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Abstract Prolonged mechanical ventilation (PMV) is commonly associated with increased post-operative complications and mortality. Nevertheless, the predictive factors of PMV after lung transplantation (LTx) using extracorporeal membrane oxygenation (ECMO) as a bridge remain unclear. The present study aimed to develop a novel nomogram for PMV prediction in patients using ECMO as a bridge to LTx. A total of 173 patients who used ECMO as a bridge following LTx from January 2022 to June 2023 were divided into the training (122) and validation sets (52). A mechanical ventilation density plot of patients after LTx was then performed. The training set was divided in two groups, namely PMV (95) and non-prolonged ventilation (NPMV) (27). For the survival analysis, the effect of PMV was assessed using the log-rank test. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was established based on the multivariate analysis, and model performance was further assessed in terms of calibration, discrimination, and clinical usefulness. Internal validation was additionally conducted. The difference in survival curves in PMV and NPMV groups was statistically significant (P

Abstract Background CRISPR/Cas-derived base editor enables precise editing of target sites and has been widely used for basic research and crop genetic improvement. However, the editing efficiency of base editors at different targets varies greatly. Results Here, we develop a set of highly efficient base editors in cotton plants. GhABE8e, which is fused to conventional nCas9, exhibits 99.9% editing efficiency, compared to GhABE7.10 with 64.9%, and no off-target editing is detected. We further replace nCas9 with dCpf1, which recognizes TTTV PAM sequences, to broaden the range of the target site. To explore the functional divergence of TERMINAL FLOWER 1 (TFL1), we edit the non-coding and coding regions of GhTFL1 with 26 targets to generate a comprehensive allelic population including 300 independent lines in cotton. This allows hidden pleiotropic roles for GhTFL1 to be revealed and allows us to rapidly achieve directed domestication of cotton and create ideotype germplasm with moderate height, shortened fruiting branches, compact plant, and early-flowering. Further, by exploring the molecular mechanism of the GhTFL1 L86P and GhTFL1 K53G+S78G mutations, we find that the GhTFL1 L86P mutation weakens the binding strength of the GhTFL1 to other proteins but does not lead to a complete loss of GhTFL1 function. Conclusions This strategy provides an important technical platform and genetic information for the study and creation of ideal plant architecture.

Abstract Insects pose significant challenges in cotton‐producing regions. Here, they describe a high‐throughput CRISPR/Cas9‐mediated large‐scale mutagenesis library targeting endogenous insect‐resistance‐related genes in cotton. This library targeted 502 previously identified genes using 968 sgRNAs, generated ≈2000 T0 plants and achieved 97.29% genome editing with efficient heredity, reaching upto 84.78%. Several potential resistance‐related mutants (10% of 200 lines) their identified that may contribute to cotton‐insect molecular interaction. Among these, they selected 139 and 144 lines showing decreased resistance to pest infestation and targeting major latex‐like protein 423 (GhMLP423) for in‐depth study. Overexpression of GhMLP423 enhanced insect resistance by activating the plant systemic acquired resistance (SAR) of salicylic acid (SA) and pathogenesis‐related (PR) genes. This activation is induced by an elevation of cytosolic calcium [Ca2+]cyt flux eliciting reactive oxygen species (ROS), which their demoted in GhMLP423 knockout (CR) plants. Protein‐protein interaction assays revealed that GhMLP423 interacted with a human epidermal growth factor receptor substrate15 (EPS15) protein at the cell membrane. Together, they regulated the systemically propagating waves of Ca2+ and ROS, which in turn induced SAR. Collectively, this large‐scale mutagenesis library provides an efficient strategy for functional genomics research of polyploid plant species and serves as a solid platform for genetic engineering of insect resistance.

