Baobab Index

Soil microbial communities underpin ecosystem functions critical for sustainable agriculture, yet our understanding of how long-term management of tropical agroecosystems shapes these communities remains limited. This is particularly the case in sub-Saharan Africa where soil health challenges are most acute for food security. Using four long-term (~20 years) experiments across contrasting agroecological zones in Kenya, we studied how organic inputs (farmyard manure, Tithonia diversifolia, Zea mays stover; applied at 4 Mg C ha

Fusarium species cause yield losses in wheat production through fusarium head blight (FHB) and the associated contamination of regulated mycotoxins, such as trichothecenes and zearalenone. Despite the widespread use of PCR-based molecular approaches for Fusarium detection, quantification, and chemotyping, most primers were developed prior to both modern phylogenetic reclassification and the availability of high-quality genome assemblies, leaving their specificity and robustness largely untested. Existing PCR- and qPCR-based assays for Fusarium detection in wheat were reviewed and re-evaluated in silico using a curated genome panel. Of 53 species-specific primer pairs, 14 (26.4%) achieved high-specificity grades (A-B), whereas 25 (47.2%) were lower performing (D-E), mainly due to cross-reactivity or inconsistent target amplification. Chemotype assays targeting TRI and ZEN genes showed stronger agreement with reported chemotypes, especially for informative TRI loci such as Tri3, Tri7, and Tri12. To support improved qPCR assay design and reporting, we propose FusaMIQE, a Fusarium-adapted framework based on MIQE 2.0 guidelines, tailored to the specific challenges of Fusarium diagnostics in wheat. Together, this manuscript provides the first in silico assessment of PCR/qPCR primers as diagnostic tools for FHB pathogens and associated recommendations for good practice (FusaMIQE) of Fusarium diagnostics in wheat.

Animals coexist with complex microbial communities that influence their development, immunity, metabolism, and behavior. Evidence shows these effects arise not just from metabolic and immune signaling but also from epigenetic mechanisms that alter host gene expression. Microbial signals can modulate DNA methylation, histone modification, chromatin accessibility, and RNA pathways, reshaping transcription across tissues. This review synthesizes evidence from diverse animal systems to demonstrate how microbial communities influence epigenetic landscapes and contribute to immunity, development, metabolism, and neurobiology. We explore data suggesting that microbial epigenetic interactions extend into the tumor microenvironment, where intratumoral microbes may shape disease progression by remodeling epigenetic states. Comparative studies indicate that microbial regulation of host epigenetics is an evolutionarily conserved mechanism linking environmental signals to phenotype. Despite recent advances, questions remain about causality, cell-type specificity, persistence, and inheritability of these effects. We propose microbial epigenetic regulation as a key interface integrating microbial cues with host physiology and pathology, providing a framework for understanding host-microbe interactions across species.

This study uniquely integrates extraction optimization, structural characterization, cytoprotection, molecular docking, and DFT analysis to valorize lemon juice pomace pectin within a circular bioeconomy framework, distinguishing it from previous work limited to peel pectin or crude extracts. The extraction process was carefully optimized to preserve the structural integrity of the polysaccharide, resulting in a high yield of galacturonic acid-rich pectin with moderate degrees of esterification. Structural analyses confirmed typical pectic features, including α-configured galacturonic acid residues as well as rhamnose, arabinose, glucose, mannose, xylose and galactose units. Therefore, PLP polysaccharides exhibited significant antioxidant activity, demonstrated by dose-dependent DPPH radical scavenging (79.5% at 10 mg/mL) and ferric-reducing antioxidant power (FRAP) of 1522.5 μmol Fe

