Endometritis is the inflammatory response of the endometrial lining of the uterus and is associated with low conception rates, early embryonic mortality, and prolonged inter-calving intervals, and thus poses huge economic losses to the dairy industry worldwide. Ginsenoside Rb1 (GnRb1) is a natural compound obtained from the roots of Panax ginseng, having several pharmacological and biological properties. However, the anti-inflammatory properties of GnRb1 in lipopolysaccharide (LPS)-challenged endometritis through the TLR4-mediated NF-κB signaling pathway has not yet been researched. This study was planned to evaluate the mechanisms of how GnRb1 rescues LPS-induced endometritis. In the present research, histopathological findings revealed that GnRb1 ameliorated LPS-triggered uterine injury. The ELISA and RT-qPCR assay findings indicated that GnRb1 suppressed the expression level of pro-inflammatory molecules (TNF-α, IL-1β and IL-6) and boosted the level of anti-inflammatory (IL-10) cytokine. Furthermore, the molecular study suggested that GnRb1 attenuated TLR4-mediated NF-κB signaling. The results demonstrated the therapeutic efficacy of GnRb1 in the mouse model of LPS-triggered endometritis via the inhibition of the TLR4-associated NF-κB pathway. Taken together, this study provides a baseline for the protective effect of GnRb1 to treat endometritis in both humans and animals.
Decompressive craniectomy is a life-saving procedure used to manage severe traumatic brain injury (TBI). While it effectively reduces mortality, the procedure is associated with multiple postoperative complications, which may impact patient recovery and outcomes. Understanding the frequency and nature of these complications is critical for improving patient care. Objective: The objective of this study was to determine the frequency of postoperative complications in patients who underwent decompressive craniectomy for traumatic brain injury at a tertiary care hospital in Karachi. Methods: This descriptive cross-sectional study was conducted at SMBB Trauma Centre, Civil Hospital Karachi, from February 20, 2020, to August 20, 2020. A total of 98 patients who underwent decompressive craniectomy for TBI were included. Data were collected on demographic variables, clinical parameters, and postoperative complications. The mean age, length of hospital stay, duration of injury, and surgery duration were analyzed. Statistical analysis was performed using descriptive statistics. Results: The mean age of the patients was 45.14 ± 9.49 years, with a mean hospital stay of 10.72 ± 6.24 days, mean duration of injury of 8.41 ± 4.69 hours, and mean surgery duration of 4.87 ± 2.14 hours. Of the 98 patients, 60 (61.2%) were male and 38 (38.8%) were female. The most common postoperative complication was subdural effusion, affecting 37 patients (37.76%), followed by contusion expansion in 19 patients (19.39%), external cerebral herniation in 16 patients (16.33%), syndrome of the trephined in 12 patients (12.24%), epilepsy in 7 patients (7.14%), and cerebrospinal fluid (CSF) leakage in 4 patients (4.08%). Conclusion: Decompressive craniectomy is an established treatment for reducing mortality in patients with traumatic brain injury. However, the procedure is associated with significant postoperative complications, such as subdural effusion and contusion expansion, which require timely identification and management. Despite its benefits, the risks associated with decompressive craniectomy necessitate careful postoperative monitoring to improve patient outcomes.
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.
Allometric equations were developed to estimate aboveground dry phytomass (AGDP) in some coastal herbaceous halophytic species of Karachi viz. Atriplex griffithii Moq. Cressa cretica L., Phragmites karka (Retz.) Trin ex Steud., Limonium stocksii (Boiss.) O. Ktze, and Urochondra setulosa (Trin.) C.E. Hubb. Best fit least square regression models were developed using height and crown diameter to estimate AGDP of individual plants. In case of P. karka, culm height, culm basal diameter or culm volume were employed to estimate phytomass of an individual culm. The crown diameter was generally better predictor of phytomass than height. The inclusion of parameter of height as an independent variable along with crown diameter could not improve the estimation of phytomass significantly except in case of P. karka where substantial improvement in estimation of culm mass was recorded (24.3%) when height was included along with culm diameter in a natural log-log model of multiple correlation and regression. Quadratic (curvilinear) relationships between phytomass and crown diameter were significant in all plants. The quadratic equations were more or less as equally statistically efficient as multiple regression models in estimating phytomass in Atriplex, Cressa and Limonium. Culm phytomass in Phragmites and AGDP in Urochondra setulosa were, however, better estimated by multiple regression models with natural log-log transformed variables.
Abstract
Double haploid (DH) technology ensures the production of complete homozygous wheat lines in a single year making the selection process efficient in plant breeding. This not only shortens the time period to release a variety, but dihaploids are also used for various aspects of genetic studies. Anther culture and wheat x maize hybridization are most commonly used methods for wheat double haploid production. However, recent studies indicate that wheat x maize hybridization is the most effective method for haploid production in wheat because of its higher efficacy, simplicity, less genotypic specificity, less somaclonal variation and less time consumption. Moreover, DH lines have applications in basic and applied research. DH lines are the ideal material for genetic studies. In this review paper, we have tried to explain the methodologies of DHs production in wheat and their comparison of both procedures in terms of their ease, efficiency and applicability. We have also summarized the possible application of DH lines in Plant Breeding.
To identify the genotypic effects of parents for wheat × maize crossing system, five F 1 wheat genotypes were crossed with five maize cultivars. The data for haploid seed and embryo production in each cross was recorded and analyzed. The data revealed that maize genotypes have significant variable effects on haploid wheat seed and embryo production. The line × tester analysis proved that wheat and maize genotypes along with their interactions, affect haploid seed and embryo production in wheat × maize crossing system. In this experiment a maize variety named Sadaf showed best performance on the basis of high GCA value as compared to others. It was also discovered that high seed production phenomenon could not be associated with high haploid embryo formation in a wheat × maize crossing system. It was concluded that maize genotypes having great potential for wheat haploid production should be identified and utilized in this system to improve its efficiency as in this study Sadaf is recommended for wheat × maize crossing system.
Double haploid (DH) breeding not only helps in accelerating conventional plant breeding programmes and make early release of cultivars with superior and desirable traits possible but it has greater utility in other research aspects of plant breeding, genetics and genetic engineering. DHs are important constituent of germplasm. These also helps in complementing back cross breeding by transferring genes of interest between wild relatives thus breaking genetic barriers. On the other hand unique complete homozygous nature of DHs, less time requirement to produce a large number of DHs, absence of heterozygosity, efficiency over conventional systems and absence of gametoclonal variation in DHs make them very valuable material for very important genetic and molecular studies. So, DHs are extensively used for genetic studies like studying inheritance of quantitative traits, Quantitative Trait Loci (QTL) mapping, Genomics, gene identification, whole genome mapping and production of stable transgenic plants. In this review, we briefly discuss utility of DHs in these genetic and molecular studies.
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