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With climate change projections indicating an increase in the frequency of extreme heat events and irregular rainfall patterns globally, the threat to global food security looms large. Terminal heat stress, which occurs during the critical reproductive stage, significantly limits lentil productivity. Therefore, there is an urgent need to improve lentil's resilience to heat stress to sustain production. However, studies identifying heat-tolerant sources in lentils are limited. To address these issues, we assessed 158 lentil genotypes under normal and late-sown conditions over two consecutive seasons. We employed eleven heat stress indices to identify lines tolerant to heat stress. All genotypes exhibited a decrease in average grain yield when subjected to stress conditions as compared to non-stress conditions, indicating the impact of heat stress on crop yield. Correlation analysis showed significant positive correlation between yield in normal and late-sown conditions and the following heat stress indices: STI, MP, MRP, YI, GMP, and HM. In contrast, TOL, SSPI, and PYR showed negative associations with yield in late-sown conditions. Based on these indices, we identified the genotypes P13143, P13130, and P13135 as high-yielding in both stress and non-stress conditions. Cluster analysis and biplot display in PCA also confirmed that genotypes P13143, P13130, and P13135 exhibited suitability and high yield potential in both environments. These genotypes can be utilized as donors in future breeding programs to introduce genetic variations for improving heat stress tolerance in lentil., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

The research aims to explore the vulnerability of Bangladesh to drought by considering a comprehensive set of twenty-four factors, classified into four major categories: meteorological, hydrological, agricultural, and socioeconomic vulnerability. To achieve this, the study utilized a knowledge-based multi-criteria method known as the Analytic Hierarchy Process (AHP) to delineate drought vulnerability zones across the country. Weight estimation was accomplished by creating pairwise comparison matrices for factors and different types of droughts, drawing on relevant literature, field experience, and expert opinions. Additionally, online-based interviews and group discussions were conducted with 30 national and foreign professionals, researchers, and academics specializing in drought-related issues in Bangladesh. Results from overall drought vulnerability map shows that the eastern hills region displays a notably high vulnerability rate of 56.85% and an extreme low vulnerability rate of 0.03%. The north central region shows substantial vulnerability at high levels (35.85%), while the north east exhibits a significant proportion (41.68%) classified as low vulnerability. The north west region stands out with a vulnerability rate of 40.39%, emphasizing its importance for drought management strategies. The River and Estuary region displays a modest vulnerability percentage (38.44%), suggesting a balanced susceptibility distribution. The south central and south east regions show significant vulnerabilities (18.99% and 39.60%, respectively), while the south west region exhibits notable vulnerability of 41.06%. The resulting model achieved an acceptable level of performance, as indicated by an area under the curve value of 0.819. Policymakers and administrators equipped with a comprehensive vulnerability map can utilize it to develop and implement effective drought mitigation strategies, thereby minimizing the losses associated with drought., (© 2024. The Author(s).)

The aim of the study was to estimate future groundwater potential zones based on machine learning algorithms and climate change scenarios. Fourteen parameters (i.e., curvature, drainage density, slope, roughness, rainfall, temperature, relative humidity, lineament density, land use and land cover, general soil types, geology, geomorphology, topographic position index (TPI), topographic wetness index (TWI)) were used in developing machine learning algorithms. Three machine learning algorithms (i.e., artificial neural network (ANN), logistic model tree (LMT), and logistic regression (LR)) were applied to identify groundwater potential zones. The best-fit model was selected based on the ROC curve. Representative concentration pathways (RCP) of 2.5, 4.5, 6.0, and 8.5 climate scenarios of precipitation were used for modeling future climate change. Finally, future groundwater potential zones were identified for 2025, 2030, 2035, and 2040 based on the best machine learning model and future RCP models. According to findings, ANN shows better accuracy than the other two models (AUC: 0.875). The ANN model predicted that 23.10 percent of the land was in very high groundwater potential zones, whereas 33.50 percent was in extremely high groundwater potential zones. The study forecasts precipitation values under different climate change scenarios (RCP2.6, RCP4.5, RCP6, and RCP8.5) for 2025, 2030, 2035, and 2040 using an ANN model and shows spatial distribution maps for each scenario. Finally, sixteen scenarios were generated for future groundwater potential zones. Government officials may utilize the study's results to inform evidence-based choices on water management and planning at the national level., (© 2024. The Author(s).)

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for Zr 67 Ni 33 and Zr 52 Ti 6 Al 10 Cu 18 Ni 14 glasses. Our strategy engages diverse (× 7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way., (© 2024. The Author(s).)

