BackgroundNatriuretic peptides (NPs) are peptide hormones that exert their biological actions by binding to three types of cell surface natriuretic peptide receptors (NPRs). The receptor NPR-B binding C-type natriuretic peptide (CNP) acts locally as a paracrine and/or autocrine regulator in a wide variety of tissues. Mutations in the gene NPR2 have been shown to cause acromesomelic dysplasia-type Maroteaux (AMDM), an autosomal recessive skeletal disproportionate dwarfism disorder in humans.MethodsIn the study, presented here, genotyping of six consanguineous families of Pakistani origin with AMDM was carried out using polymorphic microsatellite markers, which are closely linked to the gene NPR2 on chromosome 9p21-p12. To screen for mutations in the gene NPR2, all of its coding exons and splice junction sites were PCR amplified from genomic DNA of affected and unaffected individuals of the families and sequenced.ResultsSequence analysis of the gene NPR2 identified a novel missence mutation (p.T907M) in five families, and a splice donor site mutation c.2986 + 2 T > G in the other family.ConclusionWe have described two novel mutations in the gene NPR2. The presence of the same mutation (p.T907M) and haplotype in five families (A, B, C, D, E) is suggestive of a founder effect.

Land use–land cover (LULC) alteration is primarily associated with land degradation, especially in recent decades, and has resulted in various harmful changes in the landscape. The normalized difference vegetation index (NDVI) has the prospective capacity to classify the vegetative characteristics of many ecological areas and has proven itself useful as a remote sensing (RS) tool in recording vegetative phenological aspects. Likewise, the normalized difference built-up index (NDBI) is used for quoting built-up areas. The current research objectives include identification of LULC, NDVI, and NDBI changes in Jhelum District, Punjab, Pakistan, during the last 30 years (1990–2020). This study targeted five major LULC classes: water channels, built-up area, barren land, forest, and cultivated land. Satellite imagery classification tools were used to identify LULC changes in Jhelum District, northern Punjab, Pakistan. The perception data about the environmental variations as conveyed by the 500 participants (mainly farmers) were also recorded and analyzed. The results depict that the majority of farmers (54%) believe in the appearance of more drastic changes such as less rainfall, drought, and decreased water availability for irrigation during 2020 compared to 30 years prior. Overall accuracy assessment of imagery classification was 83.2% and 88.8% for 1990, 88.1% and 85.7% for 2000, 86.5% and 86.7% for 2010, and 85.6% and 87.3% for 2020. The NDVI for Jhelum District was the highest in 1990 at +0.86 and the lowest in 2020 at +0.32; similarly, NDBI values were the highest in 2020 at +0.72 and the lowest in 1990 at −0.36. LULC change showed a clear association with temperature, NDBI, and NDVI in the study area. At the same time, variations in the land area of barren soil, vegetation, and built-up from 1990 to 2020 were quite prominent, possibly resulting in temperature increases, reduction in water for irrigation, and changing rainfall patterns. Farmers were found to be quite responsive to such climatic variations, diverting to framing possible mitigation approaches, but they need government assistance. The findings of this study, especially the causes and impacts of rapid LULC variations in the study area, need immediate attention from related government departments and policy makers.

The purpose of this study was to investigate the taxonomic diversity, richness, and distribution patterns of Poaceae in relation to abiotic factors in the Jhelum district of the Pakistan Himalayas. We used a random sampling technique from 80 grids within 240 sites with a rich diversity of wild grasses and 720 quadrates in triplets from each site across the Jhelum district between 2019 and 2021 to collect data on grass species and the associated environmental factors and conditions. After evaluating the important value index for each plant taxa and for the environmental data, we analyzed the data using ordination and cluster analysis techniques. Fifty-two Poaceae taxa from twenty-nine genera were recorded within the study area. From a total of 52 recorded Poaceae species, 45 were native and 7 were invasive species. The life form (biological) showed the dominancy of 27 therophyte species, followed by 24 hemicryptophyte species, and 1 geophyte species. Microphyll had the leading leaf size spectra (27 species), followed by nanophyll (12 species), macrophyll (10 species), and leptophyll (3 species). The trend of the life cycle was the maximum (27 spp.) during the monsoon season, followed by spring (11 spp.), winter (8 spp.), and summer (6 spp.). The leading genera were Setaria with 9.61% of the species, followed by Panicum, Cenchrus, and Brachiaria with 7.69% of the species. Aristida and Echinochloa made up 5.76% of the species while Chrysopogon, Digitaria, Eragrostis, Pennisetum, and Poa made up 3.84% of the species. Other genera recorded single species. The leaf size spectra of grasses were dominated by microphylls (50%) followed by nanophylls (23.07%), macrophylls (19.23%), and leptophylls (7.69%). On the basis of the importance value index, the most dominant species was Cynodon dactylon (68), followed by Dichanthium annulatum (58), Brachiaria ramose (38), Dactyloctenium aegyptium (37), Eleusine indica (35), Saccharum bengalense (33), and Cenchrus biflorus (28). Two-way cluster analyses classified the grasses into three plant community associations based on the indicator plant species. Soil parameters as subsamples were tested for moisture, pH, EC, OM, macronutrients (CaCO3, N, P, and K), and saturation while the ordination analysis revealed that they had a significant (p ≤ 0.002) effect on vegetation associations. Overall, this study contributes to a better understanding of the influence of environmental factors on the composition and associations of grass species and the development of scientifically informed management solutions for the ecological restoration of degraded habitats in this Himalayan region.

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