Evaluating the Efficacy and Security of Steganography Techniques in Cloud Computing

Cloud computing has revolutionized the handling, access, and storage of data. However, ensuring the security and privacy of data within cloud environments remains a significant challenge. This research offers a comprehensive examination aimed at developing a dependable steganographic technique, evaluating its effectiveness, determining its impact on cloud computing performance, and exploring potential vulnerabilities along with solutions. The primary objective is to assess how steganography influences the performance of cloud computing systems. Through performance evaluations and benchmarks, the study investigates the effects of steganography on system performance. It utilizes various file formats and sizes to simulate real-world conditions. The research also identifies potential weaknesses of the proposed steganographic method and explores strategies to mitigate these vulnerabilities. An analysis of security vulnerabilities, including potential attacks and detection techniques, leads to the formulation of effective countermeasures. The findings of this research contribute to the advancement of steganography-based data security in cloud environments. By highlighting the strengths, weaknesses, and areas for improvement of the proposed steganographic approach, the study offers insights into its impact on cloud computing systems and supports the development of robust security measures

Small RNA combination therapy for lung cancer

MicroRNAs (miRNAs) and siRNAs have enormous potential as cancer therapeutics, but their effective delivery to most solid tumors has been difficult. Here, we show that a new lung-targeting nanoparticle is capable of delivering miRNA mimics and siRNAs to lung adenocarcinoma cells in vitro and to tumors in a genetically engineered mouse model of lung cancer based on activation of oncogenic Kirsten rat sarcoma viral oncogene homolog (Kras) and loss of p53 function. Therapeutic delivery of miR-34a, a p53-regulated tumor suppressor miRNA, restored miR-34a levels in lung tumors, specifically down-regulated miR-34a target genes, and slowed tumor growth. The delivery of siRNAs targeting Kras reduced Kras gene expression and MAPK signaling, increased apoptosis, and inhibited tumor growth. The combination of miR-34a and siRNA targeting Kras improved therapeutic responses over those observed with either small RNA alone, leading to tumor regression. Furthermore, nanoparticle-mediated small RNA delivery plus conventional, cisplatin-based chemotherapy prolonged survival in this model compared with chemotherapy alone. These findings demonstrate that RNA combination therapy is possible in an autochthonous model of lung cancer and provide preclinical support for the use of small RNA therapies in patients who have cancer.National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)National Institutes of Health (U.S.) (Grant 2-PO1-CA42063)National Institutes of Health (U.S.) (Grant RO1-EB000244)National Institutes of Health (U.S.) (Grant RO1-CA115527)National Institutes of Health (U.S.) (Grant RO1-CA132091)National Cancer Institute (U.S.) (1K99CA169512)American Association for Cancer Research (Fellowship)Leukemia & Lymphoma Society of America (Fellowship)National Science Foundation (U.S.). Graduate Research Fellowship ProgramMassachusetts Institute of Technology. Presidential FellowshipUnited States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship

In vivo endothelial siRNA delivery using polymeric nanoparticles with low molecular weight

Dysfunctional endothelium contributes to more diseases than any other tissue in the body. Small interfering RNAs (siRNAs) can help in the study and treatment of endothelial cells in vivo by durably silencing multiple genes simultaneously, but efficient siRNA delivery has so far remained challenging. Here, we show that polymeric nanoparticles made of low-molecular-weight polyamines and lipids can deliver siRNA to endothelial cells with high efficiency, thereby facilitating the simultaneous silencing of multiple endothelial genes in vivo. Unlike lipid or lipid-like nanoparticles, this formulation does not significantly reduce gene expression in hepatocytes or immune cells even at the dosage necessary for endothelial gene silencing. These nanoparticles mediate the most durable non-liver silencing reported so far and facilitate the delivery of siRNAs that modify endothelial function in mouse models of vascular permeability, emphysema, primary tumour growth and metastasis.American Society for Engineering Education. National Defense Science and Engineering Graduate FellowshipNational Science Foundation (U.S.)Massachusetts Institute of Technology. Presidential Fellowshi

Ionizable Lipid Nanoparticles for Therapeutic Base Editing of Congenital Brain Disease

Delivery of mRNA-based therapeutics to the perinatal brain holds great potential in treating congenital brain diseases. However, nonviral delivery platforms that facilitate nucleic acid delivery in this environment have yet to be rigorously studied. Here, we screen a diverse library of ionizable lipid nanoparticles (LNPs) via intracerebroventricular (ICV) injection in both fetal and neonatal mice and identify an LNP formulation with greater functional mRNA delivery in the perinatal brain than an FDA-approved industry standard LNP. Following in vitro optimization of the top-performing LNP (C3 LNP) for codelivery of an adenine base editing platform, we improve the biochemical phenotype of a lysosomal storage disease in the neonatal mouse brain, exhibit proof-of-principle mRNA brain transfection in vivo in a fetal nonhuman primate model, and demonstrate the translational potential of C3 LNPs ex vivo in human patient-derived brain tissues. These LNPs may provide a clinically translatable platform for in utero and postnatal mRNA therapies including gene editing in the brain