Search Results (45)

Background/Objectives: The primary goal of our research is to develop a process to prepare an aqueous dispersion of Cisplatin, an important anticancer drug, with increased solubility and storage stability. Method: In this context, we report the use of a customized RESS process for the synthesis of a novel, amber-colored and viscous aqueous cisplatin solution, an important anticancer drug, which we have denoted as “liquid” cisplatin. Results: Using specialized liquid cell in situ transmission electron microscopy (Liquid in situ TEM) and Raman spectroscopy, we demonstrated that “liquid” cisplatin comprises a bi-modal distribution of a highly solvated network of stable cisplatin nanoclusters in water and exhibited 27 times greater water solubility than standard cisplatin. More importantly, “liquid” cisplatin was stable at ambient conditions for over two years. Extensive analytical characterization of “liquid” cisplatin confirmed that it retained the original chemical identity of cisplatin. Cell viability and apoptosis studies on human lung adenocarcinoma A549 cells provided compelling evidence that “liquid” cisplatin demonstrated a more sustained anticancer effect compared to standard cisplatin. Conclusions: Aqueous cisplatin solubility was increased by 27X in the “liquid” cisplatin medium which retained its bio efficacy over a 2-year period. Our experimental results suggest the possibility of developing non-invasive and highly effective novel cisplatin drug-delivery platforms. Full article

This research presents an efficient and highly accurate cubic B-spline method (CBSM) for solving second-order linear boundary value problems (BVPs). The method achieves sixth-order convergence, supported by rigorous error analysis, ensuring rapid error reduction with mesh refinement. The effectiveness of the CBSM is validated through four numerical examples, showcasing its accuracy, reliability, and computational efficiency, making it well-suited for large-scale problems. A comparative analysis with existing methods confirms the superior performance of the CBSM, positioning it as a practical and powerful tool for solving second-order BVPs. Full article

This research examines the information management processes implemented in student dormitories and evaluates the enhancement of institutional efficiency based on student satisfaction. The study involved 150 students residing in dormitories across two universities, and data were collected through participant interviews. The findings indicate that while dormitory management is perceived as effective in some areas, there are significant opportunities for improvement in information management, communication, and service quality. Based on the student feedback, this article proposes several strategies to enhance dormitory management, including the adoption of digital platforms for better communication, regular maintenance schedules, and improved transparency in financial management. The challenges of implementing these measures, such as resource constraints and institutional resistance to change, are also discussed. These recommendations aim to improve student satisfaction and, consequently, institutional efficiency. Full article

A nontrivial conformal vector field $\omega$ on an m-dimensional connected Riemannian manifold $\left(M^m,g\right)$ has naturally associated with it the conformal potential $\theta$, a smooth function on $M^m$, and a skew-symmetric tensor T of type $(1,1)$ called the associated tensor. There is a third entity, namely the vector field $T\omega$, called the orthogonal reflection field, and in this article, we study the impact of the condition that commutator $\left[\omega ,T\omega \right]=0$; this condition that we refer to as the orthogonal reflection field is commutative. As a natural impact of this condition, we see the existence of a smooth function $\rho$ on $M^m$ such that $\nabla \theta =\rho \omega$; this function $\rho$ is called the proportionality function. First, we show that an m-dimensional compact and connected Riemannian manifold $\left(M^m,g\right)$ admits a nontrivial conformal vector field $\omega$ with a commuting orthogonal reflection $T\omega$ and constant proportionality function $\rho$ if and only if $\left(M^m,g\right)$ is isometric to the sphere $S^m\left(c\right)$ of constant curvature c. Secondly, we find three more characterizations of the sphere and two characterizations of a Euclidean space using these ideas. Finally, we provide a condition for a conformal vector field on a compact Riemannian manifold to be closed. Full article

The accurate diagnosis and identification of Leishmania species are crucial for the therapeutic selection and effective treatment of leishmaniasis. This study aims to develop and evaluate the use of high-resolution melting curve analysis (HRM)-PCR for Leishmania species identification causing visceral leishmaniasis (VL), post-kala-azar dermal leishmaniasis (PKDL) and cutaneous leishmaniasis (CL) in the Indian subcontinent. Two multi-copy targets (ITS-1 and 7SL-RNA genes) were selected, and an HRM-PCR assay was established using L. donovani, L. major, and L. tropica standard strain DNA. The assay was applied on 93 clinical samples with confirmed Leishmania infection, including VL (n = 30), PKDL (n = 50), and CL (n = 13) cases. The ITS-1 HRM-PCR assay detected as little as 0.01 pg of template DNA for L. major and up to 0.1 pg for L. donovani and L. tropica. The detection limit for the 7SL-RNA HRM-PCR was 1 pg for L. major and 10 pg for L. donovani and L. tropica. The ITS-1 HRM-PCR identified 68 out of 93 (73.11%) leishmaniasis cases, whereas 7SL-RNA HRM-PCR could only detect 18 out of 93 (19.35%) cases. A significant correlation was observed between the kDNA-based low Ct values and ITS-1 HRM-PCR positivity in the VL (p = 0.007), PKDL (p = 0.0002), and CL (p = 0.03) samples. The ITS-1 HRM-PCR assay could identify Leishmania spp. causing different clinical forms of leishmaniasis in the Indian subcontinent, providing rapid and accurate results that can guide clinical management and treatment decisions. Full article

