Further Evaluation of Teaching Behavior Technicians to Input Data and Graph Using GraphPad Prism

Comparing instructor-led, video-model, and no-instruction control tutorials for creating single-subject graphs in Microsoft Excel: A systematic replication and extension

Visual inspection of single-subject data is the primary method for behavior analysts to interpret the effect of an independent variable on a dependent variable; however, there is no consensus on the most suitable method for teaching graph construction for single-subject designs. We systematically replicated and extended Tyner and Fienup (2015) using a repeated-measures between-subjects design to compare the effects of instructor-led, video-model, and no-instruction control tutorials on the graphing performance of 81 master's students with some reported Microsoft Excel experience. Our mixed-design analysis revealed a statistically significant main effect of pretest, tutorial, and posttest submissions for each tutorial group and a nonsignificant main effect of tutorial group. Tutorial group significantly interacted with submissions, suggesting that both instructor-led and video-model tutorials may be superior to providing graduate students with a written list of graphing conventions (i.e., control condition). Finally, training influenced performance on an untrained graph type (multielement) for all tutorial groups.

Selection and validation of a novel set of specific differential methylation markers and construction of a random forest prediction model for the accurate tissue origin identifications of body fluids involving young and middle-aged group of Chinese Han population

The identification of tissue origin of body fluid is helpful to the determination of the case nature and the reproduction of the case process. It has been confirmed that tissue-specific differential methylation markers could be used to identify the tissue origins of different body fluids. To select suitable tissue-specific differential methylation markers and establish the efficient typing system which could be applied to the identifications of body fluids in forensic cases involving Chinese Han individuals of young and middle-aged group, a total of 125 body fluids (venous blood, semen, vaginal fluid, saliva, and menstrual blood) were collected from healthy Chinese Han volunteers aged 20-45 years old. After genome-wide explorations of DNA methylation patterns in these five kinds of body fluids based on the Illumina Infinium Methylation EPIC BeadChip, 15 novel body fluid-specific differential CpGs were selected and verified based on the pyrosequencing method. And these identification efficiencies for target body fluids were verified by ROC curves. The pyrosequencing results indicated that the average methylation rates of nine CpGs were consistent with those of DNA methylation chip detection results, and the other five CpGs (except for cg12152558) were still helpful for the tissue origin identifications of target body fluids. Finally, a random forest classification prediction model based on these 14 CpGs was constructed to successfully identify five kinds of body fluids, and the tested accuracy rates all reached 100%.

Integrative bioinformatics and validation studies reveal KDM6B and its associated molecules as crucial modulators in Idiopathic Pulmonary Fibrosis

Background

Idiopathic Pulmonary Fibrosis (IPF) can be described as a debilitating lung disease that is characterized by the complex interactions between various immune cell types and signaling pathways. Chromatin-modifying enzymes are significantly involved in regulating gene expression during immune cell development, yet their role in IPF is not well understood.

Methods

In this study, differential gene expression analysis and chromatin-modifying enzyme-related gene data were conducted to identify hub genes, common pathways, immune cell infiltration, and potential drug targets for IPF. Additionally, a murine model was employed for investigating the expression levels of candidate hub genes and determining the infiltration of different immune cells in IPF.

Results

We identified 33 differentially expressed genes associated with chromatin-modifying enzymes. Enrichment analyses of these genes demonstrated a strong association with histone lysine demethylation, Sin3-type complexes, and protein demethylase activity. Protein-protein interaction network analysis further highlighted six hub genes, specifically KDM6B, KDM5A, SETD7, SUZ12, HDAC2, and CHD4. Notably, KDM6B expression was significantly increased in the lungs of bleomycin-induced pulmonary fibrosis mice, showing a positive correlation with fibronectin and α-SMA, two essential indicators of pulmonary fibrosis. Moreover, we established a diagnostic model for IPF focusing on KDM6B and we also identified 10 potential therapeutic drugs targeting KDM6B for IPF treatment.

Conclusion

Our findings suggest that molecules related to chromatin-modifying enzymes, primarily KDM6B, play a critical role in the pathogenesis and progression of IPF.

DNA methylation regulatory patterns and underlying pathways behind the co-pathogenesis of allergic rhinitis and chronic spontaneous urticaria

Background

Allergic rhinitis (AR) and chronic spontaneous urticaria (CSU) are often concurrent in patients. Changes in DNA methylation affect T cell biological processes, which may explain the occurrence and progression of comorbidity. However, downstream regulatory pathways of DNA methylation in two diseases and the underlying mechanisms have not been fully elucidated.

