Baobab Index

Epidermolysis bullosa simplex (EBS) is a genetic skin disorder driven by dominant pathogenic variants in

Cadmium (Cd) is a toxic heavy metal that causes severe physiological damage in plants, inhibiting growth and ultimately reducing crop yield. Lactic acid bacteria regulate Cd availability through bioaccumulation and biosorption. This study evaluated the Cd tolerance of Lactiplantibacillus plantarum 10CH by determining its survival capacity under Cd stress and its potential to mitigate Cd-induced stress in onion (Allium cepa L.). The bacterial strain tolerated Cd concentrations up to 100 µM, and whole-genome sequencing identified genes involved in Cd biosorption, accumulation, and efflux. Exposure of onion to increasing CdCl

Breast cancer remains the most frequently diagnosed cancer and a leading cause of cancer-related mortality among women worldwide, underscoring the need for accurate, minimally invasive biomarkers to support precision oncology. Conventional tissue biopsy remains the standard for molecular characterization but is limited by its invasiveness, inability to capture spatial and temporal tumor heterogeneity, and challenges in serial monitoring. Circulating tumor DNA (ctDNA), a tumor-derived fraction of cell-free DNA, has emerged as a promising liquid biopsy biomarker capable of providing real-time genomic information throughout disease progression. This narrative review examines recent advances in ctDNA biology, analytical technologies, clinical applications, current limitations, and future directions in breast cancer management. A structured literature search of PubMed/MEDLINE, Scopus, Embase, Web of Science, and Google Scholar identified relevant English-language publications from 2015 to 2026. Current evidence indicates that highly sensitive platforms, including digital PCR, BEAMing, and next-generation sequencing, can detect clinically actionable alterations in genes such as The Problem Breast cancer is the most common cancer and a leading cause of cancer death among women worldwide. Choosing the best personalized treatment requires analyzing tumor genetics. However, traditional tissue biopsies are invasive, miss differences across different parts of a tumor, and are difficult to repeat frequently. The Solution Circulating tumor DNA (ctDNA)—tiny pieces of cancer DNA shed into the bloodstream—offers a simple, minimally invasive blood test (“liquid biopsy”) to monitor a patient’s cancer in real time. Key Takeaways. Guiding Treatment: Advanced blood testing can detect key genetic mutations (such as PIK3CA, ESR1, TP53, ERBB2, AKT1, and BRCA1/2) to match patients with targeted therapies. Tracking Cancer: ctDNA is particularly effective for spotting tiny hidden traces of remaining cancer (minimal residual disease), monitoring how well treatments are working, and revealing early signs of drug resistance. Current Limits: ctDNA is not yet ready for early cancer screening because early-stage tumors release very little DNA into the blood. High costs and a lack of standardized testing rules also limit wide access. Bottom Line ctDNA is a powerful molecular compass for personalized breast cancer care. However, standardized guidelines, prospective clinical trials, and lower costs are still needed before it becomes routine standard practice everywhere.

Armed conflicts can severely disrupt wildlife conservation and management, yet their long-term genomic consequences remain poorly understood. South Sudan has experienced decades of conflict that have limited conservation efforts and prevented genomic assessment of its fauna, including the endangered subspecies of Nubian giraffe (Giraffa camelopardalis camelopardalis). Due to long-standing logistical and political challenges, populations from South Sudan have remained largely unsampled. The Nubian giraffe represents a critical conservation unit and new sampling efforts provide an opportunity to investigate its genomic diversity and potential genetic isolation by the White Nile River, a hypothesized gene flow barrier. Here, we present genomic data from 30 individuals sampled in Boma and Badingilo National Parks in eastern South Sudan. Adding these sequences to existing genomic data reveals genetically distinct groups within the Nubian giraffe according to three regions: Ethiopia-South Sudan, Kenya, Uganda. Despite limited wildlife management due to economic and political constraints in South Sudan, the Nubian giraffe populations have maintained high heterozygosity (He ≈ 0.14%) and minimal evidence of inbreeding (mean F

Recently, several studies using cloned PCR amplicons have revealed greater haplotype diversity in Giardia duodenalis assemblage B than can be detected using conventional methods. This study aimed to estimate the geographical distribution of G. duodenalis assemblage B using these highly diverse haplotype sets. Samples were collected from two Indonesian sites (Waitabula and Wainyapu). Partial sequences of the glutamate dehydrogenase (gdh), triosephosphate isomerase (tpi), and beta-giardin (bg) loci were used as the PCR targets. Sequence analysis of the cloned PCR amplicons confirmed the presence of unique haplotypes in each region. For further analysis, we employed not only the Indonesian (Waitabula and Wainyapu) haplotypes acquired in this study but also the Kenyan haplotypes detected in our previous study. The phylogenetic relationships among haplotypes were calculated and plotted using multidimensional scaling (MDS). The plot integrating information from the three loci indicated geographically dependent clustering not only between Waitabula and Wainyapu but also between Indonesia and Kenya. This study demonstrates that employing greater haplotype diversity detected using the PCR-cloning method is an effective way to detect geographical differences in G. duodenalis assemblage B.

