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Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. These inhibitors exhibit high toxicity, less efficacy, and specificity against RET. The development of drug-resistant mutations in RET protein further deteriorates this situation. Hence, in the present study, we aimed to design novel drug-like compounds using a fragment-based drug designing strategy to overcome these issues. About 18 known inhibitors from diverse chemical classes were fragmented and bred to form novel compounds against RET proteins. The inhibitory activity of the resultant 115 hybrid molecules was evaluated using molecular docking and RF-Score analysis. The binding free energy and chemical reactivity of the compounds were computed using MM-GBSA and density functional theory analysis, respectively. The results from our study revealed that the developed hybrid molecules except for LF21 and LF27 showed higher reactivity and stability than Pralsetinib. Ultimately, the process resulted in three hybrid molecules namely LF1, LF2, and LF88 having potent inhibitory activity against RET proteins. The scrutinized molecules were then subjected to molecular dynamics simulation for 200 ns and MM-PBSA analysis to eliminate a false positive design. The results from our analysis hypothesized that the designed compounds exhibited significant inhibitory activity against multiple RET variants. Thus, these could be considered as potential leads for further experimental studies.

In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the in vivo experiments and the expenses, we intended to develop novel machine learning-based tools to predict the toxicity of the compounds with high precision. A total of 372 compounds with known toxicity information were retrieved from the PubChem Bioassay database and literature. The fingerprints and descriptors of the compounds were generated using PaDEL and ChemSAR, respectively, for the analysis. The performance of the models was assessed using the three tires of evaluation strategies such as fivefold, tenfold, and validation by external dataset. Further, structural alerts causing genotoxicity of the compounds were identified using SARpy method. Of note, fingerprint-based random forest model built in our analysis is able to demonstrate the highest accuracy of about 0.97 during tenfold cross-validation. In essence, our study highlights that structural alerts such as chlorocyclohexane and trimethylamine are likely to be the leading cause of toxicity in humans. Indeed, we believe that random forest model generated in this study is appropriate for reduction of test animals and should be considered in the future for the good practice of animal welfare.

Rearranged during transfection (RET) is a tyrosine kinase oncogenic receptor, activated in several cancers including non-small-cell lung cancer (NSCLC). Multiple kinase inhibitors vandetanib and cabozantinib are commonly used in the treatment of RET-positive NSCLC. However, specificity, toxicity, and reduced efficacy limit the usage of multiple kinase inhibitors in targeting RET protein. Thus, in the present investigation, we aimed to figure out novel and potent candidates for the inhibition of RET protein using combined in silico and in vitro strategies. In the present study, screening of 11,808 compounds from the DrugBank repository was accomplished by different hypotheses such as pharmacophore, e-pharmacophore, and receptor cavity-based models in the initial stage. The results from the different hypotheses were then integrated to eliminate the false positive prediction. The inhibitory activities of the screened compounds were tested by the glide docking algorithm. Moreover, RF score, Tanimoto coefficient, prime-MM/GBSA, and density functional theory calculations were utilized to re-score the binding free energy of the docked complexes with high precision. This procedure resulted in three lead molecules, namely DB07194, DB03496, and DB11982, against the RET protein. The screened lead molecules together with reference compounds were then subjected to a long molecular dynamics simulation with a 200 ns time duration to validate the inhibitory activity. Further analysis of compounds using MM-PBSA and mutation studies resulted in the identification of potent compound DB07194. In essence, a cell viability assay with RET-specific lung cancer cell line LC-2/ad was also carried out to confirm the in vitro biological activity of the resultant compound, DB07194. Indeed, the results from our study conclude that DB07194 can be effectively translated for this new therapeutic purpose, in contrast to the properties for which it was originally designed and synthesized.

Connected and automated vehicles (CAV) are increasingly recognized as a critical component of intelligent transportation systems (ITS), contributing to advances in transportation safety and mobility. However, the implementation of CAV in a real-world environment comes with various threats, and cybersecurity is among the most vulnerable. As the technology becomes more advanced and complex, it is essential to develop a comprehensive cybersecurity framework that can address these concerns. This research proposes a novel framework based on complexity theory and employs the fuzzy set qualitative comparative analysis (fsQCA) technique to identify combinations of security attacks that lead to achieving cybersecurity in CAV. Compared to structural equation modelling (SEM), the fsQCA method offers the advantage of demonstrating all possible ways to achieve the outcome. The study’s findings suggest that in-vehicle networks and data storage security are the most crucial factors in ensuring the cybersecurity of CAV. The results can be useful for automotive designers in reducing the potential for attacks while developing secure networks.

