Molecular phylogenetic characterization and analysis of the WRKY transcription factor family responsive to Rhizoctonia solani in maize

In this study we have identified, based on the maize genome, 85 WRKY genes that were phylogenetically clustered into three families formed by 8 distinct subfamilies. The exon/intron structures and motif compositions of these WRKY genes were highly conserved in each subfamily suggesting their functional conservation. Moreover, based on qTelller analyses, the majority of these WRKY genes showed a specific temporal and spatial expression pattern. These WRKY genes, within the same group, manifested a distinct expression, indicating a similar function in their expression during the evolutionary process; this is reflected by their sub-functionalizations in their expression pattern concerning leaf developmental gradient, while mature bundle sheath, and mesophyll cells had a similar cellular localization and modality of expression. This study has also provided evidence of the presence of a subset of WRKY genes exhibiting a putative functional role in leaf sheath when infected with Rhizoctonia solani. This finding appears helpful for future functional investigations to unravel the roles of WRKY genes in plant pathogen resistance. Interestingly, in this study we have identified three WRKY genes that are predicted to be potential targets of miR160 and miR171b families. Therefore, this finding appears relevant in elucidating the biological functions of these transcription factors to clarify the molecular mechanisms affecting leaf sheath growth and development during fungal infection and plant resistance

Identification of miRNAs and their target genes in developing maize ears by combined small RNA and degradome sequencing

Background In plants, microRNAs (miRNAs) are endogenous ~22 nt RNAs that play important regulatory roles in many aspects of plant biology, including metabolism, hormone response, epigenetic control of transposable elements, and stress response. Extensive studies of miRNAs have been performed in model plants such as rice and Arabidopsis thaliana. In maize, most miRNAs and their target genes were analyzed and identified by clearly different treatments, such as response to low nitrate, salt and drought stress. However, little is known about miRNAs involved in maize ear development. The objective of this study is to identify conserved and novel miRNAs and their target genes by combined small RNA and degradome sequencing at four inflorescence developmental stages. Results We used deep-sequencing, miRNA microarray assays and computational methods to identify, profile, and describe conserved and non-conserved miRNAs at four ear developmental stages, which resulted in identification of 22 conserved and 21-maize-specific miRNA families together with their corresponding miRNA*. Comparison of miRNA expression in these developmental stages revealed 18 differentially expressed miRNA families. Finally, a total of 141 genes (251 transcripts) targeted by 102 small RNAs including 98 miRNAs and 4 ta-siRNAs were identified by genomic-scale high-throughput sequencing of miRNA cleaved mRNAs. Moreover, the differentially expressed miRNAs-mediated pathways that regulate the development of ears were discussed. Conclusions This study confirmed 22 conserved miRNA families and discovered 26 novel miRNAs in maize. Moreover, we identified 141 target genes of known and new miRNAs and ta-siRNAs. Of these, 72 genes (117 transcripts) targeted by 62 differentially expressed miRNAs may attribute to the development of maize ears. Identification and characterization of these important classes of regulatory genes in maize may improve our understanding of molecular mechanisms controlling ear development

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Overview of Artificial Intelligence in Breast Cancer Medical Imaging