The Barki sheep is well adapted to desert conditions with intense solar radiation, low precipitation, and feed shortages. This review highlights advances in the genomic characterization of Barki sheep and outlines prospects for genetic improvement. Studies on the genomic architecture of their growth traits have identified multiple candidate genes, many of which overlap with those reported in other sheep breeds, suggesting the existence of shared biological pathways for growth regulation. Reproduction performance has been linked to genomic mutations in key loci, with limited evidence of polymorphisms in other genes, reflecting possible breed-specific selection pressures. Genomic studies have further revealed candidate genes related to milk production, although milk yield remains modest. Heat stress represents a major challenge for desert livestock, and the physiological responses of Barki sheep are evident through changes in the respiration rate, gas exchange, and breathing intensity. Candidate genes associated with heat tolerance are involved in multiple signaling and transduction pathways that regulate cellular and biochemical responses to heat stress, highlighting the strong adaptive capacity of the breed. Population-based genomic studies have shown that Barki sheep cluster closely with other Egyptian breeds but remain genetically distinct from exotic populations, underscoring their local adaptation. The considerable within-breed genetic variation provides opportunities for selection to improve lamb growth rates while maintaining moderate ewe size, lean meat, and heat resilience. Overall, genomic evidence indicates that Barki sheep represent a valuable model for climate-resilient livestock production. Owing to their unique adaptation to desert conditions and the availability of identified candidate genes for growth, reproductive performance, milk production, and heat tolerance, these genes provide a foundation for accurate genomic prediction. Future breeding programs should focus on their strengths to improve productivity while safeguarding their adaptive performance.

Combined heat and drought stress, mainly during sensitive growth stages, considerably limits wheat yields. Herein, we report on an experiment conducted to analyze and predict the phenology, architecture, and kernel yield component (PAKyC) traits of a diverse bread wheat population grown under heat stress and fully irrigated conditions (HSFIC), and combined recurrent drought and heat stress (CRDHS). 17,711 high-quality single-nucleotide polymorphisms (SNPs) were used to perform a GWAS for 13 PAKyC traits on 187 genotypes, a subset of 234 genotypes, using the BLINK model. Nine constitutive SNPs, 24 marker-trait associations (MTAs), broad-effect pleiotropic SNPs, conditional pleiotropic SNPs, adaptive pleiotropic SNPs under CRDHS, and two robust SNPs were identified. Furthermore, 35 candidate genes were associated with cellular components, biological processes, and molecular functions under CRDHS and HSFIC. Among these genes, 12 were highly expressed (> 0.5 TPM) in response to drought, heat, and combined stresses. Nine genes were identified to be transcription factors regulating drought and heat responses, while the functions of the other three genes remain unclear. Overall, HSFIC and CRDHS environments enabled the dissection of heritable and strongly correlated traits, MTAs, and pleiotropy types: constitutive, adaptive, and conditional. They also helped identify robust SNPs and candidate genes that are important for bread wheat breeding.

Despite the high burden of cardiovascular disease (CVD) in Latin America and the Caribbean (LAC), risk prediction models adapted for use in LAC populations remain limited. The aim of this study was to recalibrate the Systematic COronary Risk Evaluation 2 (SCORE2) risk models for estimating 10-year CVD risk in individuals without prior CVD or diabetes mellitus in LAC, resulting in the SCORE2 Latin America and the Caribbean (SCORE2-LAC) models. Sex-specific, competing risk-adjusted SCORE2 models were recalibrated to contemporary CVD incidence across four risk regions, defined by country-level age- and sex-standardized CVD mortality rates, using region-specific risk factor distributions. Cardiovascular disease incidence was estimated from CVD mortality data and ratios of the total first-to-fatal CVD events, derived from 40 237 152 individuals (1 261 329 CVD events). External validation included 132 512 individuals without prior CVD or diabetes from 11 cohorts across seven countries (3938 CVD events). Discrimination was assessed using Harrell's C-index. In the external validation datasets, the pooled C-index of SCORE2-LAC was .740 [95% confidence interval (CI) .716-.763], with cohort-specific C-indices ranging from .674 (95% CI .588-.761) to .789 (95% CI .747-.831). Estimated CVD risk varied several-fold across the four LAC risk regions. For a 50-year-old non-smoker with a systolic blood pressure of 140 mmHg, total cholesterol of 213 mg/dL (5.5 mmol/L), and HDL cholesterol of 50 mg/dL (1.3 mmol/L), the predicted risk ranged from 3% in low-risk countries to 10% in very-high-risk countries for women, and from 4% to 10% for men. The SCORE2-LAC models provide region-specific contemporary estimates of 10-year CVD risk in apparently healthy individuals, enabling identification of individuals at high CVD risk across LAC.