Soil salinity is a pressing issue for sustainable food security in coastal regions. However, the coupling of machine learning and remote sensing was seldom employed for soil salinity mapping in the coastal areas of Bangladesh. The research aims to estimate the soil salinity level in a southwestern coastal region of Bangladesh. Using the Landsat OLI images, 13 soil salinity indicators were calculated, and 241 samples of soil salinity data were collected from a secondary source. This study applied three distinct machine learning models (namely, random forest, bagging with random forest, and artificial neural network) to estimate soil salinity. The best model was subsequently used to categorize soil salinity zones into five distinct groups. According to the findings, the artificial neural network model has the highest area under the curve (0.921), indicating that it has the most potential to predict and detect soil salinity zones. The high soil salinity zone covers an area of 977.94 km 2 or roughly 413.51% of the total study area. According to additional data, a moderate soil salinity zone (686.92 km 2 ) covers 30.56% of Satkhira, while a low soil salinity zone (582.73 km 2 ) covers 25.93% of the area. Since increased soil salinity adversely affects human health, agricultural production, etc., the study's findings will be an effective tool for policymakers in integrated coastal zone management in the southwestern coastal area of Bangladesh., (© 2023. Springer Nature Limited.)

We report a new type of fossil margin galls arranged in a linear series on dicot leaf impressions from the latest Neogene (Pliocene) sediments of the Chotanagpur Plateau, Jharkhand, eastern India. We collected ca. 1500 impression and compression leaf fossils, of which 1080 samples bear arthropod damage referable to 37 different damage types (DT) in the 'Guide to Insect (and Other) Damage Types in Compressed Plant Fossils'. A few leaf samples identified as Ipomoea L. (Convolvulaceae) have specific margin galls that do not match any galling DT previously described. This type of galling is characterized by small, linearly arranged, irregular, sessile, sub-globose, solitary, indehiscent, solid pouch-galls with irregular ostioles. The probable damage inducers of the present galling of the foliar margin might be members of Eriophyidae (Acari). The new type of gall suggests that marginal gall-inducing mites on leaves of Ipomoea did not change their host preference at the genus level since the Pliocene. The development of marginal leaf galling in Ipomoea is linked to extrafloral nectaries that do not offer protection against arthropod galling but indirectly protect the plant against herbivory from large mammals., (© 2023. The Author(s).)

Chromium (Cr) accumulation in crops reduces yield. Here, we grew two chickpea cultivars, Pusa 2085 (Cr-tolerant) and Pusa Green 112 (Cr-sensitive), in hydroponic and pot conditions under different Cr treatments: 0 and 120 µM Cr and 120 µM Cr + 100 mM glycine betaine (GB). For plants grown in the hydroponic media, we evaluated root morphological attributes and plasma membrane integrity via Evans blue uptake. We also estimated H + -ATPase activity in the roots and leaves of both cultivars. Plants in pots under conditions similar to those of the hydroponic setup were used to measure growth traits, oxidative stress, chlorophyll contents, enzymatic activities, proline levels, and nutrient elements at the seedling stage. Traits such as Cr uptake in different plant parts after 42 days and grain yield after 140 days of growth were also evaluated. In both cultivars, plant growth traits, chlorophyll contents, enzymatic activities, nutrient contents, and grain yield were significantly reduced under Cr stress, whereas oxidative stress and proline levels were increased compared to the control levels. Further, Cr uptake was remarkably decreased in the roots and leaves of Cr-tolerant than in Cr-sensitive cultivars. Application of GB led to improved root growth and morpho-physiological attributes and reduced oxidative stress along with reduced loss in plasma membrane integrity and subsequently increase in H + -ATPase activity. An increment in these parameters shows that the exogenous application of GB improves the Cr stress tolerance in chickpea plants., (© 2022. The Author(s).)

Alpha-synuclein (aSyn) has implications in pathological protein aggregations in neurodegeneration. Matrix metalloproteases (MMPs) are broad-spectrum proteases and cleave aSyn, leading to aggregation. Previous reports showed that allosteric communications between the two domains of MMP1 on collagen fibril and fibrin depend on substrates, activity, and ligands. This paper reports quantification of allostery using single molecule measurements of MMP1 dynamics on aSyn-induced aggregates by calculating Forster Resonance Energy Transfer (FRET) between two dyes attached to the catalytic and hemopexin domains of MMP1. The two domains of MMP1 prefer open conformations that are inhibited by a single point mutation E219Q of MMP1 and tetracycline, an MMP inhibitor. A two-state Poisson process describes the interdomain dynamics, where the two states and kinetic rates of interconversion between them are obtained from histograms and autocorrelations of FRET values. Since a crystal structure of aSyn-bound MMP1 is unavailable, binding poses were predicted by molecular docking of MMP1 with aSyn using ClusPro. MMP1 dynamics were simulated using predicted binding poses and compared with the experimental interdomain dynamics to identify an appropriate pose. The selected aSyn-MMP1 binding pose near aSyn residue K45 was simulated and analyzed to define conformational changes at the catalytic site. Allosteric residues in aSyn-bound MMP1 exhibiting strong correlations with the catalytic motif residues were compared with allosteric residues in free MMP1, and aSyn-specific residues were identified. The allosteric residues in aSyn-bound MMP1 are K281, T283, G292, G327, L328, E329, R337, F343, G345, N346, Y348, G353, Q354, D363, Y365, S366, S367, F368, P371, R372, V374, K375, A379, F391, A394, R399, M414, F419, V426, and C466. Shannon entropy was defined to quantify MMP1 dynamics. Virtual screening was performed against a site on selected aSyn-MMP1 binding poses, which showed that lead molecules differ between free MMP1 and substrate-bound MMP1. Also, identifying aSyn-specific allosteric residues in MMP1 enabled further selection of lead molecules. In other words, virtual screening needs to take substrates into account for potential substrate-specific control of MMP1 activity in the future. Molecular understanding of interactions between MMP1 and aSyn-induced aggregates may open up the possibility of degrading aggregates by targeting MMPs., (© 2022. The Author(s).)