The RV144 Phase III clinical trial with ALVAC-HIV prime and AIDSVAX B/E subtypes CRF01_AE (A244) and B (MN) gp120 boost vaccine regime in Thailand provided a foundation for the future development of improved vaccine strategies that may afford protection against the human immunodeficiency virus type 1 (HIV-1). Results from this trial showed that immune responses directed against specific regions V1V2 of the viral envelope (Env) glycoprotein gp120 of HIV-1, were inversely correlated to the risk of HIV-1 infection. Due to the low production of gp120 proteins in CHO cells (2-20 mg/L), cleavage sites in V1V2 loops (A244) and V3 loop (MN) causing heterogeneous antigen products, it was an urgent need to generate CHO cells harboring A244 gp120 with high production yields and an additional, homogenous and uncleaved subtype B gp120 protein to replace MN used in RV144 for the future clinical trials. Here we describe the generation of Chinese Hamster Ovary (CHO) cell lines stably expressing vaccine HIV-1 Env antigens for these purposes: one expressing an HIV-1 subtype CRF01_AE A244 Env gp120 protein (A244.AE) and one expressing an HIV-1 subtype B 6240 Env gp120 protein (6240.B) suitable for possible future manufacturing of Phase I clinical trial materials with cell culture expression levels of over 100 mg/L. The antigenic profiles of the molecules were elucidated by comprehensive approaches including analysis with a panel of well-characterized monoclonal antibodies recognizing critical epitopes using Biacore and ELISA, and glycosylation analysis by mass spectrometry, which confirmed previously identified glycosylation sites and revealed unknown sites of O-linked and N-linked glycosylations at non-consensus motifs. Overall, the vaccines given with MF59 adjuvant induced higher and more rapid antibody (Ab) responses as well as higher Ab avidity than groups given with aluminum hydroxide. Also, bivalent proteins (A244.AE and 6240.B) formulated with MF59 elicited distinct V2-specific Abs to the epitope previously shown to correlate with decreased risk of HIV-1 infection in the RV144 trial. All together, these results provide critical information allowing the consideration of these candidate gp120 proteins for future clinical evaluations in combination with a potent adjuvant.

Non-small cell lung cancer (NSCLC) remains the leading cause of mortality and morbidity worldwide accounting about 85% of total lung cancer cases. The receptor REarranged during Transfection (RET) plays an important role by ligand independent activation of kinase domain resulting in carcinogenesis. Presently, the treatment for RET driven NSCLC is limited to multiple kinase inhibitors. This situation necessitates the discovery of novel and potent RET specific inhibitors. Thus, we employed high throughput screening strategy to repurpose FDA approved compounds from DrugBank comprising of 2509 molecules. It is worth noting that the initial screening is accomplished with the aid of in-house machine learning model built using IC 50 values corresponding to 2854 compounds obtained from BindingDB repository. A total of 497 compounds (19%) were predicted as actives by our generated model. Subsequent in silico validation process such as molecular docking, MMGBSA and density function theory analysis resulted in identification of two lead compounds named DB09313 and DB00471. The simulation study highlights the potency of DB00471 (Montelukast) as potential RET inhibitor among the investigated compounds. In the end, the half-minimal inhibitory activity of montelukast was also predicted against RET protein expressing LC-2/ad cell lines demonstrated significant anticancer activity. Collective analysis from our study highlights that montelukast could be a promising candidate for the management of RET specific NSCLC.

To compare refractive outcomes, visual acuities, and satisfaction of patients between those treated with laser-assisted in situ keratomileusis (LASIK) using a Hansatome microkeratome (HM) and femto-assisted laser (FAL). This was a retrospective analysis of 1,366 eyes in 687 patients who underwent LASIK with an HM (n=1,137) and an FAL (n=229) at the two centers of Hashmanis Hospital, Karachi, Pakistan. Refractive outcomes, including sphere, cylinder, and spherical equivalent in diopters (D), and visual acuities were assessed both preoperatively and at 1 month follow-up. Patient satisfaction was gauged by contacting the patient at the time of chart review. The postoperative median sphere, cylinder, and spherical equivalent values for those treated with FAL were 0.3±0.7 (-5.5-1.8), -0.5±0.6 (-5.0-1.0), and 0.0±0.7 (-6.0-1.6), respectively. For the HM arm, they were 0.0±1.28 (-10.8-6.8), -0.5±0.5 (-4.5-1.5), and -0.3±1.3 (-11.6-6.8), respectively. All preoperative values were statistically insignificant between the groups, while postoperative values were significant with -values <0.001. Predictability and efficacy index was higher for the FAL (92.1%, 1.00) than the HM group (82.2%, 0.84). Similarly, patient satisfaction was slightly higher for those treated with FAL (93.3%) than HM (91.4%). Our large retrospective analysis of eyes that have undergone LASIK using HM and FAL shows superior refractive outcomes in the latter, with special regard to procedural efficacy and predictability.

Purpose To compare visual outcomes and satisfaction among patients of photorefractive keratectomy (PRK; Wavelight EX 500, Alcon, Ft Worth, TX, USA) and femtosecond laser-assisted in situ keratomileusis (FAL; Wavelight FS 200 laser and Wavelight EX 500, Alcon, Ft Worth, TX, USA). Methods We performed a retrospective study of 409 eyes in 207 patients that underwent either PRK (n=90) or FAL (n=117) at the two centers of Hashmanis Hospital, Karachi, Pakistan. The included refractive outcomes were sphere diopters (D), cylinder D, and spherical equivalent D. Additionally, visual acuities were included. All of these were assessed preoperatively and at the one-month postoperative check-up. Patient satisfaction was gauged at the time of chart review by contacting the patient. Results When looking at the postoperative outcomes, we found all values to be statistically significant (p<0.001) with superior outcomes in the FAL cohort. Additionally, 90% and 15% of eyes achieved a postoperative uncorrected visual acuity (UCVA) of 20/20 in FAL and PRK, respectively. Furthermore, the efficacy indexes of the FAL and PRK arms were 1.00 and 0.82, respectively. The predictability of the procedures were 92.1% and 64.9%, respectively. Lastly, 93.3% of patients were satisfied with FAL and 95.7% with PRK. Conclusion Our study shows superior visual outcomes in patients undergoing FAL. However, we found a higher satisfaction rate in those that underwent PRK, perhaps due to the higher cost of FAL.

Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-III respectively. Topological analysis of the protein–protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70 months were identified for hub genes during the Kaplan–Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.