CURRENT ISSUE

ABSTRACT: Spatial tumour heterogeneity, which denotes the changes in cellular and molecular attributes across distinct locations within a tumour, significantly influences cancer diagnosis and treatment resistance. The heterogeneity of tumour cells inside a singular mass facilitates tumour development, metastasis, and the ineffectiveness of standard therapy. Comprehending the geographical distribution of tumour cells is crucial for formulating more efficient treatment regimens. Diverse methodologies are employed to investigate spatial heterogeneity, encompassing modern imaging techniques such as MRI, PET, and multiplexed imaging, alongside omics approaches including genomes, transcriptomics, and proteomics. These instruments offer insights into the tumour microenvironment and facilitate the identification of resistant subpopulations. The amalgamation of imaging and genomic data via radiogenomics has emerged as a viable methodology, providing an extensive perspective on the spatial and molecular intricacies of tumours. Principal findings reveal that spatial heterogeneity fosters medication resistance by establishing microenvironments characterised by varying oxygen levels, immunological infiltration, and genetic alterations, hence complicating the efficacy of monotherapy strategies. Hypoxic environments and immunological evasion significantly contribute to treatment resistance. Addressing geographical heterogeneity has the potential to enhance cancer treatments. By analysing the molecular and geographical characteristics of tumours, physicians can customise therapies more efficiently, minimising resistance and improving therapeutic results. This methodology signifies a vital advancement in precision medicine, providing more individualised and efficacious cancer therapies in the future.

ABSTRACT: Recent advances in artificial intelligence—particularly Vision–Language Models (VLMs)—offer promising avenues for enhancing microscopic diagnostics. This review synthesizes the current landscape of VLM applications across microbiology, hematology, cytology, and histopathology, spanning tasks such as Gram stain classification, cell-type recognition, feature localization, captioning, and report drafting. We outline how VLMs integrate visual features with domain-specific prompts to support triage, decision support, and quality control, while highlighting opportunities for few-shot and zero-shot generalization to rare findings. In parallel, we compare conventional convolutional pipelines with VLM-enhanced workflows, emphasizing gains in scalability, reproducibility, and explainability through multimodal rationales and grounded visual evidence. Key challenges include data curation and harmonization across laboratories, domain shift from variable staining and optics, bias and safety risks, limited task-relevant benchmarks, and the need for rigorous human-in-the-loop evaluation in clinical contexts. We propose a practical roadmap for deployment—covering dataset governance, prompt and template standardization, uncertainty reporting, and audit trails—alongside research priorities in robust evaluation, privacy-preserving learning, and alignment with clinical guidelines. Overall, VLMs are poised to complement expert microscopy by accelerating routine workflows and improving documentation, provided their adoption is guided by transparent validation and fit-for-purpose governance.

ABSTRACT: Cervical cancer remains a leading cause of cancer-related mortality in Sub-Saharan Africa, where it disproportionately affects women due to late-stage diagnoses. Despite the availability of preventive measures such as screening and HPV vaccination, uptake remains critically low. This systematic review and meta-analysis aimed to estimate the pooled prevalence and identify key predictors of cervical cancer screening uptake across Sub-Saharan Africa. A comprehensive search of databases including PubMed, Google Scholar, African Journal Online (AJOL) and ScienceDirect identified 27 studies involving a total of 357,586 women. Our results revealed that the overall prevalence of cervical cancer screening uptake was 21.2% (95% CI: 16.2%, 27.2%). Key predictors of uptake included education, healthcare access, awareness of cervical cancer, age, and integration with other health services like HIV care. This study underscores the urgent need for tailored interventions to address barriers such as lack of awareness, financial constraints, and cultural stigma. The findings provide crucial evidence to guide policy and public health strategies aimed at increasing screening rates and reducing the cervical cancer burden in the region.

ABSTRACT: Pathogen-reduction technologies (PRTs) methods for platelet and plasma are increasingly being relied on to inactivate a broad spectrum of pathogens to ensure safety in transfusion. However, there is continuing debate about the impact of such technology on clinical effectiveness, bleeding outcomes, and transfusion-related adverse events.
Objective: This systematic review evaluated the clinical effectiveness and safety of PRT-treated platelets and plasma using studies published between 2015 and 2025.
Methods: Following PRISMA 2020 guidelines, major databases including PubMed, Scopus, Embase, Web of Science, and Google Scholar were searched for studies published between 2015 and 2025. Eligible studies included human studies, platelet and/or plasma products that have been treated with specific PRT technology.  A total of 1256 records were identified. Findings were synthesized narratively and presented descriptively.
Results: Fifteen qualifying studies utilizing pathogen-reduced platelets and plasma from various areas were included.  In randomized trials, platelets treated with PRT consistently exhibited decreased CCI at both 1 hour and 24 hours compared to conventional platelets, with certain studies indicating greater platelet use.  Even though the platelet increments were lower, most trials did not report any significant rise in WHO grade ≥2 clinical bleeding, and the hemostatic efficacy was still satisfactory.  Safety outcomes were relatively good: datasets showed that transfusion-reaction rates were low (<1%) and major adverse events were not so common.  PRT systems showed strong pathogen-inactivation abilities, including the ability to effectively inactivate clinically important viruses such as hepatitis viruses, dengue, and Japanese encephalitis virus.  Different technologies had different results, and UVC-based systems sometimes showed smaller increases after transfusions.
Conclusion: Platelets and plasma treated with PRT are still clinically useful and very safe. They also greatly lower the risk of infections that can be spread by transfusions.  Even though there are fewer laboratory increments and more platelet use, these changes don't seem to affect clinical hemostasis. Strengthening implementation methods, inventory planning, and hemovigilance systems alongside continuing evaluation of performance will enable safer transfusion procedures and safeguard vulnerable patient groups globally.

ABSTRACT: Minimal residual disease (MRD) has become a significant predictor of relapse and survival in acute myeloid leukemia (AML), indicating the extent of remission beyond traditional morphological evaluation. Although multicolor flow cytometry and quantitative PCR are essential methodologies in minimal residual disease identification, both are constrained by immunophenotypic variability, the necessity for stable molecular targets, and limited sensitivity. Advancements in next-generation sequencing (NGS) have revolutionized the minimal residual disease (MRD) field by enabling highly sensitive, mutation-driven identification of leukemic clones across a broad genomic landscape. Contemporary error-suppressed next-generation sequencing techniques—such as unique molecular identifiers, duplex sequencing, and single-molecule molecular inversion probes—have enhanced analytical sensitivity to the 10⁻⁵ to 10⁻⁶ range, enabling the detection of ultra-low-frequency variations with greater specificity. These techniques improve clinical risk classification, refine prognostication within genetically defined AML subtypes, and guide therapeutic options, including post-remission therapy, targeted inhibition, and the timing and intensity of allogeneic stem cell transplantation. Innovative applications, such as single-cell sequencing, cell-free DNA studies, and integrative multi-omic MRD evaluation, enhance the capabilities of genomics-based monitoring. Nonetheless, obstacles remain, such as differentiating cancer mutations from clonal hematopoiesis, standardizing analytical pipelines, establishing clinically relevant thresholds, and incorporating NGS MRD into standardized treatment protocols. This review encapsulates contemporary NGS methods for AML MRD diagnosis, assesses their clinical ramifications and constraints, and suggests future pathways necessary for comprehensive clinical integration. With advancements in the area, NGS-based MRD is set to become a pivotal element of precision-guided AML control.