The roles of protein conformational dynamics and allostery in function are well-known. However, the roles that interdomain dynamics have in function are not entirely understood. We used matrix metalloprotease-1 (MMP1) as a model system to study the relationship between interdomain dynamics and activity because MMP1 has diverse substrates. Here we focus on fibrin, the primary component of a blood clot. Water-soluble fibrinogen, following cleavage by thrombin, self-polymerize to form water-insoluble fibrin. We studied the interdomain dynamics of MMP1 on fibrin without crosslinks using single-molecule Forster Resonance Energy Transfer (smFRET). We observed that the distance between the catalytic and hemopexin domains of MMP1 increases or decreases as the MMP1 activity increases or decreases, respectively. We modulated the activity using (1) an active site mutant (E219Q) of MMP1, (2) MMP9, another member of the MMP family that increases the activity of MMP1, and (3) tetracycline, an inhibitor of MMP1. We fitted the histograms of smFRET values to a sum of two Gaussians and the autocorrelations to an exponential and power law. We modeled the dynamics as a two-state Poisson process and calculated the kinetic rates from the histograms and autocorrelations. Activity-dependent interdomain dynamics may enable allosteric control of the MMP1 function.

Flax (Linum usitatissimum) is a cool season crop commercially cultivated for seed oil and stem fibre production. A comprehensive characterization of the heat shock factor (HSF) candidate genes in flax can accelerate genetic improvement and adaptive breeding for high temperature stress tolerance. We report the genome-wide identification of 34 putative HSF genes from the flax genome, which we mapped on 14 of the 15 chromosomes. Through comparative homology analysis, we classified these genes into three broad groups, and sub-groups. The arrangement of HSF-specific protein motifs, DNA-binding domain (DBD) and hydrophobic heptad repeat (HR-A/B), and exon-intron boundaries substantiated the phylogenetic separation of these genes. Orthologous relationships and evolutionary analysis revealed that the co-evolution of the LusHSF genes was due to recent genome duplication events. Digital and RT-qPCR analyses provided significant evidence of the differential expression of the LusHSF genes in various tissues, at various developmental stages, and in response to high-temperature stress. The co-localization of diverse cis-acting elements in the promoters of the LusHSF genes further emphasized their regulatory roles in the abiotic stress response. We further confirmed DNA-binding sites on the LusHSF proteins and designed guide RNA sequences for gene editing with minimal off-target effects. These results will hasten functional investigations of LusHSFs or assist in devising genome engineering strategies to develop high-temperature stress tolerant flax cultivars.

Lignin, a cross-linked macromolecule of hydrophobic aromatic structure, provides additional rigidity to a plant cell wall. Although it is an integral part of the plant cell, presence of lignin considerably reduces the quality of the fiber of fiber-yielding plants. Decreasing lignin in such plants holds significant commercial and environmental potential. This study aimed at reducing the lignin content in jute-a fiber crop, by introducing hpRNA-based vectors for downregulation of two monolignoid biosynthetic genes- cinnamate 4-hydroxylase (C4H) and caffeic acid O-methyltransferase (COMT). Transgenic generations, analyzed through Southern, RT-PCR and northern assays showed downregulation of the selected genes. Transgenic lines exhibited reduced level of gene expression with ~ 16-25% reduction in acid insoluble lignin for the whole stem and ~13-14% reduction in fiber lignin content compared to the control lines. Among the two transgenic plant types one exhibited an increase in cellulose content and concomitant improvement of glucose release. Composition of the lignin building blocks was found to alter and this alteration resulted in a pattern, different from other plants where the same genes were manipulated. It is expected that successful COMT-hpRNA and C4H-hpRNA transgenesis in jute will have far-reaching commercial implications leading to product diversification and value addition.