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Spatial disparities in socio-economic conditions are increasingly recognized as a significant challenge for policymakers. Even minor discrepancies can exacerbate societal inequalities, posing risks to both economic and social stability. In terms of literature, there is hardly any study that includes spatial disparity in Meghalaya with respect to socio-economic aspects. Thereby, to address this lacuna in previous studies, this research focuses on the pronounced spatial disparities in the state of Meghalaya, using Principal Component Analysis (PCA), Moran’s I, Local Indicators of Spatial Association (LISA) and Prin score, through which it aims to identify clusters, spatial autocorrelation and rank districts based on socio-economic indicators and identify underlying factors contributing to these disparities. Additionally, Z-scores have been employed to assess the severity of backwardness among different districts. Spatial analysis presents the factors in PC2 (i.e. educational) are clustered at local level (LISA = high-high, East Khasi Hills, < 0.01; Ri-Bhoi, < 0.05) with moderate spatial autocorrelation (Moran’s I = 0.299, p-value = 0.154). Results also portray notable spatial disparity exists in Meghalaya, with districts like West Garo Hills (1st rank, Q1) and East Khasi Hills (2nd rank, Q1) are 13.8 and 14 times more developed in terms of cropped area and number of industries than East Jaintia Hills (11th rank, Q4) and South West Khasi Hills (10th rank, Q4), respectively, which remains less developed, reflecting Matthew's effect and core-periphery pattern. The paper concludes by proposing balanced regional development through potential mitigation strategies, including enhanced community participation, expansion of welfare schemes (e.g., Meghalaya State Rural Livelihood Mission and Border Area Development Programme) in underdeveloped districts and equitable resource allocation.
Marine ecosystems represent a largely untapped reservoir of bioactive compounds with significant pharmacological potential. This study aimed to evaluate the therapeutic properties of ethanol extracts from four marine species: Padina australis, Spatoglossum asperum, Holothuria (Halodeima) atra, and Hypnea valentiae. Phytochemical screening, along with a comprehensive series of in vitro, in vivo, and in silico assays, was performed to evaluate the extracts' pharmacological activities, including antioxidant potential (2,2-diphenyl-1-picrylhydrazyl assay), anti-inflammatory effect (carrageenan-induced paw edema method), analgesic activity (acetic acid-induced writhing and tail immersion tests), and anti-arthritic efficacy (protein denaturation assay). The extracts were found to be rich in flavonoids, tannins, alkaloids, saponins, glycosides, and phenolic compounds, which may underlie the observed bioactivities. In the acetic acid-induced writhing test, Hypnea valentiae at 400 mg/kg exhibited the highest peripheral analgesic activity, producing 82.51% inhibition of writhing (p < 0.001). In the tail immersion assay, Padina australis at doses of 200 and 400 mg/kg showed significant central analgesic effects, as evidenced by increased latency time and percentage of maximum possible effect (MPE). In the carrageenan-induced paw edema model, several treatment groups, including Padina australis, Hypnea valentiae, Spatoglossum asperum, and Holothuria atra, at both tested doses showed marked suppression of inflammation, with some groups achieving complete inhibition (100%; p < 0.001) at 120 min. The ethanol extract of Holothuria atra exhibited the strongest antioxidant and anti-arthritic activities, with an IC50 value of 88.39 µg/mL in the DPPH assay and 81.35% inhibition of protein denaturation. Additionally, the compounds derived from the four marine species exhibited significant binding affinity to the selected target receptors, thereby validating the experimental findings. The marine species studied possess multifaceted pharmacological properties, supporting their potential as natural sources for developing therapeutic agents supporting the blue economy. Further studies are recommended to isolate active compounds and elucidate underlying mechanisms to support future drug development efforts.
Mangrove ecosystems along the Indian Ocean coast show great biodiversity, adapting to harsh environmental conditions of high salinity and higher organic matter, and they are a host for a range of microbial communities with special features that produce unique secondary metabolites. Of this, mangrove-associated endophytic fungi, the second largest ecological group of marine fungi, show the greater potential, being a diverse pool for discovering novel bio-actives with pharmacological and biotechnological interest. This review summarizes the research findings on structural diversity and the associated pharmacological activities of secondary metabolites produced by mangrove-associated fungi along the Indian Ocean coast reported over the period of 2002–2025, based on the literature retrieved from Google Scholar. The total of 302 secondary metabolites is presented mainly from classes of polyketides (208), alkaloids (34), and terpenoids (60). Interestingly, 164 compounds were identified, as first reported in those publications. These compounds have been reported to show diverse biological activities, and the most prominent activities are cytotoxic, antibacterial, antifungal, antioxidant, enzyme inhibitory, and anti-inflammatory effects. The structural novelty and pharmacological activities of these metabolites highlight the importance of mangrove fungi as promising sources for new drug discovery and advancing industrial biotechnology. Therefore, this review highlights the insight into the possible application of these chemical compounds in the future drug industry, as well as in biotechnology for advancing human well-being. Furthermore, though significant progress has been made in exploring the fungi community from mangroves of the African and Middle Eastern coasts, the Indian coast mangrove fungi are yet to be explored more for novel discoveries.
Two mononuclear Cu(II) complexes of ONO donor 3,5-dibromosalicylaldehyde semicarbazone (H2dbsc) were synthesized and characterized. Tridentate nature of the ligand 3,5-dibromosalicylaldehyde semicarbazone to Cu (II) was realized from different physiochemical techniques. In both complexes, phenolic hydrogen of the semicarbazone deprotonates and is coordinated to copper in the phenolate form. The azomethine nitrogen and the amido oxygen serves the other two coordination sites, with chlorido/bromido atom occupies the fourth coordination position. Both the Cu(II) complexes, [Cu(Hdbsc)Cl]center dot H2O (1) and [Cu(Hdbsc)Br]center dot H2O (2) are crystallized and their structures are determined by SCXRD. A molecule of water is present in the lattice in both complexes. Extensive hydrogen bonding, C-Br center dot center dot center dot pi and pi center dot center dot center dot pi interactions make the complexes more rigid in crystal lattice, and they generate supramolecular network. IR spectra indicate tridentate behavior of the semicarbazone in copper(II) complexes. EPR spectra of both complexes in frozen DMF solution at 77 K indicate axial geometry with metalligand bonds largely covalent in nature. The in vitro cytotoxicity study of the synthesized Cu(II) complexes 1 and 2 was performed on HepG2 and HeLa cells using CCK-8 assay. It is found that metal complexation increases the cytotoxicity against HeLa cells.
Addressing health inequalities requires detailed insights into local population behaviors beyond national averages. This study applies a multilevel regression with post-stratification (MRP) framework to assess chlamydia screening rates among young adults across England’s local authorities. By integrating individual-level demographic and behavioral data from the Natsal-3 survey with area-specific census and surveillance datasets, the model adjusts for socio-demographic heterogeneity and identifies regions performing above or below expectations. Bayesian hierarchical logistic regression was used to estimate expected screening rates, with significant variation attributed to factors such as age, gender, ethnicity, and student status. The analysis reveals that while demographic composition explains much of the variation, notable outliers suggest opportunities for targeted intervention.