Advances in digital pathology, image analysis, and artificial intelligence (AI) are rapidly transforming how pathologists and researchers interact with tissue samples and enable the development of diagnostic tools that harness high-resolution whole-slide images; these advances are in turn creating new opportunities for research, education, and routine clinical care globally. Liver disease is no exception, and digital pathology and AI have many applications in the diagnosis of liver cancer and liver diseases and in the assessment and management of transplantation. Although quantitative image analysis techniques have been applied to liver disease in research settings for over 50 years, recent improvements in image resolution, data storage, and the availability of advanced AI methods such as deep learning have driven multiple exciting developments. In this Review, we summarise the advancements in digital pathology, image analysis, and AI in liver disease. Key challenges such as access to and the logistics of using digital solutions, quality issues, and appropriate guidance in research and clinical use are reviewed, along with potential solutions to these challenges in the context of liver pathology and liver disease. Digital technologies are well established in liver pathology research, and access in clinical practice is increasing, with potential to address current laboratory challenges. Further evaluation is required to assess real-world effectiveness, clinical safety, and implementation of AI tools in liver pathology.

Ergothioneine (EGT) is a bioactive, rare variant of histidine with many applications in the medical, pharmaceutical, and food fields. Therefore, we aimed to investigate in this study the impact of genomic and physicochemical factors on EGT production by the industrial filamentous fungus Aspergillus oryzae. Firstly, to facilitate efficient EGT production, we analyzed the subcellular localization of the three EGT biosynthetic enzymes present in A. oryzae. During screening for the most potent producer of EGT among bioengineered constructed transformants, the strain EgtACO overexpressing both AoegtA and AoegtC showed promising EGT production in DPY medium. Five days of incubation was the optimum period, and CZYP medium was the optimum medium for EGT production. Co-cultivation with the nisin Z-producing Lactococcus lactis JCM 7638 yielded EGT production equivalent to that of the EgtACO strain alone. Having broad-spectrum antimicrobial activity without suppressing growth of the EgtACO strain suggested that bacteriocin may help reduce the risk of contamination during long-term cultivation. Moreover, supplementing the production medium with L-methionine or zinc sulfate improved EGT production (1468.5 or 1565mg/L, respectively). Furthermore, repeated inoculation of the producer strain EgtACO and incubation in blue light were the optimum conditions for EGT production (1895 mg/L). Finally, we achieved cost-effective EGT production using A. oryzae strain EgtACO under the optimal culture conditions using agricultural wastes: potato peel and sweet potato peel (293 and 308mg/L, respectively).

Parkinson's disease (PD) is a progressive neurodegenerative disorder with a prolonged prodromal phase and complex motor symptoms. Despite improved clinical criteria, early diagnosis and longitudinal monitoring remain challenging. While cerebrospinal fluid (CSF) and plasma metabolites and proteins show biomarker potential, their utility in predictive models is insufficiently characterized. We employed a secondary computational approach to integrate proteometabolomic profiles from CSF and plasma samples of >1100 Parkinson's Progression Markers Initiative (PPMI) participants. Using multi-omics machine learning, we identified biofluid-specific signatures and evaluated predictive performance. Twenty-one biomarker candidates were validated across three models (SVM, GLMNET, RF); SVM and GLMNET achieved the highest recall (83-86%) and AUCs of 0.84-0.89. Longitudinal mixed-effects modeling revealed eight candidates associated with progression across diagnostic stages. We identified a three-part molecular framework characterizing neurodegeneration: a diagnostic subpanel reflecting early microbiome dysregulation (secretory granins and metabolites) and synaptic breakdown; a second subpanel monitoring phenoconversion via neurogenesis precursors and extracellular matrix proteins; and a third subpanel tracking progression through chronic neuroinflammation and immune activation. This integrated multi-omics approach provides a robust framework for stage-specific PD monitoring and potential clinical deployment.