Deletion Strategy Research Articles

7260 Nuclear Corepressor 1 (NCoR1) plays important role in the regulation of insulin gene transcription in mouse Min6 pancreatic beta cells

Abstract Disclosure: H. Shimizu: None. Y. Horibata: None. I. Amano: None. M.J. Ritter: None. M. Ohyama: None. M. Domae: None. H. Sugimoto: None. A.N. Hollenberg: None. Background: Nuclear Corepressor 1 (NCoR1) is a transcriptional corepressor which has been recognized as an important player in the regulation of hepatic lipogenesis and hematopoiesis in mouse embryo. NCoR1 is also widely expressed in mouse insulin sensitive organs, for instance adipocyte, skeletal muscle, and hepatocytes. Mouse genetic deletion strategies of either NCoR1 or SMRT(NCoR2; an ortholog corepressor of NCoR1) demonstrated that each corepressor effects the insulin sensitivity in the tissues. However, the role of each corepressor in pancreatic beta cell is not still elucidated. Methods: To clarify this, we took the gene-targeting strategy for NCoR1 using CRISPR Cas-9 and made the pancreatic beta Min6 clone which lacks NCoR1 protein (Min6-NCoR1KO; NKO cells). For this study, wild type Min6 cells (WT) and NKO cells were cultured in the Dulbecco's DMEM medium with 10% fetal bovine serum for 4-5 days, and the expression analyses compared between two cell types were performed. Results: Both comprehensive proteomics and following expression analyses compared between WT and NKO cells demonstrated that NKO cells have significantly lower expression level of insulin (INS-1 and INS-2), accompanied with high expression of histone deacetylase 6 (HDAC6). For further analyses, we also made the Min6 clone which lacks SMRT(Min6-SMRTKO; SKO cells). Interestingly, SKO cell had higher insulin and lower HDAC6 levels, accompanied with significant up-regulation of NCoR1. Conclusion: Taken together, these data indicate that NCoR1 has dominant effects in the regulation of both histone deacetylation and insulin gene transcription in Min6 cells. Further investigations for the function of NCoR1 in the insulin gene transcription observed in Min6 cells will be needed. Presentation: 6/2/2024

CHIR99021 and Brdu Are Critical in Chicken iPSC Reprogramming via Small-Molecule Screening.

Background/Objectives: Induced pluripotent stem cells (iPSCs) reprogrammed from somatic cells into cells with most of the ESC (embryonic stem cell) characteristics show promise toward solving ethical problems currently facing stem cell research and eventually yield clinical grade pluripotent stem cells for therapies and regenerative medicine. In recent years, an increasing body of research suggests that the chemical induction of pluripotency (CIP) method can yield iPSCs in vitro, yet its application in avian species remains unreported. Methods: Herein, we successfully obtained stably growing chicken embryonic fibroblasts (CEFs) using the tissue block adherence method and employed 12 small-molecule compounds to induce chicken iPSC formation. Results: The final optimized iPSC induction system was bFGF (10 ng/mL), CHIR99021 (3 μM), RepSox (5 μM), DZNep (0.05 μM), BrdU (10 μM), BMP4 (10 ng/mL), vitamin C (50 μg/mL), EPZ-5676 (5 μM), and VPA (0.1 mM). Optimization of the induction system revealed that the highest number of clones was induced with 8 × 104 cells per well and at 1.5 times the original concentration. Upon characterization, these clones exhibited iPSC characteristics, leading to the development of a stable compound combination for iPSC generation in chickens. Concurrently, employing a deletion strategy to investigate the functionality of small-molecule compounds during induction, we identified CHIR99021 and BrdU as critical factors for inducing chicken iPSC formation. Conclusions: In conclusion, this study provides a reference method for utilizing small-molecule combinations in avian species to reprogram cells and establish a network of cell fate determination mechanisms.

