UnizikSpace Collection: Scholarly Works

Heavy metal application of response surface optimized‑lipopeptide biosurfactant produced by Pseudomonas aeruginosa strain CGA‑02 in low‑cost substrate

2025-08-25T13:29:37Z

Title: Heavy metal application of response surface optimized‑lipopeptide biosurfactant produced by Pseudomonas aeruginosa strain CGA‑02 in low‑cost substrate Authors: Chikodili Gladys Anaukwu1, Chikodili Gladys; Ekwealor, Chito Clare; Anakwenze, Vivian Nonyelum; Orji, Chinedu Christian; Ogbukagu, Chioma Maureen; Anyaoha, Victoria Ihedinachi; Isiaka, Amarachukwu Bernaldine; Green, Stefan Joshua; Ekwealor, Ikechukwu Amechi Abstract: Cost-efective methods of biosurfactant production with minimal environmental impact are needed as global demand continues to increase. This study evaluated lipopeptide biosurfactant production in a Pseudomonas aeruginosa strain CGA-02 using a low-cost carbon substrate. The structural properties of the biosurfactant and applicability of the biosurfactant in heavy metal removal were evaluated. Response surface methodology (RSM) involving central composite design (CCD) was used to optimize process parameters to maximize biosurfactant production. The study identifed sugar cane molasses and sodium nitrate as carbon and nitrogen sources of choice for bacterial growth and biosurfactant production, with a relatively 2.64-fold increase in biosurfactant yield under optimized conditions. Analysis of the biosurfactant measured a surface tension reduction of water from 72.2±0.26 to 30.5±0.2 mN/m at 40 mg/L critical micelle concentration. GC–MS and FTIR analysis revealed structural properties of the lipopeptide biosurfactant, with fatty acid components predominantly 9-octadecenoic acid (oleic acid), n-hexadecanoic acid, cyclotetrasiloxane and trimyristin, and infrared peaks belonging to amine, carboxyl, nitrile, alkanol, ether and carbonyl groups. Capture of heavy metals using the biosurfactant was evaluated in soil microcosms. Removal rates of 80.47, 100, 77.57, 100, and 97.57% were recorded for As, Pb, Hg, Cd and Cr respectively after 12 weeks of incubation. There was no signifcant diference (p<0.05) in the removal efciency of the biosurfactant and an analogous chemical surfactant, sodium dodecyl sulphate. First and second-order kinetic models described heavy metal removal rates by the biosurfactant. We demonstrate the production of a useful biosurfactant using low-cost waste carbon. Description: scholarly works

Exploring the role of gut microbiota in human health

2025-08-25T13:12:44Z

Title: Exploring the role of gut microbiota in human health Authors: Isiaka, Amarachukwu Bernaldine; Anakwenze, Vivian Nonyelum; Uzoka, Ugonna Henry; Ilodinso, Chiamaka Rosemary; Oso, Mercy Oluwayomi; Ekwealor, Chito Clare; Anaukwu, Chikodili Gladys Abstract: The study explores the intricate relationship between the human gut microbiota and health. It analyzes the gut microbiota’s roles in digestion, metabolism, immune responses, and overall well-being. The review discusses the composition and diversity of gut microbial communities, emphasizing their symbiotic relationship with the host. It also examines how gut dysbiosis, or microbial imbalance, relates to health conditions like inflammatory bowel diseases and metabolic disorders. The review highlights research methodologies like metagenomics and metabolomics that deepen our understanding of gut microbiota function. It also explores external factors, such as diet and antibiotic use, in shaping the gut microbiome. The review discusses potential therapeutic interventions like probiotics and fecal microbiota transplantation, suggesting a future for personalized medicine. By synthesizing existing knowledge, the review aims to advance understanding of the gut microbiota’s role in health and suggest future research and interventions. Description: scholarly works

Harnessing Artificial Intelligence for Early Detection and Management of Infectious Disease Outbreaks

2025-08-25T13:05:46Z

Title: Harnessing Artificial Intelligence for Early Detection and Management of Infectious Disease Outbreaks Authors: Isiaka, Amarachukwu Bernaldine; Anakwenze, Vivian Nonyelum; Ilodinso, Chiamaka Rosemary; Anaukwu, Chikodili Gladys; Ezeokoli, Chukwuebuka Mary-Vin; Noi, Samuel Mensah; Agboola, Gazali Oluwasegun; Adonu, Richard Mensah Abstract: Infectious diseases pose ongoing threats to global public health, demanding advanced detection methods for effective outbreak management. This study explores integrating artificial intelligence (AI) for early detection and management. AI algorithms analyze diverse datasets, including electronic health records and social media, to identify potential outbreaks. Machine learning models predict disease spread and severity, aiding proactive resource allocation. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses AI's role in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study also evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. Ethical considerations are crucial, emphasizing collaboration between public health agencies, healthcare providers, and technology experts. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. This paper advocates for AI integration to enhance infectious disease surveillance, offering a proactive response to safeguard public health. Description: scholarly works

Microbiology in Nigeria: Navigating Challenges, Exploring Prospects

2025-08-14T13:59:53Z

Title: Microbiology in Nigeria: Navigating Challenges, Exploring Prospects Authors: Anakwenze, Vivian Nonyelum; Isiaka, Amarachukwu Bernaldine; Okoli, Uzoma Odinakachi; Ekwealor, Chito Clare; Ezemba, Chinyere Constance; Anaukwu, Chikodili Gladys; Osilo, Chidimma Linda; Ekwealor, Ikechukwu Amechi Abstract: Microbiology, as a scientific discipline, plays a pivotal role in unraveling the mysteries of the microscopic world, shaping our understanding of life at its most fundamental level. In the context of Nigeria, a nation with a rich tapestry of diverse ecosystems and health challenges, microbiology has been gaining increasing importance over the years. As Nigeria strides towards technological and scientific progress, microbiology plays a pivotal role in addressing pressing issues such as infectious diseases, food safety, and environmental sustainability. However, the journey is not without hurdles. Infrastructure limitations, funding constraints, and educational gaps present formidable challenges to the growth and development of microbiological research and applications in the country. This discourse delves into the intricacies of microbiology in Nigeria, examining the barriers that impede its progress and the boundless potential it carries for advancements in academia, healthcare, industry, agriculture, and environmental sustainability. From the laboratory to the field, microbiology in Nigeria stands at the crossroads of obstacles and opportunities, presenting a narrative of scientific resilience and the quest for innovative solutions to societal challenges. Description: Scholarly works