Methods

The GSE50101, GSE72541, GSE50222 and OEP002482 were mined for the identification of differentially expressed genes (DEGs) or co-expressed genes and differentially methylated genes (DMGs) in AR and CSU patients. We applied GO analysis and consensus clustering to study the potential functions and signal pathways of selected genes in two diseases. GSVA and logistic regression analysis were used to find the regulatory pathway between DNA methylation and activation patterns of CD4+ T cells. Besides, we used the Illumina 850k chip to detect DNA methylation expression profiles and recognize the differentially methylated CpG positions (DMPs) on corresponding genes. Finally, we annotated the biological process of these genes using GO and KEGG pathway analysis.

Result

The AR-related DEGs were found closely related to the differentiation and activation of CD4+ T cells. The DEGs or co-expressed genes of CD4+ T cells in AR and CSU patients were also clustered using GO and KEGG analysis and we got 57 co-regulatory pathways. Furthermore, logistic regression analysis showed that the regulation of cellular component size was closely related to the activation of CD4+ T cells regulated by DNA methylation. We got self-tested data using the Illumina 850k chip and identified 98 CpGs that were differentially methylated in patients. Finally, we mapped the DMPs to 15 genes and found that they were mainly enriched in the same CD4+T cell regulating pathway.

Conclusion

Our study indicated that DNA methylation affected by pollen participated in the activation patterns of CD4 + T cells, providing a novel direction for the symptomatic treatment of the co-occurrence of AR and CSU.

Integrated bioinformatics to identify potential key biomarkers for COVID-19-related chronic urticaria

Background

A lot of studies have revealed that chronic urticaria (CU) is closely linked with COVID-19. However, there is a lack of further study at the gene level. This research is aimed to investigate the molecular mechanism of COVID-19-related CU via bioinformatic ways.

Methods

The RNA expression profile datasets of CU (GSE72540) and COVID-19 (GSE164805) were used for the training data and GSE57178 for the verification data. After recognizing the shared differently expressed genes (DEGs) of COVID-19 and CU, genes enrichment, WGCNA, PPI network, and immune infiltration analyses were performed. In addition, machine learning LASSO regression was employed to identify key genes from hub genes. Finally, the networks, gene-TF-miRNA-lncRNA, and drug-gene, of key genes were constructed, and RNA expression analysis was utilized for verification.

Results

We recognized 322 shared DEGs, and the functional analyses displayed that they mainly participated in immunomodulation of COVID-19-related CU. 9 hub genes (CD86, FCGR3A, AIF1, CD163, CCL4, TNF, CYBB, MMP9, and CCL3) were explored through the WGCNA and PPI network. Moreover, FCGR3A, TNF, and CCL3 were further identified as key genes via LASSO regression analysis, and the ROC curves confirmed the dependability of their diagnostic value. Furthermore, our results showed that the key genes were significantly associated with the primary infiltration cells of CU and COVID-19, such as mast cells and macrophages M0. In addition, the key gene-TF-miRNA-lncRNA network was constructed, which contained 46 regulation axes. And most lncRNAs of the network were proved to be a significant expression in CU. Finally, the key gene-drug interaction network, including 84 possible therapeutical medicines, was developed, and their protein-protein docking might make this prediction more feasible.

Conclusions

To sum up, FCGR3A, TNF, and CCL3 might be potential biomarkers for COVID-19-related CU, and the common pathways and related molecules we explored in this study might provide new ideas for further mechanistic research.

Transcriptomic analysis of succulent stem development of Chinese kale (Brassica oleracea var. alboglabra Bailey) and its synthetic allotetraploid via RNA sequencing

