were developed and optimized on 373 iCCA patients from our center and demonstrated consistent accuracy and robustness on both internal (n = 213) and external (n = 168) cohorts. The occlusion sensitivity map revealed that the distribution of tertiary lymphoid structures, the geometric traits of the invasive margin, the relative composition of tumor parenchyma and stroma, the extent of necrosis, the presence of the disseminated foci, and the tumor-adjacent micro-vessels were the determining architectural features that impacted on prognosis. Quantifiable morphological vector extracted by CellProfiler demonstrated that tumor nuclei from high-risk patients exhibited significant larger size, more distorted shape, with less prominent nuclear envelope and textural contrast. The multi-omics data (n = 187) further revealed key molecular alterations left morphological imprints that could be attended by the network, including glycolysis, hypoxia, apical junction, mTORC1 signaling, and immune infiltration. CONCLUSIONS: We proposed an interpretable deep-learning framework to gain insights into the biological behavior of iCCA. Most of the significant morphological prognosticators perceived by the network are comprehensible to human minds.

The role of the cytochrome P450 superfamily in the skin.

In mammals, the skin acts as a barrier to prevent harmful environmental stimuli from entering the circulation. CYP450s are involved in drug biotransformation, exogenous and endogenous substrate metabolism, and maintaining the normal physiological function of the skin, as well as facilitating homeostasis of the internal environment. The expression pattern of CYP450s in the skin is tissue-specific and thus differs from the liver and other organs. The development of skin topical medications, and knowledge of the toxicity and side effects of these medications require a detailed understanding of the expression and function of skin-specific CYP450s. Thus, we summarized the expression of CYP450s in the skin, their function in endogenous metabolic physiology, aberrant CYP450 expression in skin diseases and the influence of environmental variables and medications. This information will serve as a crucial foundation for future studies on the skin, as well as for the design and development of new drugs for skin diseases including topical medications.

Recent Progress in Hot Spot Regulated Strategies for Catalysts Applied in Li-CO2 Batteries.

As a high energy density power system, lithium-carbon dioxide (Li-CO2 ) batteries play an important role in addressing the fossil fuel crisis issues and alleviating the greenhouse effect. However, the sluggish transformation kinetic of CO2 and the difficult decomposition of discharge products impede the achievement of large capacity, small overpotential, and long life span of the batteries, which require exploring efficient catalysts to resolve these problems. In this review, the main focus is on the hot spot regulation strategies of the catalysts, which include the modulation of the active sites, the designing of microstructure, and the construction of composition. The recent progress of promising catalysis with hot spot regulated strategies is systematically addressed. Critical challenges are also presented and perspectives to provide useful guidance for the rational design of highly efficient catalysts for practical advanced Li-CO2 batteries are proposed.

Strain Self-Adaptive Iron Selenides Toward Stable Na+ -Ion Batteries with Impressive Initial Coulombic Efficiency.

High tap density electrodes play a vital role in developing rechargeable batteries with high volumetric capacities, however, developing advanced electrodes with satisfied capacity, excellent structural stability, and achieving the resulted batteries with a high initial Coulombic efficiency (ICE) and good rate capability with long lifespan simultaneously, are still an intractable challenge. Herein, an ultrahigh ICE of 94.1% and stable cycling of carbon-free iron selenides anode is enabled with a high tap density of 2.57 g cm-3 up to 4000 cycles at 5 A g-1 through strain-modulating by constructing a homologous heterostructure. Systematical characterization and theoretical calculation show that the self-adaptive homologous heterointerface alleviates the stress of the iron selenide anodes during cycling processes and subsequently improves the stability of the assembled batteries. Additionally, the well-formed homologous heterostructure also contributes to the rapid Na+ diffusion kinetic, increased charge transfer, and good reversibility of the transformation reactions, endowing the appealing rate capability of carbon-free iron selenides. The proposed design strategy provides new insight and inspiration to aid in the ongoing quest for advanced electrode materials with high tap densities and excellent stability.

Versatile CYP98A enzymes catalyse meta-hydroxylation reveals diversity of salvianolic acids biosynthesis.

