Hepatitis E virus (HEV) is recognized as one of the leading causes of acute viral hepatitis (AVH) in developing countries, where it is primarily transmitted through the consumption of contaminated food and water. Although often self-limiting, HEV infection poses a significant public health concern, particularly among pregnant women, due to its potential complications. The present study aimed to determine the seroprevalence of HEV infection in asymptomatic antenatal women attending a tertiary care center in South Punjab, Pakistan.

A total of 100 asymptomatic pregnant women were screened for anti-HEV antibodies (IgM and IgG) using an ELISA kit (DIA PRO, Italy). The overall seropositivity rate was found to be 12%, indicating prior exposure to HEV infection in this cohort. Specifically, IgG antibodies were detected in 6% of women and IgM antibodies in 5%, while two women showed evidence of both IgG and IgM positivity, suggestive of recent or ongoing infection. Notably, the majority of participants reported reliance on untreated water sources irrespective of educational background, highlighting environmental risk factors.

Although HEV is generally self-limiting, these findings underscore the importance of routine serological screening in antenatal populations to prevent adverse pregnancy outcomes. In addition, increased community awareness regarding transmission routes and preventive measures is essential. Given the scarcity of regional data, this study emphasizes the need for larger-scale epidemiological investigations to better understand the burden of HEV in South Punjab, Pakistan.

Keywords: Hepatitis E Virus, Antenatal Women, Seroprevalence, Immunoglobulins, South Punjab

Antibody–drug conjugates (ADCs) represent a novel and rapidly evolving class of targeted therapeutics that combine the high specificity of monoclonal antibodies (mAbs) with the potent cytotoxic effects of small-molecule drugs. These engineered molecules are designed to selectively deliver cytotoxic agents to specific cells, thereby reducing off-target toxicity and enhancing therapeutic efficacy. In oncology, ADCs have already demonstrated significant clinical success, particularly in the treatment of hematological malignancies and solid tumors. Agents such as trastuzumab emtansine and brentuximab vedotin exemplify how ADCs can effectively target cancer cells while limiting damage to healthy tissues. Over the past decade, the development of new linkers, payloads, and antibody engineering technologies has further refined the safety and effectiveness of ADCs, leading to an expanded pipeline of approved and investigational compounds. Following their success in oncology, interest has grown in repurposing ADCs for the treatment of non-malignant diseases, including autoimmune disorders. These conditions are characterised by inappropriate immune responses in which autoreactive cells and inflammatory mediators attack host tissues. ADCs offer a promising solution by enabling the selective depletion or modulation of these pathogenic immune cell subsets without broadly suppressing the entire immune system. Preclinical and early clinical studies have shown encouraging results. For instance, ADCs targeting CD19 or CD22 are being explored for systemic lupus erythematosus and other B-cell-driven diseases, while anti-CD3 ADCs have shown potential in type 1 diabetes. As knowledge of disease-specific immune targets increases, ADCs may provide a new avenue for achieving durable remission in autoimmune diseases with improved safety profiles compared to conventional immunosuppressants. This presentation comprehensively explores the evolving landscape of ADCs in autoimmune therapeutics.

Salmonella infections in poultry represent a significant public health and economic burden, particularly in regions where poultry serves as a major source of animal protein. Traditional control methods often rely on antibiotics, which contribute to antimicrobial resistance and raise consumer health concerns. This study developed a novel, sustainable strategy by integrating indigenous plant-based bacterial attenuation with immunotherapy using IgY antibodies. Specifically, garlic (Allium sativum) and onion (Allium cepa) extracts were employed to attenuate wild-type Salmonella serovars. These plant-derived agents exhibited strong antimicrobial properties, effectively inhibiting bacterial growth in vitro. The attenuated strains were then used to vaccinate chickens, which led to the induction of high levels of anti-Salmonella IgY antibodies, as confirmed by an enzyme-linked immunosorbent assay (ELISA). Functional assays revealed that the harvested IgY antibodies possessed robust agglutination activity, highlighting their potential role in passive immunisation strategies. Importantly, the vaccine was found to be both safe and immunogenic, with no adverse effects observed in the immunised birds. This dual approach—combining natural antimicrobial agents with immune-based protection—offers a cost-effective and environmentally friendly alternative to conventional methods. It holds particular promise for improving poultry health and food safety in the Caribbean, where locally available resources and affordable interventions are crucial. This strategy may also be applicable to broader global contexts, especially in low-resource agricultural settings.