BCDA: A blockchain-based dynamic auditing scheme for intelligent IoT

Intelligent Internet of Things (IoT) provides services for machine learning applications by collecting real-time data, where data correctness crucially impacts the training accuracy of models. Data owners host incremental real-time data in the cloud and use blockchain as a public platform for data query, usage, and certification. Malicious attackers may manipulate data through methods like data poisoning, compromising model parameters. Blockchain-based data integrity verification (auditing) schemes can effectively detect and monitor such activities. However, managing the storage demands for massive on-chain data certificates poses significant challenges. Existing compressed certificate storage strategies, such as the Merkle-Hash tree (MHT), incur significant on-chain storage costs because the auxiliary paths and the entire tree structure must be uploaded during verification, resulting in an O(n) storage overhead. Polynomial commitments offer a promising alternative by reducing storage costs to hundreds of bytes. However, current polynomial commitment methods lack effective support for incremental data updates, which are essential for real-time applications. In this paper, we propose a novel polynomial commitment-based dynamic integrity verification scheme that implements cumulative commitment updates for the first time. Our scheme includes a new data block insertion and deletion strategy that maintains the original order of data blocks within polynomial commitments. Theoretical security analysis confirms the robustness of the proposed scheme, while simulation results demonstrate that it meets the efficiency requirements for blockchain-based distributed data integrity verification mechanisms.

Thalamocortical mGlu8 Modulates Dorsal Thalamus Excitatory Transmission and Sensorimotor Activity.

Metabotropic glutamate receptor 8 (mGlu8) is a heterogeneously expressed and poorly understood glutamate receptor with potential pharmacological significance. The thalamic reticular nucleus (TRN) is a critical inhibitory modulator of the thalamocortical-corticothalamic (TC-CT) network and plays a crucial role in information processing throughout the brain, is implicated in a variety of psychiatric conditions, and is also a site of significant mGlu8 expression. Using both male and female mice, we determined via fluorescent in situ hybridization that parvalbumin-expressing cells in the TRN core and shell matrices (identified by spp1+ and ecel1+ expression, respectively), as well as the cortical layers involved in CT signaling, express grm8 mRNA. We then assayed the physiological and behavioral impacts of perturbing grm8 signaling in the TC circuit through conditional (adeno-associated virus-CRE mediated) and cell-type-specific constitutive deletion strategies. We show that constitutive parvalbumin grm8 knock-out (PV grm8 knock-out) mice exhibited (1) increased spontaneous excitatory drive onto dorsal thalamus relay cells and (2) impaired sensorimotor gating, measured via paired-pulse inhibition, but observed no differences in locomotion and thigmotaxis in repeated bouts of open field test (OFT). Conversely, we observed hyperlocomotive phenotypes and anxiolytic effects of AAV-mediated conditional knockdown of grm8 in the TRN (TRN grm8 knockdown) in repeated OFT. Our findings underscore a role for mGlu8 in regulating excitatory neurotransmission as well as anxiety-related locomotor behavior and sensorimotor gating, revealing potential therapeutic applications for various neuropsychiatric disorders and guiding future research endeavors into mGlu8 signaling and TRN function.

Enhanced production of trans-cinnamic acid in Photorhabdus luminescens with homolog expression and deletion strategies.

This study aimed to overproduce industrially relevant and safe bio-compound trans-cinnamic acid (tCA) from Photorhabdus luminescens with deletion strategies and homologous expression strategies that had not been applied before for tCA production. The overproduction of the industrially relevant compound tCA was successfully performed in P. luminescens by deleting stlB (TTO1ΔstlB) encoding a cinnamic acid CoA ligase in the isopropylstilbene pathway and the hcaE insertion (knockout) mutation (hcaE::cat) in the phenylpropionate catabolic pathway, responsible for tCA degradation. A double mutant of both stlB deletion and hcaE insertion mutation (TTO1DM ΔstlB-hcaE::cat) was also generated. These deletion strategies and the phenylalanine ammonium lyase-producing (PI-PAL from Photorhabdus luminescens) plasmid, pBAD30C, carrying stlA (homologous expression mutants) are utilized together in the same strain using different media, a variety of cultivation conditions, and efficient anion exchange resin (Amberlite IRA402) for enhanced tCA synthesis. At the end of the 120-h shake flask cultivation, the maximum tCA production was recorded as 1281mg l-1 in the TTO1pBAD30C mutant cultivated in TB medium, with the IRA402 resin keeping 793mg l-1 and the remaining 488mg l-1 found in the supernatant. TCA production was successfully achieved with homologous expression, coupled with deletion and insertion strategies. 1281mg l-1is the highest tCA concentration that achieved by bacterial tCA production in flask cultivation, according to our knowledge.