Abstract Background Adelphocoris suturalis (Hemiptera: Miridae) is a notorious agricultural pest, which causes serious economic losses to a diverse range of agricultural crops around the world. The poor understanding of its genomic characteristics has seriously hindered the establishment of sustainable and environment-friendly agricultural pest management through biotechnology and biological insecticides. Results Here, we report a chromosome-level assembled genome of A. suturalis by integrating Illumina short reads, PacBio, 10x Chromium, and Hi-C mapping technologies. The resulting 1.29 Gb assembly contains twelve chromosomal pseudomolecules with an N50 of 1.4 and 120.6 Mb for the contigs and scaffolds, respectively, and carries 20,010 protein-coding genes. The considerable size of the A. suturalis genome is predominantly attributed to a high amount of retrotransposons, especially long interspersed nuclear elements (LINEs). Transcriptomic and phylogenetic analyses suggest that A. suturalis-specific candidate effectors, and expansion and expression of gene families associated with omnivory, insecticide resistance and reproductive characteristics, such as digestion, detoxification, chemosensory receptors and long-distance migration likely contribute to its strong environmental adaptability and ability to damage crops. Additionally, 19 highly credible effector candidates were identified and transiently overexpressed in Nicotiana benthamiana for functional assays and potential targeting for insect resistance genetic engineering. Conclusions The high-quality genome of A. suturalis provides an important genomic landscape for further investigations into the mechanisms of omnivory, insecticide resistance and survival adaptation, and for the development of integrated management strategies.

Abstract Background Somatic embryogenesis is a major process for plant regeneration. However, cell communication and the gene regulatory network responsible for cell reprogramming during somatic embryogenesis are still largely unclear. Recent advances in single-cell technologies enable us to explore the mechanism of plant regeneration at single-cell resolution. Results We generate a high-resolution single-cell transcriptomic landscape of hypocotyl tissue from the highly regenerable cotton genotype Jin668 and the recalcitrant TM-1. We identify nine putative cell clusters and 23 cluster-specific marker genes for both cultivars. We find that the primary vascular cell is the major cell type that undergoes cell fate transition in response to external stimulation. Further developmental trajectory and gene regulatory network analysis of these cell clusters reveals that a total of 41 hormone response-related genes, including LAX2, LAX1, and LOX3, exhibit different expression patterns in the primary xylem and cambium region of Jin668 and TM-1. We also identify novel genes, including CSEF, PIS1, AFB2, ATHB2, PLC2, and PLT3, that are involved in regeneration. We demonstrate that LAX2, LAX1 and LOX3 play important roles in callus proliferation and plant regeneration by CRISPR/Cas9 editing and overexpression assay. Conclusions This study provides novel insights on the role of the regulatory network in cell fate transition and reprogramming during plant regeneration driven by somatic embryogenesis.

To achieve real-time safety management of on-site power system work, the object detection algorithm of the cloud platform is transplanted into the edge computing device. However, due to the limited capacity and arithmetic power of the AI chip carried in the edge computing device, the algorithm needs to be studied in a lightweight manner. Therefore, this paper proposes an improved edge-side lightweight YOLOv4 (You Only Look Once version 4) algorithm, which is compressed and accelerated by improving the network structure and the confidence loss function of the algorithm without losing too much detection accuracy. Firstly, a lightweight convolutional neural network based on depthwise separable convolution and mobile inverted bottleneck convolution is constructed as the backbone network of YOLOv4, and the depthwise separable convolution is used instead of the conventional convolution, which can greatly reduce the parameters number and computation of the algorithm. Secondly, an improved bidirectional feature fusion network is constructed as the neck network of YOLOv4 algorithm to improve the information availability of multi-semantic features and enhance the extraction capability of small-scale features. Then, the confidence loss function of the algorithm is improved to alleviate the problems of uneven distribution of positive samples and negative samples and uneven distribution of easy-to-classify samples and hard-to-classify samples. Finally, the improved YOLOv4 algorithm is tested on an edge computing device equipped with an NVIDIA Jetson Xavier NX chip, and the dataset based on the compliance of on-site dress code in the electric power system field is tested. The experimental results show that, compared with the original YOLOv4 algorithm, the improved YOLOv4 algorithm reduces the parameters number by 93.11%, and the real-time video stream detection speed on the edge computing device is increased by 22.00%, reaching 15.05 FPS. The lightweight improved YOLOv4 algorithm is suitable for deployment at the edge end and can achieve real-time accurate identification of risks in the on-site work.