We report 104-week placebo-controlled data and long-term open-label extension (OLE) data from the ongoing ELATIVE® phase III trial (NCT04526665) of elafibranor in primary biliary cholangitis (PBC). 161 patients were randomized 2:1 to elafibranor 80 mg or placebo. The double-blind period (DBP) consisted of 52-week common (Part 1) and variable (Part 2) periods. Patients completing Part 1 continued into Part 2 until all patients completed Part 1, or for a maximum of 104 weeks. All patients completing Part 1 could enter the OLE and receive elafibranor. At Week 104 in the DBP Part 2, 64.3% (18/28) and 10.7% (3/28) of elafibranor-treated patients achieved biochemical response and alkaline phosphatase (ALP) normalization, versus no placebo-treated patients. In patients with moderate-to-severe fatigue or pruritus at baseline, mean (SE) changes to Week 104 in PROMIS Fatigue Short Form 7a (PFSF 7a) and PBC Worst-Itch Numeric Rating Scale (PBC WI NRS) were -6.3 (2.2) versus -0.4 (1.2) and -4.1 (1.0) versus 0.3 (1.2) with elafibranor versus placebo. 138 patients entered the OLE (continuous elafibranor: n=93; crossover elafibranor: n=45). In continuous patients at Weeks 104 and 156, 58.8% (47/80) and 65.0% (13/20) achieved biochemical response, and 15.0% (12/80) and 25.0% (5/20) achieved ALP normalization. In crossover patients, 51.2% (21/41) and 22.0% (9/41) achieved biochemical response and ALP normalization after 52 weeks. In continuous patients with baseline moderate-to-severe symptoms, mean (SE) changes to Week 130 in PFSF 7a and PBC WI NRS were -4.8 (1.5) and -4.0 (0.7). There were no unexpected safety findings. Through three years of treatment, elafibranor led to sustained biochemical improvements and was generally well tolerated, with numerical improvements in fatigue and pruritus. NCT04526665 (https://clinicaltrials.gov/study/NCT04526665); first registered 08/26/2020 IMPACT AND IMPLICATIONS: • Given the chronic, progressive nature of primary biliary cholangitis (PBC), the long-term efficacy and tolerability of treatments is important.• Here, we present two-year results from the double-blind period, and long-term data from the ongoing open-label extension of the phase III ELATIVE® trial, wherein elafibranor (a peroxisome proliferator-activated receptor-α/δ agonist) treatment led to sustained biochemical improvements, stable non-invasive tests of fibrosis, and numerical improvements in fatigue and pruritus, through three years.• Elafibranor demonstrated a favorable safety profile up to a maximum treatment exposure of 3.5 years, including in patients crossing over from placebo.• These findings support elafibranor's role as a durable long-term treatment for patients with PBC, and are particularly relevant for clinicians managing patients with inadequate response or intolerance to first-line treatments.

Face2Gene is a clinical tool that leverages facial features to aid genetic diagnosis. The DeepGestalt application suggests potential diagnoses based on facial similarity, while the D-Score evaluates likelihood of an individual having dysmorphic features suggestive of a possible genetic diagnosis. Given performance variability across populations and limited data from South Africa, this study assessed clinical utility in South African children with neurodevelopmental disorders (NDDs). Facial photographs from 301 children were analysed. The cohort comprised three groups: 36 children with NDDs with confirmed molecular diagnoses, 176 with NDDs without molecular diagnoses and 89 unaffected children. Diagnostic (recognition) accuracy was measured by whether the confirmed diagnosis appeared in the top-1 or top-10 ranked algorithm-generated suggestions (DeepGestalt). D-Scores were extracted to calculate group differences. Among children with confirmed molecular diagnoses, accuracy was 19% (95% CI: 9-35%) (top-1) and 34% (95% CI: 20-52%) (top-10), improving to 33% (95% CI: 16-56%) and 61% (95% CI: 39-80%) when limited to conditions included in the DeepGestalt training set. One-way ANOVA revealed differences between participants with and without significant dysmorphic features, as assessed by clinicians. The D-Score demonstrated moderate sensitivity (78%, [95% CI: 0.64, 0.88]) and low specificity (42%, [95% CI: 0.38, 0.50]), but high negative predictive value (91%, [95% CI: 0.84, 0.95]), suggesting it may be more useful for ruling out dysmorphism; however, the low specificity indicates a high rate of false positives, even among clinically non-dysmorphic children. These findings suggest that under-representation of African populations may limit clinical performance and equity of AI-based facial phenotyping tools.