Baobab Index

Breast cancer remains the most common cancer affecting women globally, with a disproportionate impact on low- and middle-income countries (LMICs), where survival is poor despite lower incidence. Conducting molecular studies in these settings is often hampered by limited resources and technical challenges, particularly when using traditional DNA sources. This is also true for pharmacogenetic studies among Africans. For this, we propose novel

Mycotoxin contamination is an important threat to food and feed safety as well as human and animal health, with particular emphasis on oxidative stress, apoptosis, autophagy, inflammation, and dysbiosis. Mycotoxins represent major health threats because they disturb cellular homeostasis and induce oxidative damage. Nutritional factors, such as dietary antioxidants and bioactive chemicals, can influence the body's reaction to mycotoxin exposure, either reducing or increasing its effects. This study discusses how mycotoxins (aflatoxin B1, deoxynivalenol, and ochratoxin A) induce oxidative stress by producing reactive oxygen species (ROS)-mediated DNA damage, which induces cellular damage and activates apoptosis, an intended cell death process that is critical for tissue integrity. Furthermore, mycotoxins alter autophagy, a cellular degradation process that can be beneficial or destructive depending on the situation, affecting cell survival. The inflammatory response is particularly important because mycotoxin-induced oxidative stress and cell damage activate inflammatory pathways, which contribute to tissue injury and disease progression. Nutritional factors high in antioxidants, anti-inflammatory substances (Lycopene, Curcumin, Thyme oil, Gum Arabic, and Ginger), probiotics, and prebiotics show potential in mitigating these negative consequences by reducing oxidative stress and inflammation. Advances in molecular biology and omics technologies (transcriptomics, proteomics, metabolomics, and single-cell sequencing) can lead to better knowledge of the underlying pathways, allowing for more tailored nutritional recommendations and medicinal interventions. Finally, combining dietary modulation with mycotoxin risk management is a viable path for protecting health and increasing resilience to mycotoxin-related toxicities in animals.

Suffix trees underpin many string-processing applications, yet their classical O(n) construction algorithms suffer in practice from the gap between processor and memory speeds: cache misses, not arithmetic operations, dominate wall-clock time. This paper asks whether a lightweight machine-learning predictor can anticipate which tree branches Ukkonen's online construction will visit next, allowing the relevant nodes to be prefetched into the cache without changing what the algorithm actually does. The intuition is simple: the predictor whispers hints about upcoming memory accesses; Ukkonen's algorithm itself remains untouched. We formalise this idea through an observationally transparent layer and prove that the augmented algorithm produces exactly the same suffix tree as Ukkonen's algorithm, regardless of how good (or bad) the predictor is. Complexity is preserved at O(n) under fixed model parameters, and we derive an explicit break-even condition that predicts when learning helps and when it hurts. Experiments on natural language, genomic, and source-code corpora confirm 24-38% reductions in L3 cache misses and 1.24-1.30 × wall-clock speedups, with prediction accuracy explaining 79% of speedup variance (Pearson r = 0.89). Where the theory predicts failure-small alphabets, uniform distributions, or oversized models-the algorithm slows by up to 22%, exactly as predicted. The observational-transparency framework introduced here generalises to other classical algorithms and offers a reusable template for combining machine learning with rigorously analysed data structures.

Klebsiella pneumoniae (Kpn) is a major cause of infant mortality worldwide, with most transmission occurring among hospitalized neonates in low- and middle-income countries where infections caused by multidrug-resistant Kpn (MDR-Kpn) are increasingly common. We hypothesized that integrating laboratory surveillance for neonatal colonization and infection, real-time epidemiologic investigations, and whole-genome sequencing (WGS) could identify transmission pathways to guide targeted infection prevention and control (IPC) strategies. We conducted Kpn surveillance in a 36-bed neonatal unit in Botswana over 12 months (2022-2023). WGS was performed on Kpn isolates from bloodstream infections (BSIs), and MDR-Kpn isolates collected from environmental sampling during outbreaks and twice-monthly colonization screenings (skin and perirectal swabs) using culture media selective for MDR-Kpn (CHROMagar Extended-spectrum beta-lactamase [ESBL]/SuperCarba). WGS data were analyzed using multilocus sequence typing (MLST), pangenome and reference-based single-nucleotide polymorphism (SNP) analyses, and Bayesian phylogenetics. We identified 55 Kpn BSIs during the 12-month surveillance period and the median prevalence of MDR-Kpn colonization was 28%. Kpn was recovered from multi-use intravenous (IV) fluid bags during a Kpn outbreak (41 BSIs, 10 deaths), which was controlled by implementing a 24-hour discard policy for IV medications. Among 270 Kpn isolates available (28 BSI, 232 colonizing, 10 environmental [six IV fluid, four sink drain]), WGS confirmed over half of BSI genomes (n = 17) and all six IV fluid isolates belonged to ST1414 and were closely related (<25 SNPs). The ST1414 clone was susceptible to third-generation cephalosporins and was therefore not detected during MDR-Kpn colonization screening. This study reinforces the value of integrating WGS with real-time epidemiologic investigations to understand transmission dynamics and guide IPC. Colonization surveillance focused solely on MDR-Kpn may overlook drug-susceptible but outbreak-prone strains.