Salvianolic acids (SA), such as rosmarinic acid (RA), danshensu (DSS), and their derivative salvianolic acid B (SAB), etc. widely existed in Lamiaceae and Boraginaceae families, are of interest due to medicinal properties in the pharmaceutical industries. Hundreds of studies in past decades described that 4-coumaroyl-CoA and 4-hydroxyphenyllactic acid (4-HPL) are common substrates to biosynthesize SA with participation of rosmarinic acid synthase (RAS) and cytochrome P450 98A (CYP98A) subfamily enzymes in different plants. However, in our recent study, several acyl donors and acceptors included DSS as well as their ester-forming products all were determined in SA-rich plants, which indicated that previous recognition to SA biosynthesis is insufficient. Here, we used Salvia miltiorrhiza, a representative important medicinal plant rich in SA, to elucidate the diversity of SA biosynthesis. Various acyl donors as well as acceptors are catalysed by SmRAS to form precursors of RA and two SmCYP98A family members, SmCYP98A14 and SmCYP98A75, are responsible for different positions' meta-hydroxylation of these precursors. SmCYP98A75 preferentially catalyses C-3' hydroxylation, and SmCYP98A14 preferentially catalyses C-3 hydroxylation in RA generation. In addition, relative to C-3' hydroxylation of the acyl acceptor moiety in RA biosynthesis, SmCYP98A75 has been verified as the first enzyme that participates in DSS formation. Furthermore, SmCYP98A enzymes knockout resulted in the decrease and overexpression leaded to dramatic increase of SA accumlation. Our study provides new insights into SA biosynthesis diversity in SA-abundant species and versatility of CYP98A enzymes catalytic preference in meta-hydroxylation reactions. Moreover, CYP98A enzymes are ideal metabolic engineering targets to elevate SA content.

Chromosome-level reference genome and resequencing of 322 accessions reveal evolution, genomic imprint and key agronomic traits in adzuki bean.

Adzuki bean (Vigna angularis) is an important legume crop cultivated in over 30 countries worldwide. We developed a high-quality chromosome-level reference genome of adzuki bean cultivar Jingnong6 by combining PacBio Sequel long-read sequencing with short-read and Hi-C technologies. The assembled genome covers 97.8% of the adzuki bean genome with a contig N50 of approximately 16 Mb and a total of 32 738 protein-coding genes. We also generated a comprehensive genome variation map of adzuki bean by whole-genome resequencing (WGRS) of 322 diverse adzuki beans accessions including both wild and cultivated. Furthermore, we have conducted comparative genomics and a genome-wide association study (GWAS) on key agricultural traits to investigate the evolution and domestication. GWAS identified several candidate genes, including VaCycA3;1, VaHB15, VaANR1 and VaBm, that exhibited significant associations with domestication traits. Furthermore, we conducted functional analyses on the roles of VaANR1 and VaBm in regulating seed coat colour. We provided evidence for the highest genetic diversity of wild adzuki (Vigna angularis var. nipponensis) in China with the presence of the most original wild adzuki bean, and the occurrence of domestication process facilitating transition from wild to cultigen. The present study elucidates the genetic basis of adzuki bean domestication traits and provides crucial genomic resources to support future breeding efforts in adzuki bean.

Transcriptome and open chromatin analysis reveals the process of myocardial cell development and key pathogenic target proteins in Long QT syndrome type 7.

OBJECTIVE: Long QT syndrome type 7 (Andersen-Tawil syndrome, ATS), which is caused by KCNJ2 gene mutation, often leads to ventricular arrhythmia, periodic paralysis and skeletal malformations. The development, differentiation and electrophysiological maturation of cardiomyocytes (CMs) changes promote the pathophysiology of Long QT syndrome type 7(LQT7). We aimed to specifically reproduce the ATS disease phenotype and study the pathogenic mechanism. METHODS AND RESULTS: We established a cardiac cell model derived from human induced pluripotent stem cells (hiPSCs) to the phenotypes and electrophysiological function, and the establishment of a human myocardial cell model that specifically reproduces the symptoms of ATS provides a reliable platform for exploring the mechanism of this disease or potential drugs. The spontaneous pulsation rate of myocardial cells in the mutation group was significantly lower than that in the repair CRISPR group, the action potential duration was prolonged, and the Kir2.1 current of the inward rectifier potassium ion channel was decreased, which is consistent with the clinical symptoms of ATS patients. Only ZNF528, a chromatin-accessible TF related to pathogenicity, was continuously regulated beginning from the cardiac mesodermal precursor cell stage (day 4), and continued to be expressed at low levels, which was identified by WGCNA method and verified with ATAC-seq data in the mutation group. Subsequently, it indicated that seven pathways were downregulated (all p < 0.05) by used single sample Gene Set Enrichment Analysis to evaluate the overall regulation of potassium-related pathways enriched in the transcriptome and proteome of late mature CMs. Among them, the three pathways (GO: 0008076, GO: 1990573 and GO: 0030007) containing the mutated gene KCNJ2 is involved that are related to the whole process by which a potassium ion enters the cell via the inward rectifier potassium channel to exert its effect were inhibited. The other four pathways are related to regulation of the potassium transmembrane pathway and sodium:potassium exchange ATPase (p < 0.05). ZNF528 small interfering (si)-RNA was applied to hiPSC-derived cardiomyocytes for CRISPR group to explore changes in potassium ion currents and growth and development related target protein levels that affect disease phenotype. Three consistently downregulated proteins (KCNJ2, CTTN and ATP1B1) associated with pathogenicity were verificated through correlation and intersection analysis. CONCLUSION: This study uncovers TFs and target proteins related to electrophysiology and developmental pathogenicity in ATS myocardial cells, obtaining novel targets for potential therapeutic candidate development that does not rely on gene editing.