The future of education relies on the integration of information technologies, emphasizing the importance of equity and inclusiveness for quality education. Teacher education programs are essential for fostering qualified educators for the future. Integrating AI in education is crucial to ensure inclusivity and comprehensive services for all. This study aims to evaluate student teachers’ perceptions of using AI in learning and teaching, and to provide suggestions for enhancing sustainable education through information technologies. A qualitative research design was adopted to gather perceptions and experiences from 240 student teachers who participated in a seminar on AI usage and completed self-reflection tasks. These student teachers, enrolled in various teaching methods and principal courses, contributed to the thematic analysis. The study reveals that AI should be carefully planned and incorporated into lesson plans to enhance personalized learning. Student teachers reported that AI supports and motivates the learning process, effectively transforming students’ needs and learning experiences. However, they also noted potential drawbacks, such as AI imposing restrictions on the teaching profession, replacing teachers, and producing biased results. The study suggests that capacity-building strategies for student teachers should be enriched across different courses to raise awareness about AI’s applications. Full article

Quinoa (Chenopodium quinoa Willd.) has gained worldwide recognition for its nutritional values, adaptability to diverse environments, and genetic diversity. This review explores the current understanding of quinoa tolerance to environmental stress, focusing on drought, salinity, heat, heavy metals, and UV-B radiation. Although drought and salinity have been extensively studied, other stress factors remain underexplored. The ever-increasing incidence of abiotic stress, exacerbated by unpredictable weather patterns and climate change, underscores the importance of understanding quinoa’s responses to these challenges. Global gene banks safeguard quinoa’s genetic diversity, supporting breeding efforts to develop stress-tolerant varieties. Recent advances in genomics and molecular tools offer promising opportunities to improve stress tolerance and increase the yield potential of quinoa. Transcriptomic studies have shed light on the responses of quinoa to drought and salinity, yet further studies are needed to elucidate its resilience to other abiotic stresses. Quinoa’s ability to thrive on poor soils and limited water resources makes it a sustainable option for land restoration and food security enterprises. In conclusion, quinoa is a versatile and robust crop with the potential to address food security challenges under environmental constraints. Full article

Air pollution poses a significant health hazard in urban areas across the globe, with India being one of the most affected countries. This paper presents environmental monitoring study conducted in Jodhpur, Rajasthan, India, to assess air quality in diverse urban environments. The study involved continuous indoor and outdoor air quality monitoring, focusing on particulate matter (PM_2.5) levels, bioaerosols, and associated meteorological parameters. Laser sensor-based low-cost air quality monitors were utilized to monitor air quality and Anderson 6-stage Cascade Impactor & Petri Dish methods for bioaerosol monitoring. The study revealed that PM_2.5 levels were consistently high throughout the year, highlighting the severity of air pollution in the region. Notably, indoor PM_2.5 levels were often higher than outdoor levels, challenging the common notion of staying indoors during peak pollution. The study explored the spatial and temporal diversity of air pollution across various land-use patterns within the city, emphasizing the need for tailored interventions in different urban areas. Additionally, bioaerosol assessments unveiled the presence of pathogenic organisms in indoor and outdoor environments, posing health risks to residents. These findings underscore the importance of addressing particulate matter and bioaerosols in air quality management strategies. Despite the study’s valuable insights, limitations, such as using low-cost air quality sensors and the need for long-term data collection, are acknowledged. Nevertheless, this research contributes to a better understanding of urban air quality dynamics and the importance of public awareness in mitigating the adverse effects of air pollution. In conclusion, this study underscores the urgent need for effective air quality management strategies in urban areas. The findings provide valuable insights for policymakers and researchers striving to address air pollution in rapidly urbanizing regions. Full article

The primary neural circuit affected in Amyotrophic Lateral Sclerosis (ALS) patients is the corticospinal motor circuit, originating in upper motor neurons (UMNs) in the cerebral motor cortex which descend to synapse with the lower motor neurons (LMNs) in the spinal cord to ultimately innervate the skeletal muscle. Perturbation of these neural circuits and consequent loss of both UMNs and LMNs, leading to muscle wastage and impaired movement, is the key pathophysiology observed. Despite decades of research, we are still lacking in ALS disease-modifying treatments. In this review, we document the current research from patient studies, rodent models, and human stem cell models in understanding the mechanisms of corticomotor circuit dysfunction and its implication in ALS. We summarize the current knowledge about cortical UMN dysfunction and degeneration, altered excitability in LMNs, neuromuscular junction degeneration, and the non-cell autonomous role of glial cells in motor circuit dysfunction in relation to ALS. We further highlight the advances in human stem cell technology to model the complex neural circuitry and how these can aid in future studies to better understand the mechanisms of neural circuit dysfunction underpinning ALS. Full article

