The field of personalized medicine is undergoing a transformative shift through the integration of multi-omics data, which mainly encompasses genomics, transcriptomics, proteomics, and metabolomics. This synergy allows for a comprehensive understanding of individual health by analyzing genetic, molecular, and biochemical profiles. The generation and integration of multi-omics data enable more precise and tailored therapeutic strategies, improving the efficacy of treatments and reducing adverse effects. However, several challenges hinder the full realization of personalized medicine. Key hurdles include the complexity of data integration across different omics layers, the need for advanced computational tools, and the high cost of comprehensive data generation. Additionally, issues related to data privacy, standardization, and the need for robust validation in diverse populations remain significant obstacles. Looking ahead, the future of personalized medicine promises advancements in technology and methodologies that will address these challenges. Emerging innovations in data analytics, machine learning, and high-throughput sequencing are expected to enhance the integration of multi-omics data, making personalized medicine more accessible and effective. Collaborative efforts among researchers, clinicians, and industry stakeholders are crucial to overcoming these hurdles and fully harnessing the potential of multi-omics for individualized healthcare.

Management and control of the COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus SARS-CoV-2 is critically dependent on quick and reliable identification of the virus in clinical specimens. Detection of viral RNA by a colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a simple, reliable and cost-effective assay, deployable in resource-limited settings (RLS). Our objective was to evaluate the intrinsic and extrinsic performances of RT-LAMP in RLS. This is a multicenter prospective observational study of diagnostic accuracy, conducted from October 2020 to February 2021 in four African Countries: Cameroon, Ethiopia, Kenya and Nigeria; and in Italy. We enroled 1657 individuals who were either COVID-19 suspect cases, or asymptomatic and presented for screening. RNA extracted from pharyngeal swabs was tested in parallel by a colorimetric RT-LAMP and by a standard real time polymerase chain reaction (RT-PCR). The sensitivity and specificity of index RT LAMP compared to standard RT-PCR on 1657 prospective specimens from infected individuals was determined. For a subset of 1292 specimens, which underwent exactly the same procedures in different countries, we obtained very high specificity (98%) and positive predictive value (PPV = 99%), while the sensitivity was 87%, with a negative predictive value NPV = 70%, Stratification of RT-PCR data showed superior sensitivity achieved with an RT-PCR cycle threshold (Ct) below 35 (97%), which decreased to 60% above 35. In this field trial, RT-LAMP appears to be a reliable assay, comparable to RT-PCR, particularly with medium-high viral loads (Ct < 35). Hence, RT-LAMP can be deployed in RLS for timely management and prevention of COVID-19, without compromising the quality of output. Bill & Melinda Gates Foundation [Grant No. INV-022,816].

Cancer remains a leading global health challenge, with conventional diagnostic and treatment methods often lacking precision and adaptability. This review explores transformative advancements that are reshaping oncology by addressing these limitations. It begins with an overview of cancer’s complexity, emphasizing the shortcomings of conventional tools such as imaging and chemotherapy, which frequently fail to deliver targeted care. The discussion then shifts to biomarkers, which represent a groundbreaking frontier in early detection, enabling the identification of unique biological signatures that signal the presence of cancer with heightened sensitivity. Building on this foundation, the review examines personalized molecular therapies, which target the specific genetic and molecular vulnerabilities of tumors. These therapies not only enhance treatment efficacy but also minimize adverse effects, offering patients improved outcomes and quality of life. By integrating biomarker-driven diagnostics with tailored therapeutic strategies, a new paradigm of precision oncology emerges, bridging the gap between early detection and effective intervention. Real-world case studies highlight both successes, such as significantly improved survival rates, and persistent challenges, including accessibility and cost barriers. Looking ahead, the review outlines pathways by which to scale these innovations, emphasizing the critical need for robust infrastructure, sustained research investment, and equitable healthcare policies. It concludes by envisioning a future where biomarkers and personalized therapies converge to redefine cancer care, offering earlier detection, precise interventions, and better patient experiences. This work underscores the urgency of adopting cutting-edge approaches to overcome cancer’s persistent threats, paving the way for a more effective and humane era in oncology.

Prevalence and Susceptibility Assay of Staphylococcus aureus Isolated from Bovine Mastitis in Dairy Farms of Jimma Town, South West Ethiopia

The status of bluetongue disease, vectors for transmission of the disease and the serotypes involved are not clearly known in Ethiopia. This sero-epidemiological study was conducted to determine the seroprevalence and associated risk factors of bluetongue in small ruminants of South Western Ethiopia. 422 serum samples were screened for the presence of bluetongue virus (BTV) specific antibodies using competitive enzyme-linked immunosorbent assay (c-ELISA) and 30.6% (129/422) (confidence interval CI 26.2–35%) of the sheep and goat serum samples were found positive. Multivariate analysis of several risk factors like age, sex, altitude, body condition and species of animals were studied and it was observed that species of animals, age and altitude had significant influence (P < 0.05) on seropositivity to BTV. Goats showed more seropositivity to bluetongue as compared to sheep [AOR = 2.4, 95% CI (1.5–3.9), P = 0.001], adult animals were more seropositive [AOR = 3.1, 95% CI (1.9–5.1), P = 0.001] than other age groups and animals at the lowland [AOR = 3.1, 95% CI (1.5–6.4), P = 0.002] showed more seropositivity to bluetongue than midland and high land. Sex and body condition of the animals had no statistically significant (P > 0.05) effect on seropositivity to bluetongue.