Disruption of the cell division protein ftsK gene changes elemental selenium generation, selenite tolerance, and cell morphology in Rahnella aquatilis HX2.

Some studies have indicated that the alterations in cellular morphology induced by selenite [Se(Ⅳ)] may be attributed to its inhibitory effects on cell division. However, whether the genes associated with cell division are implicated in Se(Ⅳ) metabolism remains unclear. The ftsK gene in Rahnella aquatilis HX2 was mutated with an in-frame deletion strategy. The ftsK mutation strongly reduced the tolerance to selenite [Se(Ⅳ)] and the production of red elemental selenium [Se(0)] in R. aquatilis HX2, and this effect could not be attributed solely to the inhibition of cell growth. Deleting the ftsK gene also resulted in a significant decrease in bacterial growth of R. aquatilis HX2 during both exponential and stationary phases. The deletion of ftsK inhibited cell division, resulting in the development of elongated filamentous cells. Furthermore, the loss-of-function of FtsK significantly impacted the expression of seven genes linked to cell division and Se(Ⅳ) metabolism by at least 2-fold, as unveiled by real-time quantitative PCR (RT-qPCR) under Se(Ⅳ) treatment. These findings suggest that FtsK is associated with Se(Ⅳ) tolerance and Se(0) generation and is a key player in coordinating bacterial growth and cell morphology in R. aquatilis HX2.

Hospital readmission prediction with hybrid‐sampling and self‐paced balance learning

SummaryHospital readmission prediction is defined as an evaluation task to model the historical medical data to predict whether patients will be readmitted after discharge. In the past few years, many feasible and effective prediction methods have been proposed, however, most of them neglect the imbalanced distribution of medical data, which causes great difficulties in modeling. Thus, we proposed a new hospital readmission prediction method, which utilizes hybrid‐sampling and self‐paced balance learning strategies to solve the class‐imbalance problem. To be specifically, we first employ an interference negative sample deletion strategy to reduce the probability of important majority class samples being deleted. Then, we design a hard positive sample generation strategy to generate more positive samples. Meanwhile, we also introduce a self‐paced balance factor during the oversampling process to improve the similarity between newly generated minority class samples and hard positive samples. Finally, we perform the experiments on six real‐world readmission datasets to indicate the superiority of the proposed method.

Coupled engineering strategy of CYB2 deletion and ACS1 overexpression improves cellulosic lactic acid production by Saccharomyces cerevisiae

Lactic acid plays a significant role in the food industry as a natural preservative and serves as a platform chemical for the production of biodegradable poly-lactic acid. While its sustainable production through fermentation using cellulosic biomass instead of traditional sugar and starch raw materials shows promise, there remains limited information available on this method. In this study, a xylose-fermenting and lactic acid-tolerant Saccharomyces cerevisiae strain (BK01) was engineered for improved cellulosic lactic acid production using the promising energy crop, kenaf. Specifically, CYB2 was deleted to inhibit lactic acid consumption (BK02), which was further engineered by ACS1 overexpression to remove the cytotoxic acetate derived from cellulosic biomass (BK03). The BK03 produced 3.25-fold more lactic acid from kenaf pulp hydrolysate than the parental strain (BK01). During pH-controlled fermentation, lactic acid production by BK03 reached a titer of 31 g/L and a productivity of 1.30 g/L-h, the highest value reported so far. This is one of the few studies on yeast-based lactic acid production from lignocellulose.

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model.