Salinity is one of the most significant abiotic stress that affects the growth and development of high-value tree species, including sandalwood, which can also be managed effectively on saline soils with the help of suitable host species. Therefore, the current investigation was conducted to understand the physiological processes and antioxidant mechanisms in sandalwood along the different salinity gradients to explore the host species that could support sandalwood growth in salt-affected agro-ecosystems. Sandalwood seedlings were grown with ten diverse host species with saline water irrigation gradients (EC_iw~3, 6, and 9 dS m⁻¹) and control (EC_iw~0.82 dS m⁻¹). Experimental findings indicate a decline in the chlorophyll content (13–33%), relative water content (3–23%), photosynthetic (27–61%) and transpiration rate (23–66%), water and osmotic potential (up to 137%), and ion dynamics (up to 61%) with increasing salinity levels. Conversely, the carotenoid content (23–43%), antioxidant activity (up to 285%), and membrane injury (82–205%) were enhanced with increasing salinity stress. Specifically, among the hosts, Dalbergia sissoo and Melia dubia showed a minimum reduction in chlorophyll content, relative water content, and plant water relation and gas exchange parameters of sandalwood plants. Surprisingly, most of the host tree species maintained K⁺/Na⁺ of sandalwood up to moderate water salinity of EC_iw~6 dS m⁻¹; however, a further increase in water salinity decreased the K⁺/Na⁺ ratio of sandalwood by many-fold. Salinity stress also enhanced the antioxidative enzyme activity, although the maximum increase was noted with host plants M. dubia, followed by D. sissoo and Azadirachta indica. Overall, the investigation concluded that sandalwood with the host D. sissoo can be successfully grown in nurseries using saline irrigation water and, with the host M. dubia, it can be grown using good quality irrigation water. Full article

Nitrogen (N) and sulfur (S) are essential nutrient elements, and their deficiency affects crop growth, productivity, and nutrient uptake due to their multifaceted role in plant metabolism, which has been well documented. Therefore, agricultural management strategies that can overcome these deficiencies are the need of the hour. In this context, a study was undertaken with the objective to assess the impacts of N and S applications, either basally or through split application (12.5, 25 and 50 kg ha⁻¹), on the nutrient uptake, productivity, use efficiency, and micronutrient content status in soybean seeds, and also the change in soil nutrient zinc (Zn) and iron (Fe) content at different critical stages of soybean crop growth. The field trial was conducted utilizing a randomized complete-block design, and comprised fourteen treatments with varying N and S quantities. N and S were applied through basal and split applications in different combinations. The salient findings indicated that the highest seed, straw yield, N, and S uptake were obtained with the application of N25+25, S25+25, and did not significantly vary with N25+25, S12.5+12.5, N50, and N25+S50. The highest N use efficiency was recorded with the application of N25+S50, and S use efficiency with the application of N25+25, S25+25. The split application of N and S as N25+25, S25+25 significantly increased soil Zn and Fe content at R₂ and R₅ stages of soybean crop growth, as well as seed Zn and Fe uptake. It can be concluded that the basal and split application of N and S at the rate of 25 kg ha⁻¹ can improve soybean productivity through increased mobilization and assimilation by plants. The findings indicated that applying N and S separately, with 25 kg ha⁻¹ each basally and at the R₂ stage resulted in the highest nutrient uptake, and seed and straw yields. The nutrient use efficiencies, along with Zn and Fe uptake by seeds, exhibited noticeable improvements with this split application approach compared to the control. Furthermore, the soil Zn and Fe contents also experienced enhancements due to the split application of both Nand S fertilizers. These results underscore the potential benefits of temporally adopting optimized fertilizer application strategies to maximize agricultural productivity while ensuring efficient nutrient utilization and soil health maintenance. Further research and field trials could provide deeper insights into the long-term impacts and scalability of this approach across different crop varieties and environmental conditions. Full article