Killer-cell immunoglobulin-like receptors (KIRs) are critical regulators of the innate immune system and are found on the surfaces of natural killer (NK) cells. The KIR encoding genes, located on chromosome 19q13.4, are genetically diverse and associated with HIV progression. However, there is limited knowledge on the diversity of KIR from Uganda and Botswana HIV-infected paediatric cohorts. We applied next-generation sequencing technologies on 312 participants (Uganda: n = 246, Botswana: n = 66), Pushing Immunogenetics to the next-generation (PING) bioinformatics pipeline, logistic regression in Python for Population genetics (PyPOP) software to characterize allelic, allotypic, and disease associations. We found distinct patterns of KIR diversity between the cohorts (normalized to n = 50): the Ugandan cohort had 156 alleles compared to 99 in Botswana. Using the Ewens-Watterson test, exploratory analyses found that KIR3DL2 showed significant positive deviation towards homozygosity among long-term non-progressors (LTNPs) in the Uganda cohort, while KIR3DL1/S1 significant balancing selection among LTNPs in the Botswana cohort. Additionally, the Bw4-80I HLA ligand was more frequent in Ugandan LTNPs than Rapid Progressors (RPs) (39.2% vs 29.2%, P-value: 0.029). No KIR/HLA alleles were significantly associated with HIV disease progression after adjustment for multiple testing in the Ugandan cohort. Our study findings expand knowledge of the KIR genetic diversity in African populations.

Although extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE) are a global health challenge, molecular data from low- and middle-income countries are limited. We employed whole-genome sequencing to characterize ESCrE in community and healthcare settings in Botswana. Study isolates were collected from three hospitals and six outpatient clinics in Botswana, as well as from adults and children in the community. Enrollment occurred from 1/15/2020 to 9/4/2020, but paused from 4/2/2020 to 5/21/2020 due to a countrywide COVID-19 lockdown. Isolates from rectal swabs of participants testing positive for ESCrE underwent whole-genome sequencing. Genomic data were analyzed to characterize resistance genes, sequence types (STs), and exposures associated with putative inter-person transmission. Escherichia coli and Klebsiella pneumoniae ESCrE were diverse, represented by 87 and 49 STs respectively, carrying 16 different ESBL gene alleles. Twelve E. coli STs accounted for most isolates, with these common STs being observed in both community and healthcare settings, and increasing in the proportion post-lockdown (61% versus 80%). Examination of factors associated with harboring genetically similar E. coli revealed shared household and social networks across lockdown periods, with differences in shared hospital exposure and participant age between lockdown periods. Genomic characterization of ESCrE in Botswana revealed diverse STs carrying common ESBL genes, with overlapping STs among hospital and community participants consistent with intersecting transmission networks. Risk analysis of transmission supported the role of direct human contact, with the COVID-19 lockdown impacting the diversity of ESCrE and transmission pathways, highlighting the potential for behavioral changes to impact ESCrE spread.

The

The use of antibiotics in swine production during the stressful weaning period is widespread. While their impact on the gut microbiome is documented, their effect on the developing oral microbiota, a critical gateway to systemic health, remains poorly understood. This study investigated how chronic exposure to tylosin (TYL) or a chlortetracycline-sulfadiazine-penicillin combination (CSP) shapes oral microbiota assembly in piglets from 21 to 60 days of age. Healthy piglets exhibited a defined ecological succession, transitioning from an early, Pseudomonadota-dominated types of oral microbiota, or referred to as orotypes (driven by Moraxellaceae) at weaning to a stable, mature Bacillota-dominated state (driven by Lachnospiraceae) by 40 days of age. Antibiotic exposure disrupted this developmental program. CSP treatment locked the microbiota in an immature, Pseudomonadota-dominated state, while TYL promoted a dispersed and unstable Bacillota community. Dysbiosis was marked by enrichment of pathobionts (e.g., Moraxella, Bergeyella) and depletion of beneficial commensals like Veillonella and Phocaeicola, with the latter reduced in both the oral and gut microbiota. These structural shifts were linked to dysregulated microbial energy and lipid metabolism. Crucially, antibiotics compromised mucosal immunity, reducing salivary secretory IgA (SIgA), and provoked inflammation, evidenced by elevated salivary extracellular ATP (eATP), histological damage and transcriptome alteration in oral tissue, and changed serum metabolites. Our findings demonstrate that early-life antibiotic exposure disrupts the developmental programming of the oral ecosystem. The oral microbiota serves as a sensitive indicator of antibiotic impact and a key mediator of systemic health, highlighting the need for strategies that safeguard microbial succession to promote sustainable swine health.

The genetics of complex traits in Africa has been historically understudied, which can contribute to healthcare inequalities. Here, we present observations of 27 anthropometric, cardiovascular, and blood biomarker measurements across 2,124 individuals from sub-Saharan Africa for whom we also have dense genotype data. First, we identified trait values that differ significantly across populations and subsistence lifestyles (e.g., hemoglobin levels and height). We then identified traits with high degrees of sexual dimorphism (e.g., weight and grip strength). ADMIXTURE analyses revealed substantial population structure in our dataset, and many of the phenotypes studied here are correlated with genetic ancestry components, particularly skin color and body size traits. A variance partitioning approach further revealed traits in which much of the SNP heritability is due to polymorphisms that also contribute to differences between ancestry components. Following genomic imputation, we performed genome-wide association studies (GWASs) for all 27 traits and identified >100 independent autosomal SNPs with genome-wide significant associations for at least one trait (p < 5 × 10