A “cloud-edge-end” collaborative system architecture is adopted for real-time security management of power system on-site work, and mobile edge computing equipment utilizes lightweight intelligent recognition algorithms for on- site risk assessment and alert. Owing to its lightweight and fast speed, YOLOv4-Tiny is often deployed on edge computing equipment for real-time video stream detection; however, its accuracy is relatively low. This study proposes an improved YOLOv4-Tiny algorithm based on attention mechanism and optimized training methods, achieving higher accuracy without compromising the speed. Specifically, a convolution block attention module branch is added to the backbone network to enhance the feature extraction capability and an efficient channel attention mechanism is added in the neck network to improve feature utilization. Moreover, three optimized training methods: transfer learning, mosaic data augmentation, and label smoothing are used to improve the training effect of this improved algorithm. Finally, an edge computing equipment experimental platform equipped with an NVIDIA Jetson Xavier NX chip is established and the newly developed algorithm is tested on it. According to the results, the speed of the improved YOLOv4-Tiny algorithm in detecting on-site dress code compliance datasets is 17.25 FPS, and the mean average precision (mAP) is increased from 70.89% to 85.03%.

Abstract Background Base editors (BEs) display diverse applications in a variety of plant species such as Arabidopsis, rice, wheat, maize, soybean, and cotton, where they have been used to mediate precise base pair conversions without the collateral generation of undesirable double-stranded breaks (DSB). Studies of single-nucleotide polymorphisms (SNPs) underpinning plant traits are still challenging, particularly in polyploidy species where such SNPs are present in multiple copies, and simultaneous modification of all alleles would be required for functional analysis. Allotetraploid cotton has a number of homoeologous gene pairs located in the A and D sub-genomes with considerable SNPs, and it is desirable to develop adenine base editors (ABEs) for efficient and precise A-to-G single-base editing without DSB in such complex genome. Results We established various ABE vectors based on different engineered adenosine deaminase (TadA) proteins fused to Cas9 variants (dCas9, nCas9), enabling efficient A to G editing up to 64% efficiency on-target sites of the allotetraploid cotton genome. Comprehensive analysis showed that GhABE7.10n exhibited the highest editing efficiency, with the main editing sites specifically located at the position A5 (counting the PAM as positions 21–23). Furthermore, DNA and RNA off-target analysis of cotton plants edited with GhABE7.10n and GhABE7.10d by whole genome and whole-transcriptome sequencing revealed no DNA off-target mutations, while very low-level RNA off-target mutations were detected. A new base editor, namely GhABE7.10dCpf1 (7.10TadA + dCpf1), that recognizes a T-rich PAM, was developed for the first time. Targeted A-to-G substitutions generated a single amino acid change in the cotton phosphatidyl ethanolamine-binding protein (GhPEBP), leading to a compact cotton plant architecture, an ideotype for mechanized harvesting of modern cotton production. Conclusions Our data illustrate the robustness of adenine base editing in plant species with complex genomes, which provides efficient and precise toolkit for cotton functional genomics and precise molecular breeding.

Aiming at the problem that the detection and damage recognition algorithm of insulator aerial images is difficult to be applied to the embedded platform, this paper proposed an improved Tiny-YOLOv4 lightweight target detection network algorithm. This algorithm combined the Self-Attention mechanism and ECA-Net (Efficient Channel Attention Neural Networks), which could greatly reduce the complexity of the original YOLOv4 algorithm, and the model size is 24.9 MB. Under the condition of ensuring the detection accuracy (>91%), the detection speed is as high as 94FPS. It is transplanted to the Jetson Xavier NX embedded platform, and the average detection speed reaches 22FPS, which effectively meets the real-time detection requirements in the power inspection.

