Baobab Index

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The inactivation of tumour suppressor genes is a key step in cancer development, and is usually achieved by homozygous loss. In prostate cancer, however, large genomic regions are often hemizygously lost, which complicates the identification of putative tumour suppressors in these regions. Here, we develop Epi2Hit, an integrative computational method that leverages whole genome sequencing, epigenomic profiling and gene expression to identify biallelic inactivation of tumour suppressor genes involving DNA methylation of promoter and enhancer regions of one allele and genomic loss of the other allele. We apply Epi2Hit to a cohort of 2,021 prostate cancers to discover tumour suppressor genes. In particular, we identify epigenetic biallelic inactivation of ZFHX3 at a recurrence level similar to TP53. Biallelic inactivation of ZFHX3, a transcriptional repressor, leads to upregulation of oncogenes, including MYC and a shorter time to metastasis. Finally, we provide evidence that epigenetic silencing as 2nd hit is particularly enriched in regions with nearby essential genes, precluding homozygous loss.

There are disparities in access to antipsychotics for schizophrenia across different country settings. Improving access to a wider and more equitable range of medications in low-income and middle-income countries is a priority. A multidisciplinary team of international experts, including individuals with lived experience, appraised the most relevant and recent information on antipsychotics in schizophrenia and contextualised it to four African countries (Ethiopia, Nigeria, Rwanda, and South Africa) using a validated consensus methodology. We recommended a list of drugs to prioritise to guide clinical implementation and research, and market shaping. We identified key evidence gaps: little of the existing evidence comes from the countries of interest, trials generally involve highly selected populations, and the complexity of real-world settings is not reflected. However, this methodology highlights a route forward to prioritise the best available evidence on pharmacological treatments for schizophrenia at a global scale, which could also be applied to treatments for other mental health conditions.

Pteropine orthoreoviruses are emerging bat-borne zoonotic viruses of the genus

Tsetse flies (Glossina spp.) transmit African trypanosomes, the causative agents of human African and African animal trypanosomiases (HAT and AAT, respectively). These neglected tropical diseases impose significant public health and economic burdens across sub-Saharan Africa. Trypanosome transmission by tsetse flies is influenced by multiple factors, including host genetic background, ecological factors, and interactions with heritable microbial endosymbionts. Spiroplasma glossinidia has recently emerged as an important modulator of tsetse reproductive fitness and vector competence, making it a potential target for symbiont-based vector control strategies. In this review, we summarize the current knowledge of the tsetse-Spiroplasma symbiosis. We detail Spiroplasma's spatial and temporal infection dynamics in laboratory-reared and natural populations. Additionally, we highlight key aspects of the bacterium's genomics, phylogenetics, and physiological interactions with its tsetse host, including influences on host gene expression reproductive physiology, and vector competence. Finally, we discuss how the tsetse-Spiroplasma symbiosis could be harnessed to develop innovative, biological-based vector control and trypanosome transmission-blocking strategies, and we identify critical gaps that must be addressed to translate these findings into effective disease control interventions.

Medication dose miscalculations remain one of the most persistent patient safety concerns in clinical practice, while traditional teaching methods often fall short in ensuring proficiency. The integration of artificial intelligence (AI) based learning tools has the potential to enhance knowledge, clinical decision-making (CDM), and self-efficacy among nursing staff. To evaluate the effectiveness of a researcher-developed artificial intelligence-based mobile learning application designed to simulate realistic hospital medication environments with adaptive feedback on nursing's drug calculation knowledge, decision-making, and self-efficacy, while exploring its feasibility and acceptability in routine training contexts. Mixed-methods study with an embedded design, utilizing two-arm randomized controlled trial for quantitative evaluation and focus group discussions for qualitative exploration. The study was conducted at a non-governmental hospital where 56 nurses, randomly assigned to intervention group (n = 28) or a control group (n = 28). The mobile learning application simulated realistic hospital medication administration scenarios incorporating adaptive corrective feedback and progressively complex drug calculation cases. Data was collected at baseline and post-intervention using a drug dose calculation knowledge assessment, a clinical decision-making scale, and a self-efficacy scale. Post-intervention focus group discussions with the intervention group were analyzed using thematic analysis. The study group achieved significant improvements in knowledge, decision-making, and self-efficacy post-intervention compared to the control group with large effect sizes. Qualitatively, six themes emerged which discussed several aspects of the training such as; perceived clinical benefits, realism, increased nurses' confidence, ease of use and engagement, training efficiency and challenges and the potential for improvement. This is one of the first randomized controlled trials (RCTs) conducted using mixed-methods and focusing on training nursing staff on drug-dose calculation with artificial intelligence (AI) based simulation. Results indicated that the intervention was associated with significant improvements in the measured outcomes and was perceived positively by the participants. However, its broader implementation across different contexts requires further investigation. ClinicalTrials.gov Identifier: NCT07448259. Retrospectively registered on February 18, 2026. Registration Link: https://clinicaltrials.gov/study/NCT07448259 .

