Developing doubled haploid (DH) lines through anther or microspore culture is an important strategy for shortening breeding cycles and accelerating crop improvement. The present study aimed to enhance the regeneration of rice haploids through anther culture-induced calli and subsequently convert them into DH bacterial leaf blight (BLB)-resistant lines. Eleven lines expressing resistance against prevalent strains of Xanthomonas oryzae pv. oryzae were crossed as male parents with elite high-yielding basmati and non-Basmati varieties to develop F(1)s for collecting anthers at the appropriate stage of pollen development. Optimum callus induction in 36.45% of the genotypes was obtained on N-6 medium supplemented with maltose (40 g/l), 2,4-D (2.5 mg/l), and kinetin (0.5 mg/l), and further callus proliferation was enhanced in the presence of amino acids, particularly a combination of cysteine and tryptophan. High scores of haploid regeneration frequency were obtained in MS medium augmented with sucrose (30 g/L), BAP (2.0 mg/l), kinetin (0.5 mg/l), and NAA (0.5 mg/l). Fortification of regeneration medium with tryptophan (25 mg/l) and cysteine (40 mg/l) resulted in maximum regeneration of calli. Ranbir Basmati, Saanwal Basmati, Basmati 564, Ranbir Basmati & times; IRBB53, Ranbir Basmati & times; IRBB60, Basmati 564 & times; IRBB57, and Basmati 370 & times; IRBB56 were observed to be the most responsive genotypes for haploid regeneration. An average of 76.34% DH induction frequencies were obtained in colchicine (0.1%) treatment, while 41.56% were spontaneously induced DHs. Consequently, using anther culture to develop DH lines is a promising approach for genomic resources and elite varieties in a shorter breeding period.
Nematomorphs are one of the least studied groups of organisms with scarce information available on their ecology and distribution. Here, we provide the record of Paragordius, a nematomorph genus of the Indian Himalayan region. Based on the present observations and past evidence, we elucidate the manipulative strategies adapted by these parasites with the orthopteran hosts of headwater ecosystems. Their role in enhancing the land-river continuum by providing cross-ecosystem food subsidies through the affected orthopterans makes them potential nutrient vectors. Thus, we provide our perspective on interfaces between the newly recorded parasites and orthopteran hosts as 'keystone interactions' of headwater ecosystems. Studies like these provide an opportunity to rethink the typical food web concept, emphasising the essential incorporation of parasites as integral components in food web dynamics.
The present study presents a comparative analysis of 76 Moraceae chloroplast genomes, including a chloroplast genome for Streblus asper and an independent assembly for Ficus hispida. We identified notable structural variations, particularly significant gene truncations in ndhD and ycf 1 in S. asper. Our 76-species phylogenetic analysis robustly places S. asper in a clade with Trophis caucana and Antiaris toxicaria, resolving a key taxonomic uncertainty. The placement of F. hispida within the Ficus clade is also confirmed. These findings provide crucial genomic resources, clarify evolutionary relationships, and deepen our understanding of genomic evolution in Moraceae.
The present study reports the occurrence of the marine tube-dwelling diatom Nitzschia martiana in Indian waters, specifically within the mangrove habitats of South of diatoms encased in mucilaginous tubes, measuring 4-10 mm in length and 40-45 & micro;m in width. Individual cells display linear valves with rounded apices and chloroplasts arranged diagonally, evenly distributed across the cell (16-18 per cell). Cohabitation with other Nitzschia species was also observed. The study provides a novel record of N. martiana from Indian coastal waters, thereby contributing to the understanding of diatom diversity in mangrove ecosystems.
Long-term sustainability is the concern of today's agriculture. A field experiment was conducted in western Uttar Pradesh during the rabi season of 2021-22 to evaluate the combined effect of different combinations of synthetic (nitrogen, phosphorus and potassium (NPK) and ZnSO4 ) and organic fertilisers (vermicompost, Azotobacter + phosphorus solubilising bacteria (PSB)) on soil physico-chemical properties under a rice-wheat cropping system. The experiment consisted of ten treatment combinations with variable sources of nutrients and biofertilisers such as T-1 (Control), T-2 (75% Recommended dose of fertilisers (RDF) NPK), T3 (100% (RDF-150:75:60 kg ha(-1)) NPK), T-4(75% (RDF)NPK + ZnSO4 (25 kg/ha.) T5 (75% (RDF) NPK + Vermicompost @ 2.5 t/ha), T-6 (75% (RDF) NPK + ZnSO4 + Vermicompost @ 2.5 t/ha), T-7(75% (RDF) NPK + Azotobacter+PSB), T-8(75% (RDF) NPK +ZnSO4 +Vermicompost @ 2.5 t/ha+Azotobacter+PSB), T-9(100% (RDF) NPK +ZnSO4 ) and T10(100% (RDF) NPK +Azotobacter+PSB). It was observed that combined application of organic and synthetic fertiliser resulted in a positive influx of macro-and micronutrients by increasing electrical conductivity, soil aggregation, organic carbon content, available nitrogen, phosphorus, potassium and zinc of soil. The lowest physico-chemical properties were recorded in the control except soil pH and soil bulk density; the highest were recorded due to combined application of synthetic fertiliser along with organic manure. The highest organic carbon (0.51%), available N (186.0 kg ha(-1)), P (21.4 kg ha(-1)), K (131.1 kg ha(-1)), Zn (0.85 mg kg-1) were recorded under the treatment of 75% (RDF) NPK+ZnSO4 +Vermicompost @ 2.5 t ha(-1)+ Azotobacter + PSB, followed by 100% (RDF) NPK + ZnSO4 while bulk density (1.52 g cc(-1)) and particle density (2.65 g cc(-1)) were found highest in the control. In this way the results clearly suggested that integrated use of balanced synthetic fertilisers in combination with organic manure in a rice-wheat cropping system improves soil physico-chemical properties and thereby has the potential to enhance soil sustainability.