Temperature responses of leaf respiration in light and darkness are similar and modulated by leaf development.

Our ability to predict temperature responses of leaf respiration in light and darkness (RL and RDk ) is essential to models of global carbon dynamics. While many models rely on constant thermal sensitivity (characterized by Q10 ), uncertainty remains as to whether Q10 of RL and RDk are actually similar. We measured short-term temperature responses of RL and RDk in immature and mature leaves of two evergreen tree species, Castanopsis carlesii and Ormosia henry in an open field. RL was estimated by the Kok method, the Yin method and a newly developed Kok-iterCc method. When estimated by the Yin and Kok-iterCc methods, RL and RDk had similar Q10 (c. 2.5). The Kok method overestimated both Q10 and the light inhibition of respiration. RL /RDk was not affected by leaf temperature. Acclimation of respiration in summer was associated with a decline in basal respiration but not in Q10 in both species, which was related to changes in leaf nitrogen content between seasons. Q10 of RL and RDk in mature leaves were 40% higher than in immature leaves. Our results suggest similar Q10 values can be used to model RL and RDk while leaf development-associated changes in Q10 require special consideration in future respiration models.

Short- and long-term responses of leaf day respiration to elevated atmospheric CO2.

Evaluating leaf day respiration rate (RL), which is believed to differ from that in the dark (RDk), is essential for predicting global carbon cycles under climate change. Several studies have suggested that atmospheric CO2 impacts RL. However, the magnitude of such an impact and associated mechanisms remain uncertain. To explore the CO2 effect on RL, wheat (Triticum aestivum) and sunflower (Helianthus annuus) plants were grown under ambient (410 ppm) and elevated (820 ppm) CO2 mole fraction ([CO2]). RL was estimated from combined gas exchange and chlorophyll fluorescence measurements using the Kok method, the Kok-Phi method, and a revised Kok method (Kok-Cc method). We found that elevated growth [CO2] led to an 8.4% reduction in RL and a 16.2% reduction in RDk in both species, in parallel to decreased leaf N and chlorophyll contents at elevated growth [CO2]. We also looked at short-term CO2 effects during gas exchange experiments. Increased RL or RL/RDk at elevated measurement [CO2] were found using the Kok and Kok-Phi methods, but not with the Kok-Cc method. This discrepancy was attributed to the unaccounted changes in Cc in the former methods. We found that the Kok and Kok-Phi methods underestimate RL and overestimate the inhibition of respiration under low irradiance conditions of the Kok curve, and the inhibition of RL was only 6%, representing 26% of the apparent Kok effect. We found no significant long-term CO2 effect on RL/RDk, originating from a concurrent reduction in RL and RDk at elevated growth [CO2], and likely mediated by acclimation of nitrogen metabolism.

Half of the 18O enrichment of leaf sucrose is conserved in leaf cellulose of a C3 grass across atmospheric humidity and CO2 levels.

The 18O enrichment (Δ18O) of cellulose (Δ18OCel) is recognized as a unique archive of past climate and plant function. However, there is still uncertainty regarding the proportion of oxygen in cellulose (pex) that exchanges post-photosynthetically with medium water of cellulose synthesis. Particularly, recent research with C3 grasses demonstrated that the Δ18O of leaf sucrose (Δ18OSuc, the parent substrate for cellulose synthesis) can be much higher than predicted from daytime Δ18O of leaf water (Δ18OLW), which could alter conclusions on photosynthetic versus post-photosynthetic effects on Δ18OCel via pex. Here, we assessed pex in leaves of perennial ryegrass (Lolium perenne) grown at different atmospheric relative humidity (RH) and CO2 levels, by determinations of Δ18OCel in leaves, Δ18OLGDZW (the Δ18O of water in the leaf growth-and-differentiation zone) and both Δ18OSuc and Δ18OLW (adjusted for εbio, the biosynthetic fractionation between water and carbohydrates) as alternative proxies for the substrate for cellulose synthesis. Δ18OLGDZW was always close to irrigation water, and pex was similar (0.53 ± 0.02 SE) across environments when determinations were based on Δ18OSuc. Conversely, pex was erroneously and variably underestimated (range 0.02-0.44) when based on Δ18OLW. The photosynthetic signal fraction in Δ18OCel is much more constant than hitherto assumed, encouraging leaf physiological reconstructions.