In the last decade, immuno-oncology has revolutionized cancer therapy by harnessing the body's immune system to target and eliminate tumor cells, offering durable responses particularly in malignancies previously considered treatment-resistant. This approach exploits immune checkpoints, monoclonal antibodies, Chimeric Antigen Receptor (CAR) T-cells, and innovative cancer vaccines to activate, promote, and enhance immune responses specific to tumor-associated antigens. However, the complexity of tumor–immune interactions necessitates advanced tumor imaging techniques to accurately diagnose, monitor, and tailor effective immunotherapy techniques. Tumor imaging plays a pivotal role in visualizing immune cell infiltration, tracking immune responses in real-time, and identifying immune-related adverse events. Recent innovations such as hybrid Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Positron Emission Tomography (PET) (PET/CT and MRI) combined with novel tracers—like radiolabeled antibodies targeting Programmed Death-Ligand 1 PD-L1—allow precise quantification of immune activation within the tumor microenvironment. These modalities facilitate early assessment of therapeutic efficacy, guiding personalized treatment adjustments. Furthermore, multimodal imaging approaches integrating molecular and anatomical data improve the delineation of tumor boundaries, detect metastases, and evaluate emerging resistance mechanisms. As immuno-oncology moves toward personalized medicine, imaging biomarkers will be essential in stratifying patients most likely to benefit from immune-based therapies, predicting outcomes, and minimizing toxicity. Continued research in tumor imaging will enhance our understanding of immune dynamics, ultimately improving treatment precision and patient survival in cancer care. The main aim of this was to advance and develop the in-depth understanding and application of innovative tumor imaging techniques that accurately visualize and quantify immune responses within the tumor microenvironment. By enabling personalized immunotherapy strategies, improving personalized treatment and monitoring will significantly enhance patient therapeutic outcomes, as a result of appropriate treatment corresponding to effective and modern cancer care.

Novel and developed computational approaches in the field of antibody engineering have revolutionized and leveraged advanced algorithms through machine learning and detailed structural modeling in order to deeply facilitate the de novo design of new, effective therapeutic agents based on antibodies, affinity maturation, and stability optimization, significantly enhancing and accelerating the drug development processes. The main purpose of this paper is to clearly illustrate how advanced computational antibody design techniques, such as de novo engineering, affinity maturation, and personalized modeling, can deeply affect modern and precision therapeutics by enabling the rapid development of highly specific and potent monoclonal antibodies tailored to specific critical diseases. We observed the rapid development of highly specific and potent monoclonal antibodies tailored for some specific critical diseases—particularly cancers; for example, Human Epidermal Growth Factor Receptor 2 (HER2) or Receptor Tyrosine-Protein Kinase erbB-2- positive breast cancer or colorectal cancer. For autoimmune disorders such as Rheumatoid Arthritis (RA), Antikeratin, anticitrullinated peptides, anti-RA33, anti-Sa, and anti-p68 autoantibodies have been shown to have >90% specificity for RA. Regarding infectious diseases, the immunoglobulins lg M, lg A, and lg G are the key players in the response and the fight against COVID-19. The ultimate essential goal consists is to improve therapeutic efficacy, reduce off-target effects, and facilitate specific personalized treatment strategies that effectively address individual patients' molecular profiles. Machine learning algorithms like DeepMind’s AlphaFold have dramatically improved the accuracy of antibody–antigen structure prediction, facilitating the rapid identification of high-affinity binders. In one instance, a computational redesign of an anti-PD-1 (Immune checkpoint inhibitor) antibody enhanced its binding affinity and stability, leading to a more potent immune checkpoint inhibitor for cancer therapy. Moreover, the de novo design of bispecific antibodies has enabled simultaneous targeting of multiple tumor antigens, such as Cluster of Differentiation 3 (CD3) and Epidermal Growth Factor Receptor (EGFR), boosting immune activation in resistant cancers.