Muhammad Umair

Climate change has become a global issue that requires collective efforts, and green finance policies are an important way to address this problem and promote enterprise development. This paper uses listed company data and city panel data to investigate the utility and mechanisms of the influence of the development of green finance in different cities on the Green Total Factor Productivity (GTFP) of enterprises. The conclusion was that green finance can improve enterprise GTFP, which remained significant after conducting a series of robustness tests. The mechanism analysis showed that green finance can improve enterprise GTFP by promoting energy conservation and emission reduction. The heterogeneity analysis indicated that green finance has a better effect on non-state-owned enterprises, large-scale enterprises, and enterprises with weak financing constraints. This paper enriches the literature that addresses the impact of green finance and the influential factors among GTFP.

Polydactyly, also known as hyperdactyly or hexadactyly is the most common hereditary limb anomaly characterized by extra fingers or toes, with various associated morphologic phenotypes as part of a syndrome (syndromic polydactyly) or may occur as a separate event (non-syndromic polydactyly). Broadly, the non-syndromic polydactyly has been classified into three types i.e; preaxial polydactyly (radial), central polydactyly (axial) and postaxial polydactyly (ulnar). Mostly inherited as an autosomal dominant entity with variable penetrance and caused by defects that occur in the anterior-posterior patterning of limb development. In human, to-date at least ten loci and six genes causing non-syndromic polydactyly have been identified, including the ZNF141, GLI3, MIPOL1, IQCE, PITX1, and the GLI1. In the present review, clinical, genetic and molecular characterization of the polydactyly types has been presented including the recent genes and loci identified for non-syndromic polydactyly. This review provides an overview of the complex genetic mechanism underlie polydactyly and might help in genetic counseling and quick molecular diagnosis.

The new coronavirus SARS-COV-2, which emerged in late 2019 from Wuhan city of China was regarded as causing agent of the COVID-19 pandemic. The primary protease which is also known by various synonymous i.e., main protease, 3-Chymotrypsin-like protease (3CL PRO ) has a vital role in the replication of the virus, which can be used as a potential drug target. The current study aimed to identify novel phytochemical therapeutics for 3CL PRO by machine learning-based virtual screening. A total of 4,000 phytochemicals were collected from deep literature surveys and various other sources. The 2D structures of these phytochemicals were retrieved from the PubChem database, and with the use of a molecular operating environment, 2D descriptors were calculated. Machine learning-based virtual screening was performed to predict the active phytochemicals against the SARS-CoV-2 3CL PRO . Random forest achieved 98% accuracy on the train and test set among the different machine learning algorithms. Random forest model was used to screen 4,000 phytochemicals which leads to the identification of 26 inhibitors against the 3CL PRO . These hits were then docked into the active site of 3CL PRO . Based on docking scores and protein-ligand interactions, MD simulations have been performed using 100 ns for the top 5 novel inhibitors, ivermectin, and the APO state of 3CL PRO . The post-dynamic analysis i.e,. Root means square deviation (RMSD), Root mean square fluctuation analysis (RMSF), and MM-GBSA analysis reveal that our newly identified phytochemicals form significant interactions in the binding pocket of 3CL PRO and form stable complexes, indicating that these phytochemicals could be used as potential antagonists for SARS-COV-2.