Semen analysis (SA), recognized by the World Health Organization (WHO) as the cornerstone of male infertility evaluation, remains indispensable in reproductive medicine. However, advances in assisted reproductive technology (ART) and artificial intelligence (AI) have highlighted the limitations of relying solely on conventional semen parameters. To critically review the evolving clinical role of SA by integrating conventional assessment with emerging functional, molecular, and computational approaches that improve diagnostic accuracy and individualized patient care. A narrative review of contemporary evidence was conducted, focusing on conventional semen parameters, biofunctional sperm testing, omics technologies, AI-assisted analysis, and broader clinical applications of SA. Conventional parameters, including sperm concentration, motility, and morphology, remain essential but inadequately reflect fertilizing capacity. Adjunctive assessments, including oxidative stress biomarkers and sperm DNA fragmentation, provide valuable insights into sperm function and reproductive potential. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, deepen mechanistic understanding, while AI enhances diagnostic precision, reproducibility, and standardization. Beyond infertility evaluation, SA also supports male contraceptive assessment, natural conception, ART, and patient counseling. Integrating conventional SA with functional, molecular, and AI-driven diagnostics provides a comprehensive framework for evaluating male fertility, advancing precision reproductive medicine and personalized clinical management.

The continuous emergence of variants of concern (VoCs) represents a significant challenge to effectively control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although FDA-approved vaccines and antivirals have been successfully developed and implemented for the prophylactic and therapeutic intervention of SARS-CoV-2 infection, recent VoCs could escape protection garnered by previous vaccine and antiviral approaches. Determining the efficacy of prophylactics and/or therapeutics against recent VoCs will assist in efficiently controlling currently circulating SARS-CoV-2 strains. We used our previously described bacterial artificial chromosome-based reverse genetics approach for Omicron BA.5 to generate a recombinant SARS-CoV-2 BA.5 encoding a fusion of ZsGreen to Nanoluciferase (rBA.5 ZsG-Nluc) from the locus of the viral nucleocapsid (N) protein separated by the porcine teschovirus-1 2A proteolytic cleavage site. The rBA.5 ZsG-Nluc replicates to levels comparable to recombinant BA.5 wild type (rBA.5 WT) and expresses high levels of ZsG and Nluc in cultured cells. This facilitates tracking viral infection and the identification of antivirals and neutralizing antibodies with EC

Stem architecture is a major determinant of lodging resistance, biomass accumulation, and harvest efficiency in soybean. However, the molecular features associated with contrasting stem growth habits in wild soybean remain incompletely characterised. Here, we performed an integrated transcriptomic, metabolomic, and epigenomic analysis of stem growth-habit divergence in wild soybean, comparing the wild-type accession ZYD7068 with contrasting vining and erect mutant lines derived from carbon-ion beam mutagenesis. Pairwise transcriptomic comparisons identified between 20 311 and 28 705 differentially expressed genes per contrast, with a core set of 2672 genes consistently altered across the comparisons. Functional enrichment, gene set variation analysis, and gene set enrichment analysis converged on xylem and phloem pattern formation as a prominent molecular pathway associated with growth-habit divergence. Random forest analysis identified BBR-BPC and ARF transcription factor families as major molecular discriminators, while metabolomic profiling revealed distinct metabolic profiles involving amino-acid-derived and lipid-associated metabolites. Whole-genome bisulfite sequencing revealed context-specific DNA methylation differences, including substantial variation in CHG methylation among erect mutant lines. Integrated network and in silico perturbation analyses prioritised four candidate genes associated with vascular development for future functional validation. Together, these results provide a multi-layer molecular resource for investigating stem growth-habit divergence in G. soja and establish testable candidate pathways and genes for subsequent functional studies and soybean improvement.

T-2 toxin is a trichothecene mycotoxin produced by Fusarium species and can cause disease after contaminated food or feed ingestion. This study aimed to investigate the impact of lycopene (Ly) on systemic inflammation, oxidative stress, and dysbiosis in mice exposed to T-2 toxin. A total of 20 male BALB/c mice (6 weeks old, weighing 23.5 ± 0.32 g) randomly divided into four groups (n = 5): Control (Cont), Ly, T-2, and T-2 + Ly groups. Findings revealed that Ly enhanced the body weight, feedd, and water intake that have been reduced by T-2. Ly increased the villus height (VH) and VH: crypt depth (CD) and decreased CD and villus width (VW) in ileum compared to the T-2 group. In alpha diversity, Staphylococcus and Corynebacterium were the most prevalent in Cont group; Staphylococcus, and Lactobacillus, were the most prevalent in T-2 group; Candidatus-Arthromitus and Staphylococcus were the most prevalent in T-2 + Ly group. Moreover, T-2 mice had significantly (p < 0.05) greater levels of interleukin-1 beta (IL-1β), interferon gamma (IFN-γ), Interleukin-17 (IL-17), and tumor necrosis factor-alpha (TNF-α) than Cont, while the Ly significantly (p < 0.05) lowered their concentration. The T-2 mice had significantly (p < 0.05) higher levels of reactive oxygen species (ROS) and malondialdehyde (MDA), while their catalase (CAT),, glutathione (GSH), adenosine triphosphate (ATP), and superoxide dismutase 1(SOD1) activities were significantly (p < 0.05) lower than Cont. Ly significantly (p < 0.05) restored their concentration. Moreover, there was a significant reduction (p < 0.05) of hexanoic, butyric, acetic, pentanoic, and Heptanoic acids in the T-2 mice compared to Cont. In contrast, treatment with Ly was found to significantly restore their levels compared to T-2 group. We conclude that Ly administration in the context of T-2-induced toxicity may help attenuate systemic oxidative stress and inflammation, possibly through modulation of gut microbiota and fecal short-chain fatty acids (SCFAs).