Wildlife conservation efforts often overlook the potential impact of parasites on wildlife populations. The emergence of novel diseases has become a growing concern in recent years, particularly at the interface between livestock and wildlife. Assessing parasitic prevalence through faecal surveys is crucial in livestock and wildlife management. The present study investigates the prevalence of gastrointestinal parasites in co-grazing cattle near Pobitora Wildlife Sanctuary in Assam. We collected 122 faecal samples between March 2018 and May 2018 from cattle of different age groups and sexes and analysed them using flotation and sedimentation techniques for the presence of parasites. We found that 72.95% of the tested samples were positive for gastrointestinal parasites. The identified parasites included eight different helminth species and one coccidian species. Among them, Amphistome sp. was the most prevalent (54.09%), followed by Eimeria sp. (9.83%) and Fasciola gigantica (7.37%). The present study provides critical information and has crucial conservation implications as Pobitora Wildlife Sanctuary houses other mega-herbivores, including greater one-horned rhinoceros and water buffalo.
Glioma represents a frequent intracranial malignancy characterised by a dismal clinical outcome. Cuproptosis, a recently identified type of cellular demise, has garnered significant interest within the oncological community. The specific functions of cuproptosisassociated genes in glioma remain undefined. Herein, we utilised Cox regression modelling to detect 7 prognostic long non-coding RNAs (lncRNAs) and developed a risk framework based upon those molecules. Patients were stratified into high-risk and low-risk groups based upon the median risk score. Regardless of personal age, gender, tumour grade, or O6-methylguanine-DNA methyltransferase methylation state, the survival prospects of the high-risk cohort were considerably poorer compared to those of the low-risk cohort. Cox proportional hazards modelling verified that this model functions as an independent prognostic tool for glioma patients. Receiver operating characteristic curve evaluation indicated that this system maintains superior accuracy for predicting survival among the Cancer Genome Atlas participants. Functional enrichment analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes was performed to determine the biological roles of differentially expressed genes. Furthermore, it was noted that the cuproptosisrelated lncRNAs risk signature correlates with tumour mutation burden and the immune landscape. To summarise, we developed a prognostic risk model centred around cuproptosis-associated lncRNAs, which demonstrates solid capacity for predictive assessment.
The present study presents a novel hybrid framework for the prediction and severity classification of diabetic retinopathy (DR) and glaucoma (GL) using synthesised fundus images. DR and GL are among the leading causes of irreversible blindness worldwide, often coexisting in ageing populations and complicating diagnosis. While DR is characterised by retinal vascular damage, GL involves optic nerve deterioration-both requiring distinct yet overlapping diagnostic features. A StarGAN v2-based generative model was employed to create hybrid retinal images containing features of both DR and GL, enhancing the diversity and complexity of the dataset. Red, green, and blue channel separation was performed to highlight disease-specific cues, with a denoising convolutional neural network applied to the green channel for enhanced vessel and lesion visibility. Two deep learning models were explored: a Hippopotamus Optimized Vision Transformer (HOViT) that captures global dependencies and a convolutional neural network (CNN) architecture augmented with a convolutional block attention module (CBAM) for focused lesion-level feature learning. The CNN-CBAM model was further optimised using Optuna's Bayesian optimisation framework, improving classification accuracy. Severity scores for DR and GL were estimated using a dual-output SoftMax layer, supported by gradient-weighted class activation mapping-based interpretability. Fusing the spatial and pathological features of both diseases into a unified model enabled simultaneous, interpretable multi-disease prediction. Experimental results demonstrate high accuracy, robust generalisation, and explainable predictions, offering a powerful tool for assisting in the clinical diagnosis of co-existing retinal diseases.