Abstract Background Millennia of directional human selection has reshaped the genomic architecture of cultivated cotton relative to wild counterparts, but we have limited understanding of the selective retention and fractionation of genomic components. Results We construct a comprehensive genomic variome based on 1961 cottons and identify 456 Mb and 357 Mb of sequence with domestication and improvement selection signals and 162 loci, 84 of which are novel, including 47 loci associated with 16 agronomic traits. Using pan-genome analyses, we identify 32,569 and 8851 non-reference genes lost from Gossypium hirsutum and Gossypium barbadense reference genomes respectively, of which 38.2% (39,278) and 14.2% (11,359) of genes exhibit presence/absence variation (PAV). We document the landscape of PAV selection accompanied by asymmetric gene gain and loss and identify 124 PAVs linked to favorable fiber quality and yield loci. Conclusions This variation repertoire points to genomic divergence during cotton domestication and improvement, which informs the characterization of favorable gene alleles for improved breeding practice using a pan-genome-based approach.

Cotton (Gossypium hirsutum) is an important fiber crop worldwide. Insect attack causes cotton yield and quality losses. However, little is known about the mechanism of cotton response to insect attack. We simulated insect feeding by applying insect oral secretions (OS) to wounds, and combined transcriptome and metabolome analysis to investigate how OS from two major pest species (Helicoverpa armigera and Spodoptera litura) affect cotton defense responses. We found that respectively 12,668 and 13,379 genes were differentially expressed in comparison with wounding alone. On addition of OS, the jasmonic acid signaling pathway was rapidly and strongly induced, whereas genes involved in salicylic acid biosynthesis were downregulated. On constructing a coexpression gene network, we identified a hub gene encoding a leucine-rich repeat receptor kinase that may play an important role in early signal recognition and transduction. OS from the two insect species altered the abundance of flavonoid-related compounds in different patterns. Gossypol remained in lower concentration after OS application than after wounding alone, suggesting a suppressive effect of OS on cotton defense response. This study illustrated transcriptional and metabolic changes of cotton in responding to OS from two chewing insect species, identified potential key response genes, and revealed evidence for OS inhibition of wounding-induced cotton defense response.

Sap-sucking insects cause severe damage to cotton production. Long non-coding RNAs (lncRNAs) play vital regulatory roles in various development processes and stress response, however, the function of lncRNAs during sap-sucking insect infection in cotton is largely unknown. In this study, the transcriptome profiles between resistant (HR) and susceptible (ZS) cotton cultivars under whitefly infestation at different time points (0, 4, 12, 24, and 48 h) were compared. A total of 6,651 lncRNAs transcript and 606 differentially expressed lncRNAs were identified from the RNA-seq data. A co-expression network indicated that lncA07 and lncD09 were potential hub genes that play a regulatory role in cotton defense against aphid infestation. Furthermore, CRISPR/Cas9 knock-out mutant of lncD09 and lncA07 showed a decrease of jasmonic acid (JA) content, which potentially lead to increased susceptibility toward insect infestation. Differentially expressed genes between wild type and lncRNA knock-out plants are enriched in modulating development and resistance to stimulus. Additionally, some candidate genes such as Ghir_A01G022270, Ghir_D04G014430, and Ghir_A01G022270 are involved in the regulation of the JA-mediated signaling pathway. This result provides a novel insight of the lncRNA role in the cotton defense system against pests.

