Abstract:The purpose of this study is to investigate the potential effects of corporate governance (CG) elements on corporate social responsibility (CSR) disclosure. The annual reports of companies for the year [2007][2008][2009][2010][2011] are examined to analyze the relationship between CG and CSR reporting. It considers the elements of CG such as board size, independent directors, foreign nationalities and women representation in the board, ownership concentration, institutional ownership, firm size and profitability. The multiple regression technique is used to measure the impact of CG elements on companies' CSR reporting. The results of the study demonstrate that overall CSR reporting by Pakistani companies are rather moderate however, the assortments of CSR items are really impressive. The study found positive and significant impact from board size, institutions ownership, ownership concentration and firm size on CSR reporting. The results also display contrary relationships between the women and foreign director's representation in the board and CSR reporting. This study suggests that organizations should audit their CG activities related to CSR in order to prove themselves good corporate citizens to all stakeholders.

Genome editing is a relevant, versatile, and preferred tool for crop improvement, as well as for functional genomics. In this review, we summarize the advances in gene-editing techniques, such as zinc-finger nucleases (ZFNs), transcription activator-like (TAL) effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR) associated with the Cas9 and Cpf1 proteins. These tools support great opportunities for the future development of plant science and rapid remodeling of crops. Furthermore, we discuss the brief history of each tool and provide their comparison and different applications. Among the various genome-editing tools, CRISPR has become the most popular; hence, it is discussed in the greatest detail. CRISPR has helped clarify the genomic structure and its role in plants: For example, the transcriptional control of Cas9 and Cpf1, genetic locus monitoring, the mechanism and control of promoter activity, and the alteration and detection of epigenetic behavior between single-nucleotide polymorphisms (SNPs) investigated based on genetic traits and related genome-wide studies. The present review describes how CRISPR/Cas9 systems can play a valuable role in the characterization of the genomic rearrangement and plant gene functions, as well as the improvement of the important traits of field crops with the greatest precision. In addition, the speed editing strategy of gene-family members was introduced to accelerate the applications of gene-editing systems to crop improvement. For this, the CRISPR technology has a valuable advantage that particularly holds the scientist’s mind, as it allows genome editing in multiple biological systems.

In the present study we determined the association of angiotensin converting enzyme (ACE) and plasminogen activator inhibitor-1 (PAI-1) gene polymorphisms with diabetic retinopathy (DR) and its sub-clinical classes in Pakistani type 2 diabetic patients. A total of 353 diabetic subjects including 160 DR and 193 diabetic non retinopathy (DNR) as well as 198 healthy controls were genotyped by allele specific polymerase chain reaction (PCR) for ACE Insertion/Deletion (ID) polymorphism, rs4646994 in intron 16 and PAI-1 4G/5G (deletion/insertion) polymorphism, rs1799768 in promoter region of the gene. To statistically assess the genotype-phenotype association, multivariate logistic regression analysis was applied to the genotype data of DR, DNR and control individuals as well as the subtypes of DR. The ACE genotype ID was found to be significantly associated with DR (p = 0.009, odds ratio (OR) 1.870 [95% confidence interval (CI) = 1.04–3.36]) and its sub-clinical class non-proliferative DR (NPDR) (p = 0.006, OR 2.250 [95% CI = 1.098–4.620]), while PAI polymorphism did not show any association with DR in the current cohort. In conclusion in Pakistani population the ACE ID polymorphism was observed to be significantly associated with DR and NPDR, but not with the severe form of the disease i.e. proliferative DR (PDR).

White blood cells (WBCs) are a portion of the immune system which fights against germs. Leukemia is the most common blood cancer which may lead to death. It occurs due to the production of a large number of immature WBCs in the bone marrow that destroy healthy cells. To overcome the severity of this disease, it is necessary to diagnose the shapes of immature cells at an early stage that ultimately reduces the modality rate of the patients. Recently different types of segmentation and classification methods are presented based upon deep-learning (DL) models but still have some limitations. This research aims to propose a modified DL approach for the accurate segmentation of leukocytes and their classification. The proposed technique includes two core steps: preprocessing-based classification and segmentation. In preprocessing, synthetic images are generated using a generative adversarial network (GAN) and normalized by color transformation. The optimal deep features are extracted from each blood smear image using pretrained deep models i.e., DarkNet-53 and ShuffleNet. More informative features are selected by principal component analysis (PCA) and fused serially for classification. The morphological operations based on color thresholding with the deep semantic method are utilized for leukemia segmentation of classified cells. The classification accuracy achieved with ALL-IDB and LISC dataset is 100% and 99.70% for the classification of leukocytes i.e., blast, no blast, basophils, neutrophils, eosinophils, lymphocytes, and monocytes, respectively. Whereas semantic segmentation achieved 99.10% and 98.60% for average and global accuracy, respectively. The proposed method achieved outstanding outcomes as compared to the latest existing research works.

No abstract