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

THE EFFECT OF MACROSTRUCTURE AND SUPERSTRUCTURE TEACHING ON SUMMARIZATION ACHIEVEMENT

Selecting and remembering the necessary information from rapidly increasing information requires summarization skills. Research on improving students' summarization skills has focused on deletion, generalization, and reconstruction strategies. However, direct teaching of these strategies does not yield successful results. For this reason, researchers have turned to teaching summarization based on understanding the text. Knowing the macrostructure and superstructure of the text can help understand the text and select the information to be included in the summary. The aim of this study is to determine the effect of macrostructure and superstructure teaching on summary writing achievement. The study was conducted in a one-group pretest-posttest design and lasted for 6 weeks. The study was conducted with 22 seventh grade students in a public secondary school. The data were collected with a total of 132 summary texts in which students summarized five stories. The summaries of texts were scored with the Text Summary Evaluation Rubric (TSER). As a result of the study, significant differences were obtained in summarization achievement in favor of the posttest. Based on this result, it is recommended that macrostructure and superstructure teaching be included in programs and course books. This study is limited to narrative texts. In future studies, whether the achievement in summarization narrative and informative texts differs and how long it takes for different age groups to develop their achievement in summarization of different types of texts can be examined based on text structure teaching. Keywords: Macrostructure teaching, superstructure teaching, summarization achievement, seventh grade students

Transformation of (allo)securinine to (allo)norsecurinine via a molecular editing strategy.

Securinega alkaloids have intrigued chemists since the isolation of securinine in 1956. This family of natural products comprises a securinane subfamily with a piperidine substructure and norsecurinane alkaloids featuring a pyrrolidine core. From a biosynthetic perspective, the piperidine moiety in securinane alkaloids derives from lysine, whereas the pyrrolidine moiety in norsecurinane natural products originates from ornithine, marking an early biogenetic divergence. Herein, we introduce a single-atom deletion strategy that enables the late-stage conversion of securinane to norsecurinane alkaloids. Notably, for the first time, this method enabled the transformation of piperidine-based (allo)securinine into pyrrolidine-based (allo)norsecurinine. Straightforward access to norsecurinine from securinine, which can be readily extracted from the plant Flueggea suffruticosa, abundant across the Korean peninsula, holds promise for synthetic studies of norsecurinine-based oligomeric securinega alkaloids.

To be forgotten or to be fair: unveiling fairness implications of machine unlearning methods

The right to be forgotten (RTBF) allows individuals to request the removal of personal information from online platforms. Researchers have proposed machine unlearning algorithms as a solution for erasing specific data from trained models to support RTBF. However, these methods modify how data are fed into the model and how training is done, which may subsequently compromise AI ethics from the fairness perspective. To help AI practitioners make responsible decisions when adopting these unlearning methods, we present the first study on machine unlearning methods to reveal their fairness implications. We designed and conducted experiments on two typical machine unlearning methods (SISA and AmnesiacML) along with a retraining method (ORTR) as baseline using three fairness datasets under three different deletion strategies. Results show that non-uniform data deletion with the variant of SISA leads to better fairness compared to ORTR and AmnesiacML, while initial training and uniform data deletion do not necessarily affect the fairness of all three methods. This research can help practitioners make informed decisions when implementing RTBF solutions that consider potential trade-offs on fairness.

3D multi-object tracking with boosting data association and improved trajectory management mechanism

In the multi-object tracking (MOT) algorithm based on the tracking-by-detection paradigm, matching accuracy between detection and prediction, robustness to occlusion and consistency between trajectory and ground truth are three emphasized issues. In this study, we propose a tracking-by-detection-based online 3D MOT framework, which produces 3D bounding boxes with identity, position, and shape in real time from point clouds provided in each sequential frame. Specifically, first, to increase the correct matching rate, we propose a 3D efficient affinity (3D-EAFF) that combines position correlation and geometric features to optimize data association between predictions and actual detections. Second, to reduce the identity switches caused by occlusion, a trajectory deletion strategy is proposed by using multiple distance thresholds to judge occlusion as well as setting a decay coefficient to eliminate prediction error accumulation. Third, to enhance the smoothness of the trajectory, a trajectory update strategy based on the position relationship between detection and prediction is proposed. By reallocating weights between measurements and prior estimates for Kalman filter updates, we aim to achieve a more optimal dynamic balance. The experimental results on two representative 3D MOT benchmarks NuScenes and KITTI show that our method effectively improves the tracking accuracy, and its robustness to occlusion also reaches competitive performance.