The heavy global burden and mortality of breast cancer emphasize the importance of early diagnosis and treatment. Imaging detection is one of the main tools used in clinical practice for screening, diagnosis, and treatment efficacy evaluation, and can visualize changes in tumor size and texture before and after treatment. The overwhelming number of images, which lead to a heavy workload for radiologists and a sluggish reporting period, suggests the need for computer-aid detection techniques and platform. In addition, complex and changeable image features, heterogeneous quality of images, and inconsistent interpretation by different radiologists and medical institutions constitute the primary difficulties in breast cancer screening and imaging diagnosis. The advancement of imaging-based artificial intelligence (AI)-assisted tumor diagnosis is an ideal strategy for improving imaging diagnosis efficient and accuracy. By learning from image data input and constructing algorithm models, AI is able to recognize, segment, and diagnose tumor lesion automatically, showing promising application prospects. Furthermore, the rapid advancement of “omics” promotes a deeper and more comprehensive recognition of the nature of cancer. The fascinating relationship between tumor image and molecular characteristics has attracted attention to the radiomic and radiogenomics, which allow us to perform analysis and detection on the molecular level with no need for invasive operations. In this review, we integrate the current developments in AI-assisted imaging diagnosis and discuss the advances of AI-based breast cancer precise diagnosis from a clinical point of view. Although AI-assisted imaging breast cancer screening and detection is an emerging field and draws much attention, the clinical application of AI in tumor lesion recognition, segmentation, and diagnosis is still limited to research or in limited patients’ cohort. Randomized clinical trials based on large and high-quality cohort are lacking. This review aims to describe the progress of the imaging-based AI application in breast cancer screening and diagnosis for clinicians

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy

Image_4_Tissue-specific transcriptomic analysis uncovers potential roles of natural antisense transcripts in Arabidopsis heat stress response.PDF

Natural antisense transcripts (NATs) are an important class of non-coding ribonucleic acids (RNAs) that have been shown to regulate gene expression. Using strand-specific RNA sequencing, 36,317 NAT pairs were identified, and 5,536 were specifically expressed under heat stress. We found distinct expression patterns between vegetative and reproductive tissues for both coding genes and genes encoding NATs. Genes for heat-responsive NATs are associated with relatively high levels of H3K4me3 and low levels of H3K27me2/3. On the other hand, small RNAs are significantly enriched in sequence overlapping regions of NAT pairs, and a large number of heat-responsive NATs pairs serve as potential precursors of nat-siRNAs. Collectively, our results suggest epigenetic modifications and small RNAs play important roles in the regulation of NAT expression, and highlight the potential significance of heat-inducible NATs.</p

Cross-cultural adaptation and psychometric properties of the Chinese version of the Person-Centered Maternity Care Scale

Abstract Background Increasing evidence show that women across the world face unacceptable mistreatment during childbirth. Person-centered maternity care is fundamental and essential to quality of healthcare services. The aim of this study was to translate and determine the psychometric properties of the Person-Centered Maternity Care (PCMC) Scale among Chinese postpartum women. Methods A cross-sectional study was conducted among 1235 post-partum women in China. The cross-cultural adaptation process followed the Beaton intercultural debugging guidelines. A total of 1235 women were included to establish the psychometric properties of the PCMC. A demographic characteristics form and the PCMC were used for data collection. The psychometric properties of the PCMC were evaluated by examining item analysis, exploratory factor analysis, known-groups discriminant validity, and internal consistency. Results The number of extracted common factors was limited to three (dignity & respect, communication & autonomy, supportive care), explaining a total variance of 40.8%. Regarding internal consistency, the Cronbach’s alpha coefficient and split-half reliability of the full PCMC score were 0.989 and 0.852, respectively. Conclusions The Chinese version of the PCMC is a reliable and valid tool to assess person-centered care during childbirth in China

Image_8_Tissue-specific transcriptomic analysis uncovers potential roles of natural antisense transcripts in Arabidopsis heat stress response.PDF

Natural antisense transcripts (NATs) are an important class of non-coding ribonucleic acids (RNAs) that have been shown to regulate gene expression. Using strand-specific RNA sequencing, 36,317 NAT pairs were identified, and 5,536 were specifically expressed under heat stress. We found distinct expression patterns between vegetative and reproductive tissues for both coding genes and genes encoding NATs. Genes for heat-responsive NATs are associated with relatively high levels of H3K4me3 and low levels of H3K27me2/3. On the other hand, small RNAs are significantly enriched in sequence overlapping regions of NAT pairs, and a large number of heat-responsive NATs pairs serve as potential precursors of nat-siRNAs. Collectively, our results suggest epigenetic modifications and small RNAs play important roles in the regulation of NAT expression, and highlight the potential significance of heat-inducible NATs.</p