Lidar AOD inversion and aerosol extinction profile correction method based on GA-BP neural network.

Lidar is an effective remote sensing method to obtain the vertical distribution of aerosols, and how to select the aerosol extinction-backscattering ratio (AE-BR) during the inversion process is a key step to guarantee the accuracy of the lidar inversion of aerosol optical thickness (AOD) and aerosol extinction coefficient profile (AECP). In this paper, an inversion algorithm for AOD and AECP based on a genetic BP (GA-BP) neural network is proposed. Simultaneous measurements are carried out using CE318 sun photometer and lidar, and the mapping relationship between the lidar echo signal and AOD is established based on the genetic BP (GA-BP) neural network method, which achieves the accurate inversion of AOD with an absolute error mean value of 0.0156. Based on the AOD output from the GA-BP neural network, the real-time best AE- BR to improve the inversion accuracy of AECP. Finally, practical tests show that the method achieves accurate inversion of AOD, determines the range of AE-BR from 20-50sr, realizes real-time dynamic correction of AECP, and has strong generalization ability and applicability in practical situations.

Improved reproducibility of γ-aminobutyric acid measurement from short-echo-time proton MR spectroscopy by linewidth-matched basis sets in LCModel.

γ-Aminobutyric acid (GABA), as the primary inhibitory neurotransmitter, is extremely important for maintaining healthy brain function, and deviations from GABA homeostasis are related to various brain diseases. Short-echo-time (short-TE) proton MR spectroscopy (1 H-MRS) has been employed to measure GABA concentration from various human brain regions at high magnetic fields. The aim of this study was to investigate the effect of spectral linewidth on GABA quantification and explore the application of an optimized basis-set preparation approach using a spectral-linewidth-matched (LM) basis set in LCModel to improve the reproducibility of GABA quantification from short-TE 1 H-MRS. In contrast to the fixed-linewidth basis-set approach, the LM basis-set preparation approach, where all metabolite basis spectra were simulated with a linewidth 4 Hz narrower than that of water, showed a smaller standard deviation of estimated GABA concentration from synthetic spectra with varying linewidths and lineshapes. The test-retest reproducibility was assessed by the mean within-subject coefficient of variation, which improved from 19.2% to 12.0% in the thalamus, from 27.9% to 14.9% in the motor cortex, and from 9.7% to 2.8% in the medial prefrontal cortex using LM basis sets at 7 T. We conclude that spectral linewidth has a large effect on GABA quantification from short-TE 1 H-MRS data and that using LM basis sets in LCModel can improve the reproducibility of GABA quantification.

δ13C of bulk organic matter and cellulose reveal post-photosynthetic fractionation during ontogeny in C4 grass leaves.

The 13C isotope composition (δ13C) of leaf dry matter is a useful tool for physiological and ecological studies. However, how post-photosynthetic fractionation associated with respiration and carbon export influences δ13C remains uncertain. We investigated the effects of post-photosynthetic fractionation on δ13C of mature leaves of Cleistogenes squarrosa, a perennial C4 grass, in controlled experiments with different levels of vapour pressure deficit and nitrogen supply. With increasing leaf age class, the 12C/13C fractionation of leaf organic matter relative to the δ13C of atmosphere CO2 (ΔDM) increased while that of cellulose (Δcel) was almost constant. The divergence between ΔDM and Δcel increased with leaf age class, with a maximum value of 1.6‰, indicating the accumulation of post-photosynthetic fractionation. Applying a new mass balance model that accounts for respiration and export of photosynthates, we found an apparent 12C/13C fractionation associated with carbon export of -0.5‰ to -1.0‰. Different ΔDM among leaves, pseudostems, daughter tillers, and roots indicate that post-photosynthetic fractionation happens at the whole-plant level. Compared with ΔDM of old leaves, ΔDM of young leaves and Δcel are more reliable proxies for predicting physiological parameters due to the lower sensitivity to post-photosynthetic fractionation and the similar sensitivity in responses to environmental changes.