Chinese kale (Brassica oleracea var. alboglabra Bailey, CC) is a succulent stem vegetable in the Brassica family. Its allotetraploid (AACC) vegetable germplasm, which was synthesized via distant hybridization with the colloquially named 'yellow turnip' (B. rapa L. ssp. rapifera Matzg., AA), has a swelling stem similar to CC. To address the molecular mechanism of stem development for CC and AACC, RNA sequencing (RNA-seq) was used to investigate transcriptional regulation of their stem development at three key stages including 28 days, 42 days and the bolting stage (BS) after sowing. As a result, 32,642, 32,665, 33,816, 32,147, 32,293 and 32,275 genes were identified in six corresponding cDNA libraries. Among them, 25,459 genes were co-expressed, while 7,183, 7,206, 8,357, 6,688, 6,834 and 6,814 genes were specifically expressed. Additionally, a total of 29,222 differentially expressed genes (DEGs) were found for functional enrichment as well as many genes involved in plant hormones including gibberellin (GA), abscisic acid (ABA), cytokinin (CTK) and auxin (AUX). Based on gene expression consistency between CC and AACC, the gene families including DELLA, GID, PYR/PYL, PP2C, A-ARR and AUX/IAA might be related to stem development. Among these, eight genes including Bo00834s040, Bo5g093140, Bo6g086770, Bo9g070200, Bo7g116570, Bo3g054410, Bo7g093470 and Bo5g136600 may play important roles in stem development based on their remarkable expression levels as confirmed by qRT-PCR. These findings provide a new theoretical basis for understanding the molecular mechanism of stem development in Brassica vegetable stem breeding.

Alterations in Microbiota and Metabolites Related to Spontaneous Diabetes and Pre-Diabetes in Rhesus Macaques

Spontaneous type 2 diabetes mellitus (T2DM) macaques are valuable resources for our understanding the pathological mechanism of T2DM. Based on one month’s fasting blood glucose survey, we identified seven spontaneous T2DM macaques and five impaired glucose regulation (IGR) macaques from 1408 captive individuals. FPG, HbA1c, FPI and IR values were significant higher in T2DM and IGR than in controls. 16S rRNA sequencing of fecal microbes showed the significantly greater abundance of Oribacterium, bacteria inhibiting the production of secondary bile acids, and Phascolarctobacterium, bacteria producing short-chain fatty acids was significantly lower in T2DM macaques. In addition, several opportunistic pathogens, such as Mogibacterium and Kocuria were significantly more abundant in both T2DM and IGR macaques. Fecal metabolites analysis based on UHPLC-MS identified 50 differential metabolites (DMs) between T2DM and controls, and 26 DMs between IGR and controls. The DMs were significantly enriched in the bile acids metabolism, fatty acids metabolism and amino acids metabolism pathways. Combining results from physiochemical parameters, microbiota and metabolomics, we demonstrate that the imbalance of gut microbial community leading to the dysfunction of glucose, bile acids, fatty acids and amino acids metabolism may contribute to the hyperglycaemia in macaques, and suggest several microbes and metabolites are potential biomarkers for T2DM and IGR macaques.

A concise review of recent advancements in the graphical training of behavior analysts

This Concise Review is an appraisal of contemporary research on teaching single-case experimental design (SCED) graphical creation published between 2017-2021. Recent work on SCED graphical creation is summarized and areas for future research are highlighted.

Novel Insight into the Potential Role of Acylglycerophosphate Acyltransferases Family Members on Triacylglycerols Synthesis in Buffalo

Acylglycerophosphate acyltransferases (AGPATs) are the rate-limiting enzymes for the de novo pathway of triacylglycerols (TAG) synthesis. Although AGPATs have been extensively explored by evolution, expression and functional studies, little is known on functional characterization of how many members of the AGPAT family are involved in TAG synthesis and their impact on the cell proliferation and apoptosis. Here, 13 AGPAT genes in buffalo were identified, of which 12 AGPAT gene pairs were orthologous between buffalo and cattle. Comparative transcriptomic analysis and real-time quantitative reverse transcription PCR (qRT-PCR) further showed that both AGPAT1 and AGPAT6 were highly expressed in milk samples of buffalo and cattle during lactation. Knockdown of AGPAT1 or AGPAT6 significantly decreased the TAG content of buffalo mammary epithelial cells (BuMECs) and bovine mammary epithelial cells (BoMECs) by regulating lipogenic gene expression (p < 0.05). Knockdown of AGPAT1 or AGPAT6 inhibited proliferation and apoptosis of BuMECs through the expression of marker genes associated with the proliferation and apoptosis (p < 0.05). Our data confirmed that both AGPAT1 and AGPAT6 could regulate TAG synthesis and growth of mammary epithelial cells in buffalo. These findings will have important implications for understanding the role of the AGPAT gene in buffalo milk performance.