Abstract Background Wintersweet (Chimonanthus praecox), an important ornamental plant, has evolved unique fragrant aroma and winter-flowering properties, which are critical for its successful sexual reproduction. However, the molecular mechanisms underlying these traits are largely unknown in this species. In addition, wintersweet is also a typical representative species of the magnoliids, where the phylogenetic position of which relative to eudicots and monocots has not been conclusively resolved. Results Here, we present a chromosome-level wintersweet genome assembly with a total size of 695.36 Mb and a draft genome assembly of Calycanthus chinensis. Phylogenetic analyses of 17 representative angiosperm genomes suggest that Magnoliids and eudicots are sister to monocots. Whole-genome duplication signatures reveal two major duplication events in the evolutionary history of the wintersweet genome, with an ancient one shared by Laurales, and a more recent one shared by the Calycantaceae. Whole-genome duplication and tandem duplication events have significant impacts on copy numbers of genes related to terpene and benzenoid/phenylpropanoid (the main floral scent volatiles) biosynthesis, which may contribute to the characteristic aroma formation. An integrative analysis combining cytology with genomic and transcriptomic data reveals biological characteristics of wintersweet, such as floral transition in spring, floral organ specification, low temperature-mediated floral bud break, early blooming in winter, and strong cold tolerance. Conclusions These findings provide insights into the evolutionary history of wintersweet and the relationships among the Magnoliids, monocots, and eudicots; the molecular basis underlying floral scent biosynthesis; and winter flowering, and highlight the utility of multi-omics data in deciphering important ornamental traits in wintersweet.

Black pepper (Piper nigrum) belongs to the long-isolated lineage of basal angiosperm and its fruit has been used for food spice and phytomedicines for thousands of years. Here, the authors assemble the reference genome of this species and analyze gene families associated with piperine biosynthesis.

Upland cotton (Gossypium hirsutum), an allotetraploid, contains At- and Dt- subgenome and most genes have multiple homologous copies, which pose a huge challenge to investigate genes’ function due to the functional redundancy. Therefore, it is of great significance to establish effective techniques for the functional genomics in cotton. In this study, we tested two novel genome editing vectors and compared them with the CRISPR/Cas9 system (pRGEB32-GhU6.7) developed in our laboratory previously. In the first new vector, the sgRNA transcription unite was constructed into the replicon (LIR-Donor-SIR-Rep-LIR) of the bean yellow dwarf virus (BeYDV) and named as pBeYDV-Cas9-KO and in the second vector, the ubiquitin promoter that drives Cas9 protein was replaced with a constitutive CaMV 35S promoter and defined as pRGEB32-35S. The results from transgenic cotton calli/plants revealed that pBeYDV-Cas9-KO vector showed the highest editing efficiency of GhCLA1 in At and Dt subgenomes edited simultaneously up to 73.3% compared to the 44.6% of pRGEB32-GhU6.7 and 51.2% of pRGEB32-35S. The editing efficiency of GhCLA1 in At and Dt subgenome by pBeYDV-Cas9-KO was 85.7% and 97.2%, respectively, whereas the efficiency by pRGEB32-GhU6.7 and pRGEB32-35S vectors was 67.7%, 86.5%, 84%, and 87.2%, respectively. The editing profile of pBeYDV-Cas9-KO was mainly composed of fragment deletion, accounting for 84.0% and ranging 1–10 bp in length. The main editing sites are located at positions 11–17 upstream of PAM site. The off-target effects were not detected in all potential off-target sites. Taken together, the pBeYDV-Cas9-KO system has high editing efficiency and specificity with wide editing range than the traditional CRISPR/Cas9 system, which provides a powerful tool for cotton functional genomics research and molecular breeding.

Al films and TiO2 films were separately coated on AZ31 magnesium alloy substrates by means of magnetron sputtering method. The surface properties of the samples were explored and compared. Scanning electron microscope (SEM) observed the compact structure characteristics of as-deposited Al films and TiO2 films. After heat treatment under 200ºC for half an hour the films kept the compact structure characteristics and there didn’t exist structural defects on the surface of the films. Nano-indentation measurement results display that the micro-hardness of as-deposited Al film and TiO2 film reaches about 1.90 Gpa and 1.51 Gpa, separately. Al film is a bit harder than TiO2 film. Finally, the corrosion experiments in simulated body fluid initially indicate the different corrosion properties for Al film and TiO2 film. Al film presents more effective anti-corrosion properties than TiO2 film.

