Huanglongbing (HLB), caused by ‘Candidatus Liberibacter asiaticus’ (CLas), poses a major threat to citrus production worldwide and has recently emerged as a serious constraint to sweet orange cultivation in Bangladesh. Despite widespread disease occurrence, information on the genetic diversity of CLas populations in the country is lacking. This study investigated the genetic structure of CLas across major sweet orange–growing regions of Bangladesh using tandem repeat number (TRN) variation at the CLIBASIA_01645 genomic locus. Field surveys were conducted in 17 districts between 2022 and 2023, and 89 HLB-symptomatic leaf samples were collected from commercial orchards. PCR and qPCR detection confirmed CLas infection in 67 (75%) and 74 (83%) samples, respectively. Thirty-seven representative isolates were sequenced and analyzed for TRN polymorphism. Ten TRN genotypes (TRN2–TRN12, excluding TRN3) were identified, with TRN6 being the most prevalent. Bangladeshi CLas isolates were further grouped into three classes based on TRN: Class I (TRN ≤ 5), Class II (5 < TRN ≤ 10), and Class III (10 < TRN ≤ 15), of which Class II was the predominant. All Bangladeshi isolates harbored the CTTGTGT repeat motif and clustered closely with Indian isolates in haplotype network and phylogenetic analyses, while isolates carrying the AGACACA motif from other countries formed a distinct clade. These results reveal intraspecific diversity of CLas in Bangladesh and suggest regional structuring and shared ancestry with neighboring Indian populations. This study provides the first population-level genetic insight into CLas in Bangladesh and establishes a foundation for improved epidemiological understanding and disease management.
Spinach is a nutrient rich leafy vegetable with high nitrogen demand. Its growth and productivity are strongly influenced by the availability of nitrogen. This study evaluated the effect of foliar-applied nano urea on the vegetative growth, chlorophyll content, and soil nutrient status of spinach in Hajee Mohammad Danesh Science and Technology University, Dinajpur, Bangladesh. The pot experiment was conducted in open-field conditions during the Rabi season, from mid-February to March 2025, using a completely randomized design (CRD) with six treatments and three replications. Treatments included T0 = Control (only soil), T1 = 100% RDF, T2 = Only Nano Urea (4 times) + 100% RDF (without Urea), T3 = 4 Times Nano Urea + 50% RDF (No Urea), T4 = 2 Times Nano Urea + 50% RDF, and T5 = No Nano Urea + No Urea + 100% Rest RDF. The results demonstrated that nano-urea treatments, especially the T3 treatment, significantly enhanced vegetative growth, such as plant height (12.81 cm and 17.47 cm at 30 and 45 DAS), number of leaves per plant (4.67 and 6.67 at 30 and 45 DAS), root length (6.90 cm), shoot length (17.47 cm), fresh plant weight (64.31 g), and chlorophyll content like chlorophyll a (11.22 mg g-1 FW), chlorophyll b (3.06 mg g-1 FW), and carotenoid (2.67 mg g-1 FW) compared to conventional fertilizer treatments. Soil nutrient analysis revealed improved availability of N, P, K, and S under nano-fertilizer treatments. The study highlights the potential of nano-urea to improve nitrogen use efficiency, enhance growth, and optimize soil fertility in spinach cultivation, suggesting its suitability as a sustainable nutrient management strategy.
BATScore is a longitudinal index developed by BATWatch Research Group (TeamBrain, Inc.) to quantify brain clearance efficiency over time. Derived primarily from BAT Levels, it integrates contextual adjustments from systemic inflammatory markers (e.g., hs-CRP, IL-6) and validated metabolic indicators (e.g., fasting glucose, insulin sensitivity) that reflect transient clearance pressure. Observational data from the BATWatch Registry (over 3,000 participants, 10,000+ data points) demonstrate that BATScore trajectories are stable within individuals and sensitive to clearance rhythm disruptions, making it a promising candidate for population-scale preventive neuroscience. This publication presents the conceptual framework, validation approach, and interpretive model for BATScore, while maintaining confidentiality of quantitative weighting and computational methods under the BAT Framework.