In pursuit of a minimal CHO genome: Establishment of large-scale genome deletions

Chinese hamster ovary (CHO) cells are the most commonly used mammalian cell line for the production of complex therapeutic glycoproteins. As CHO cells have evolved as part of a multicellular organism, they harbor many cellular functions irrelevant for their application as production hosts in industrial bioprocesses. Consequently, CHO cells have been the target for numerous genetic engineering efforts in the past, but a tailored host cell chassis holistically optimized for its specific task in a bioreactor is still missing. While the concept of genome reduction has already been successfully applied to bacterial production cells, attempts to create higher eukaryotic production hosts exhibiting reduced genomes have not been reported yet. Here, we present the establishment and application of a large-scale genome deletion strategy for targeted excision of large genomic regions in CHO cells. We demonstrate the feasibility of genome reduction in CHO cells using optimized CRISPR/Cas9 based experimental protocols targeting large non-essential genomic regions with high efficiency. Achieved genome deletions of non-essential genetic regions did not introduce negative effects on bioprocess relevant parameters, although we conducted the largest reported genomic excision of 864 kilobase pairs in CHO cells so far. The concept presented serves as a directive to accelerate the development of a significantly genome-reduced CHO host cell chassis paving the way for a next generation of CHO cell factories.

Impact of Missing Data on Correlation Coefficient Values: Deletion and Imputation Methods for Data Preparation

The correlation coefficient is one of the essential statistical techniques used to discover relationships among variables. Various techniques can quantify correlation, such as Pearson's, Spearman's, and Kendall's correlation coefficients, depending on the data type. As with any use of data, missing data will impact the availability of data, reducing it and potentially affecting the results. Furthermore, the removal of missing-value data from the study when using complete case analysis or available case analysis may result in selection biases. In this paper, we investigate the impact of missing data on the correlation coefficient value by calculating the difference between the correlation coefficient of the original complete dataset and that of a dataset with missing data. Two deletion strategies (Listwise and Pairwise) and three imputation strategies (Mean, k-Nearest Neighbors (k-NN), and Expectation-Maximization) were used to prepare the data before calculating the correlation coefficient. Unique correlation coefficient values were created by converting unique values to a one-dimensional array, and RMSE metrics were used to evaluate the experiments. Eight UCI and Kaggle datasets with different sizes and numbers of attributes were used in this study. The experiment results demonstrate that the Pairwise strategy and k-NN give good results on the correlation coefficient, respectively, when the missing rate is moderate or less. Pairwise uses all the available values and discards only the missing values of the related attribute, while k-NN fills the missing values with new values that produce correlation coefficient values close to the actual values.

A Knowledge Graph-Based Many-Objective Model for Explainable Social Recommendation

As an application area of social computing, social recommendation aims to exploit the richness of social relationships to improve recommendation accuracy. Current research mainly considers social information that can be directly observed, with little attention to indirect social relationships between users or the explainability of social recommendation results. To address this challenge, this article proposes a knowledge graph-based many-objective model for explainable social recommendation (KGMESR) by considering the explainability, accuracy, novelty, and content quality of social recommendation results. The model takes advantage of social behavior information to calculate user similarity and quantifies the explainability of social recommendation results using entity vectors and embedding vectors. To ensure model efficiency, a many-objective recommendation algorithm based on the partition deletion strategy is designed. It employs the association of individuals with the nearest reference vector to render the diversity of the population and then obtains the final solution by deleting poorly converged individuals in each partition. Experimental results show that many-objective optimization recommendation algorithm based on partition deletion strategy (MaOEA-PDS) allows for preferable recommendation results for users in real datasets. The explainability of the proposed model is demonstrated by two case studies.