Cotton, a natural fiber producing crop of huge importance, is often prone to attack of Verticillium dahliae. Papain-like cysteine proteases (PLCPs) constitute a large family in plants and were proposed to involve in plant defense against pathogen attack in a number of studies. However, there is no detailed characterization of PLCP genes in cotton against infection of V. dahliae. In this study, we carried out a genome-wide analysis in cotton and identified seventy-eight PLCPs, which were divided into nine subfamilies based on their evolution phylogeny: RD21 (responsive to desiccation 21), CEP (cysteine endopeptidase), XCP (xylem cysteine peptidase), XBCP3 (xylem bark cysteine peptidase 3), THI, SAG12 (senescence-associated gene 12), RD19 (responsive to desiccation 19), ALP (aleurain-like protease) and CTB (cathepsin B-like). Genes in each subfamily exhibit a similar structure and motif composition. The expression patterns of these genes in different organs were examined, and subfamily RD21 was the most abundant in these families. Expression profiles under abiotic stress showed that thirty-five PLCP genes were induced by multiple stresses. Further transcriptome analysis showed that sixteen PLCP genes were up-regulated in response to V. dahliae in cotton. Among those, GhRD21-7 showed a higher transcription level than most other PLCP genes. Additionally, over-expression of GhRD21-7 led to enhanced resistance and RNAi lines were more susceptible to V. dahliae in cotton. Our results provide valuable information for future functional genomic studies of PLCP gene family in cotton.

Thermal groundwater is relatively abundant in the deep-seated bedrock underlying the Beijing plain area. The main geothermal reservoir is composed of dolomites of the Wumishan Group of the Meso−Neoproterozic Jixian System. The thermal groundwater has been developed and utilized since the 1970s and significant declines in groundwater levels were observed. A 3D unsteady flow model of an anisotropic karst-fissure aquifer based on the equivalent continuum is used to describe the flow of thermal groundwater and heat transport. The heat transportation is described by the governing equation including convection and dispersion. The simulation of this paper aims to solve such problems as uneven distribution and thinness of the aquifer, insufficient initial monitoring data, and poor knowledge of the properties of the horizontal boundary. They are solved by considering vertical stratification of the aquifer with equal thickness, replacing initial water level data by surface elevation, and choosing natural boundary far away from the exploitation areas. Through a trial−error procedure, the simulated and measured groundwater level and temperature in the simulation period are well fitted. Three exploitation schemes are proposed to predict the spatial and temporal changes in groundwater level and temperature of the thermal groundwater in the study area. The prediction results show that the reinjection can effectively slow the decline in the thermal groundwater levels. Except for the Dongnanchengqu, Xiaotangshan, and Liangxiang subgeothermal fields, the other six subgeothermal fields have the potential for further development of thermal groundwater.

BACKGROUND AND PURPOSE: Paired-like homeodomain transcription factor 3 (PITX3) is an important transcription factor for differentiation and survival of dopaminergic neurons. Recent reports have shown a strong association of polymorphisms in the PITX3 gene with Parkinson’s disease (PD). Our study was designed to verify whether three previous PITX3 SNPs (rs2281983, rs4919621 and rs3758549) were associated with PD in the Chinese population. We also investigate the association of novel polymorphisms in PITX3 gene with PD. METHODS: All the polymorphisms of PITX3 we found in this study were sequenced by PCR products from both directions with dye terminator methods using an ABI-3100 sequencer. We included 356 sporadic PD patients and 300 healthy elderly people as controls. RESULTS: We provide evidence for strong association of a novel polymorphism c.219G>A (p = 0.000307) with PD. Our data showed that the substitution of c.219G>A in PITX3 Exon 3 was significantly higher in PD compared with control. Previous finding suggesting three SNPs (rs2281983, rs4919621 and rs3758549) in the PITX3 gene to be associated with PD could not be replicated. CONCLUSIONS: Our findings indicate that a novel synonymous SNP in PITX3 gene may contribute to PD risk in the Chinese population.