Integrated Bioinformatics and Validation Reveal IL1B and Its Related Molecules as Potential Biomarkers in Chronic Spontaneous Urticaria

Background

The etiopathogenesis of chronic spontaneous urticaria (CSU) has not been fully understood, and there has been extensive interest in the interaction between inflammatory dermatosis and pyroptosis. This study intends to investigate the molecular mechanism of pyroptosis-related genes in CSU via bioinformatic ways, aiming at identifying the potential key biomarker.

Methods

GSE72540, the RNA expression profile dataset of CSU, was utilized as the training set, and GSE57178 as the validation set. Differently expressed pyroptosis-related genes (DEPRGs), GO, KEGG, and DO analyses were performed. The hub genes were explored by the protein–protein interaction analysis. Moreover, CIBERSORT was employed for estimating immune cell types and proportions. Then, we constructed a DEmRNA–miRNA–DElncRNA ceRNA network and a drug–gene interaction network. Finally, ELISA was used for gene expression analysis.

Results

We recognized 17 DEPRGs, whose enrichment analyses showed that they were mostly enriched in inflammatory response and immunomodulation. Moreover, 5 hub genes (IL1B, TNF, and IRF1 are upregulated, HMGB1 and P2RX7 are downregulated) were identified via the PPI network and verified by a validation set. Then immune infiltration analysis displayed that compared with normal tissue, CSU owned a significantly higher proportion of mast cells activated, but a lower proportion of T cells CD4 naive and so on. Furthermore, IL1B was statistically and positively associated with mast cells activated in CSU, and SNHG3, the upstream factor of IL1B in the ceRNA we constructed, also related with mast cells in CSU. Further analysis exhibited that the protein subcellular localization of IL1B was extracellular, according with its intercellular regulation role; IL1B was significantly correlated with key immune checkpoints; and the NOD-like receptor signaling pathway was the mainly involved pathway of IL1B based on the couple databases. What is more, the result of ELISA of CSU patients was the same as the above analyses about IL1B. In addition, the drug–gene interaction network contained 15 potential therapeutic drugs targeting IL1B, and molecular docking might make this relationship viable.

Conclusion

IL1B and its related molecules might play a key role in the development of CSU and could be potential biomarkers in CSU.

Using GraphPad Prism's Heat Maps for Efficient, Fine-Grained Analyses of Single-Case Data

Behavior analysts sometimes consider various forms of data analysis when making clinical decisions and when attempting to illuminate interesting relations in existing datasets. For example, an ongoing plot of when problem behavior occurs across days and times can yield useful information regarding the function(s) of problem behavior. In a post-hoc analysis, a plot of within-session error patterns can reveal which variables may be contributing to faulty stimulus control. Such analyses can be burdensome to conduct manually (e.g., changing the color of individual data points based on error type), and more efficient methods (e.g., using conditional formatting in Microsoft Excel data tables) might not be conducive for producing publication-quality figures. In the present article, we provide an overview of how behavior analysts can use GraphPad Prism's heat-map feature to efficiently populate fine-grained graphs of behavior with data points that are coded automatically (e.g., with categorical colors or gradients). Implications for clinical utility and research production are discussed.

Transcriptome profiling reveals key genes in regulation of the tepal trichome development in Lilium pumilum D.C

A number of potential genes and pathways involved in tepal trichome development were identified in a natural lily mutant by transcriptome analysis and were confirmed with trichome and trichomeless species. Trichome is a specialized structure found on the surface of the plant with an important function in survival against abiotic and biotic stress. It is also an important economic trait in crop breeding. Extensive research has investigated the foliar trichome in model plants (Arabidopsis and tomato). However, the developmental mechanism of tepal trichome remains elusive. Lilium pumilum is an edible ornamental bulb and a good breeding parent possessing cold and salt-alkali resistance. Here, we found a natural mutant of Lilium pumilum grown on a highland whose tepals are covered by trichomes. Our data indicate that trichomes of the mutant are multicellular and branchless. Notably, stomata are also developed on the tepal of the mutant as well, suggesting there may be a correlation between trichome and stomata regulation. Furthermore, we isolated 27 differentially expressed genes (DEGs) by comparing the transcriptome profiling between the natural mutant and the wild type. These 27 genes belong to 4 groups: epidermal cell cycle and division, trichome morphogenesis, stress response, and transcription factors. Quantitative real-time PCR in Lilium pumilum (natural mutant and the wild type) and other lily species (Lilium leichtlinii var. maximowiczii/trichome; Lilium davidii var. willmottiae/, trichomeless) confirmed the validation of RNA-seq data and identified several trichome-related genes.