RNA surveillance by ADAR1 is required for vascular endothelial resilience

Abstract Introduction Long dsRNAs are recognised as danger-associated molecular patterns by the cytosolic innate immune sensors inducing thus innate immune responses. RNA editing is a post-transcriptional modification induced by the binding of Adenosine Deaminases Acting on RNA (ADARs) to double-stranded RNA structures (dsRNAs). We have recently reported that ADAR1 is the main RNA editor in endothelial cells (ECs) but the role of ADAR1 in vascular homeostatic processes remains yet elusive. Methods Genetic deletion strategies were employed by crossing mice carrying a conditional (floxed) Adar1 , Ifh1 or Tlr3 allele with either a Tie2-Cre or with a tamoxifen-inducible VE-Cadherin-CreERT2 mouse line. Primary human and murine vascular EC culture assays, dsRNA metabolism studies, gene-silencing and expression techniques, immunohistochemistry and confocal microscopy were used to assess the EC-specific ADAR1 effects. Results EC-specific ADAR1 deletion resulted in prenatal embryonic lethality evidencing an absolute requirement of EC-ADAR1 in life. Inducible EC-ADAR1 ablation in adult mice elicited premature sudden death due to a widespread lung vascular leakage and pleural effusion, reflecting a compromised EC barrier function. Mechanistically, silencing of endothelial ADAR1 disrupted long-to-short dsRNA metabolism witnessed by the striking accumulation of cytoplasmic long dsRNAs. Subsequently, the cytoplasmic accumulation of endogenous long dsRNAs induced aberrant levels of interferon-β and activation of innate immune system. Finally, activation of the cytosolic dsRNA sensors inflicted the dissociation of β-catenin from VE-cadherin in EC junctions, while, co-silencing of the dsRNA sensor, MDA5, was sufficient to restore the integrity of the ADAR1-deficient endothelium. While double EC-specific ADAR1 and TLR3 did not fully rescue the lethality of the EC-ADAR1 animals, in vivo experiments using double EC-specific ADAR1 and MDA5 KO mice fully rescued the phenotype. Validation experiments using murine vascular ECs isolated from the mouse strains of our studies confirmed our mechanistic and phenotypic findings. Conclusion Endogenous suppression of double-stranded RNA-induced MDA5 autoinflammatory signaling by the RNA editor ADAR1 is essential for the maintenance of vascular integrity in adult mice.

Low Pressure Carbonylation of Benzyl Carbonates and Carbamates for Applications in13C Isotope Labeling and Catalytic CO2Reduction

AbstractHerein, we report a methodology to access isotopically labeled esters and amides from carbonates and carbamates employing an oxygen deletion strategy. This methodology utilizes a decarboxylative carbonylation approach for isotope labeling with near stoichiometric, ex situ generated12C, or13C carbon monoxide. This reaction is characterized by its broad scope, functional group tolerance, and high yields, which is showcased with the synthesis of structurally complex molecules. A complementary method that operates by the catalytic in situ generation of CO via the reduction of CO2liberated during decarboxylation has also been developed as a proof‐of‐concept approach that CO2‐derived compounds can be converted to CO‐containing frameworks. Mechanistic studies provide insight into the catalytic steps which highlight the impact of ligand choice to overcome challenges associated with low‐pressure carbonylation methodologies, along with rational for the development of future methodologies.

Low Pressure Carbonylation of Benzyl Carbonates and Carbamates for Applications in 13 C Isotope Labeling and Catalytic CO2 Reduction.

Herein, we report a methodology to access isotopically labeled esters and amides from carbonates and carbamates employing an oxygen deletion strategy. This methodology utilizes a decarboxylative carbonylation approach for isotope labeling with near stoichiometric, ex situ generated 12 C, or 13 C carbon monoxide. This reaction is characterized by its broad scope, functional group tolerance, and high yields, which is showcased with the synthesis of structurally complex molecules. A complementary method that operates by the catalytic in situ generation of CO via the reduction of CO2 liberated during decarboxylation has also been developed as a proof-of-concept approach that CO2 -derived compounds can be converted to CO-containing frameworks. Mechanistic studies provide insight into the catalytic steps which highlight the impact of ligand choice to overcome challenges associated with low-pressure carbonylation methodologies, along with rational for the development of future methodologies.

Effects of gender and degree of formality on the use of euphemistic strategies in Iraqi Arabic

Although euphemism has been studied in many Arabic dialects, it has not yet received due attention in Iraqi Arabic (IA). This study investigates the use of euphemistic strategies by IA speakers and the effect of gender and degree of formality on the use of these strategies. In order to achieve these objectives, a discourse completion test (DCT) was developed and distributed to 160 (80 males and 80 females) Iraqi university students. The data were analysed quantitively and qualitatively using strategies adopted from a number of previous frameworks. The findings show that the participants used a variety of euphemistic strategies, with the deletion strategy being the most frequently used when talking about the topic of death, the fuzzy words strategy for the topic of mental illness, and the implication strategy for the topic of obesity. The analysis also revealed that the degree of formality plays a key role in the use of euphemistic strategies in the topic of mental illness and that gender plays an effective role in the use of euphemistic strategies in all three topics.