A very small proportion of people remain negative for HIV infection after repeated HIV-1 viral exposure, which is called HIV-1 resistance. Understanding the mechanism of HIV-1 resistance is important for the development of HIV-1 vaccines and Acquired Immune Deficiency Syndrome (AIDS) therapies. In this study, we analyzed the gene expression profiles of CD4+ T cells from HIV-1-resistant individuals and HIV-susceptible individuals. One hundred eighty-five discriminative HIV-1 resistance genes were identified using the Minimum Redundancy-Maximum Relevance (mRMR) and Incremental Feature Selection (IFS) methods. The virus protein target enrichment analysis of the 185 HIV-1 resistance genes suggested that the HIV-1 protein nef might play an important role in HIV-1 infection. Moreover, we identified 29 infection information exchanger genes from the 185 HIV-1 resistance genes based on a virus-host interaction network analysis. The infection information exchanger genes are located on the shortest paths between virus-targeted proteins and are important for the coordination of virus infection. These proteins may be useful targets for AIDS prevention or therapy, as intervention in these pathways could disrupt communication with virus-targeted proteins and HIV-1 infection.

Deubiquitinating enzymes (DUBs) are important regulators of cell proliferation. Here we identified a functional deubiquitinating enzyme, ovarian tumor domain-containing 6B (OTUD-6B). Mutation of the conserved Cys residue abolished its deubiquitinating activity in vitro. Otud-6b expression was induced with cytokine stimulation in both mouse Ba/F3 cells and primary B lymphocytes followed a rapid decrease. This rapid decrease was partially facilitated by tristetraprolin (TTP) destabilization of Otud-6b mRNA through AU-rich motifs. Enforced expression of OTUD-6B in Ba/F3 cells could block cell proliferation by arresting cells in G1 phase. In addition, cyclin D2 level was down-regulated when OTUD-6B WT was overexpressed. Therefore, down-regulation of Otud-6b expression after prolonged cytokine stimulation may be required for cell proliferation in B lymphocytes.

Protein concentrations depend not only on the mRNA level, but also on the translation rate and the degradation rate. Prediction of mRNA's translation rate would provide valuable information for in-depth understanding of the translation mechanism and dynamic proteome. In this study, we developed a new computational model to predict the translation rate, featured by (1) integrating various sequence-derived and functional features, (2) applying the maximum relevance & minimum redundancy method and incremental feature selection to select features to optimize the prediction model, and (3) being able to predict the translation rate of RNA into high or low translation rate category. The prediction accuracies under rich and starvation condition were 68.8% and 70.0%, respectively, evaluated by jackknife cross-validation. It was found that the following features were correlated with translation rate: codon usage frequency, some gene ontology enrichment scores, number of RNA binding proteins known to bind its mRNA product, coding sequence length, protein abundance and 5'UTR free energy. These findings might provide useful information for understanding the mechanisms of translation and dynamic proteome. Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale.

As an important tumor suppressor protein, reactivate mutated p53 was found in many kinds of human cancers and that restoring active p53 would lead to tumor regression. In this work, we developed a new computational method to predict the transcriptional activity for one-, two-, three- and four-site p53 mutants, respectively. With the approach from the general form of pseudo amino acid composition, we used eight types of features to represent the mutation and then selected the optimal prediction features based on the maximum relevance, minimum redundancy, and incremental feature selection methods. The Mathew's correlation coefficients (MCC) obtained by using nearest neighbor algorithm and jackknife cross validation for one-, two-, three- and four-site p53 mutants were 0.678, 0.314, 0.705, and 0.907, respectively. It was revealed by the further optimal feature set analysis that the 2D (two-dimensional) structure features composed the largest part of the optimal feature set and maybe played the most important roles in all four types of p53 mutant active status prediction. It was also demonstrated by the optimal feature sets, especially those at the top level, that the 3D structure features, conservation, physicochemical and biochemical properties of amino acid near the mutation site, also played quite important roles for p53 mutant active status prediction. Our study has provided a new and promising approach for finding functionally important sites and the relevant features for in-depth study of p53 protein and its action mechanism.