The widespread integration of smartphones into modern society has profoundly impacted various aspects of our lives, revolutionizing communication, work, entertainment, and access to information. Among the diverse range of smartphones available, those operating on the Android platform dominate the market as the most widely adopted type. With a commanding 70% share in the global mobile operating systems market, the Android OS has played a pivotal role in the surge of malware attacks targeting the Android ecosystem in recent years. This underscores the pressing need for innovative methods to detect Android malware. In this context, our study pioneers the application of rough set theory in Android malware detection. Adopting rough set theory offers distinct advantages, including its ability to effectively select attributes and handle qualitative and quantitative features. We utilize permissions, API calls, system commands, and opcodes in conjunction with rough set theory concepts to facilitate the identification of Android malware. By leveraging a Discernibility Matrix, we assign ranks to these diverse features and subsequently calculate their reducts–streamlined subsets of attributes that enhance overall detection effectiveness while minimizing complexity. Our approach encompasses deploying various Machine Learning (ML) algorithms, such as Support Vector Machines (SVM), K-Nearest Neighbor, Random Forest, and Logistic Regression, for malware detection. The results of our experiments demonstrate an impressive overall accuracy of 97%, surpassing numerous state-of-the-art detection techniques proposed in existing literature. Full article

To address the complex challenges faced by our planet such as rapidly changing climate patterns, food and nutritional insecurities, and the escalating world population, the development of hybrid vegetable crops is imperative. Vegetable hybrids could effectively mitigate the above-mentioned fundamental challenges in numerous countries. Utilizing genetic mechanisms to create hybrids not only reduces costs but also holds significant practical implications, particularly in streamlining hybrid seed production. These mechanisms encompass self-incompatibility (SI), male sterility, and gynoecism. The present comprehensive review is primarily focused on the elucidation of fundamental processes associated with floral characteristics, the genetic regulation of floral traits, pollen biology, and development. Specific attention is given to the mechanisms for masculinizing and feminizing cucurbits to facilitate hybrid seed production as well as the hybridization approaches used in the biofortification of vegetable crops. Furthermore, this review provides valuable insights into recent biotechnological advancements and their future utilization for developing the genetic systems of major vegetable crops. Full article

The welfare of laying hens in conventional caged houses has become an increased public concern, leading primary food chains, restaurants, and grocers in the United States to pledge to source only cage-free (CF) eggs by 2025 or 2030. Cage-free housing systems have been considered as a more humane alternative; however, they still come with certain challenges. One of the primary challenges with CF housing is the poor indoor air quality due to the high levels of ammonia (NH₃) and particulate matter (PM). Despite the importance of air quality in animal welfare, most studies have focused on the egg-laying stage, thereby leaving a significant knowledge gap in the pullet phase. Addressing this gap is essential to ensure the well-being of laying hens in CF housing and to help producers and researchers identify effective strategies to mitigate the impact of poor indoor air quality on the bird’s health and welfare. Therefore, the objective of this study was to (a) examine the effect of the pullets’ age on NH₃ and PM levels, and (b) find the effect of housing, litter moisture content (LMC), and relative humidity (RH) on air pollutant concentrations. The results show that the PM levels of PM_2.5, PM₁₀, and total suspended particles (TSP) increased significantly with the growth of birds from 1 to 16 weeks of age (WOA) (p < 0.01). For instance, PM_2.5, PM₁₀, and TSP levels were measured at 0.023 ± 0.003, 0.031 ± 0.004, and 0.058 ± 0.013 mg m⁻³ in the first week, and these levels increased to 1.44 ± 0.58, 2.723 ± 1.094, and 6.39 ± 2.96 mg m⁻³, respectively, by 16 WOA. In addition, PM levels measured near the perch were found to be three times higher than other locations inside the rooms (e.g., between the feeder and drinker or near the exhaust fan) (p < 0.01), as perching is one of the primary reasons for dust generation. Furthermore, a significant interaction between the age of the pullets and PM levels was found (p < 0.01), as the litter quality and the behaviors of birds were changing over time. For NH₃ levels, average daily concentrations were lower than 1 ppm at 16 WOA for all rooms due to dry litter conditions (i.e., 9–10% LMC). Additionally, RH has been shown to have a significant effect on air pollutant concentration. Overall, the results indicate that the bird’s age significantly affects PM generation and PM variation within the rooms. The variation of PM was directly affected by RH inside the house. Therefore, this research will provide valuable information for both researchers and producers to control air pollutant emissions from the pullet stage in CF housing to ultimately improve the health and welfare of hens. Full article

Insufficient research has been conducted on musk deer species across their distribution range, primarily because of their elusive behaviour and the fact they occupy remote high-altitude habitats in the Himalayas above 2500 m. The available distribution records, primarily derived from ecological studies with limited photographic and indirect evidence, fail to provide comprehensive information on the species distribution. Consequently, uncertainties arise when attempting to determine the presence of specific taxonomic units of musk deer in the Western Himalayas. This lack of knowledge hampers species-oriented conservation efforts, as there need to be more species-specific initiatives focused on monitoring, protecting, and combatting the illegal poaching of musk deer for their valuable musk pods. We used transect surveys (220 trails), camera traps (255 cameras), non-invasive DNA sampling (40 samples), and geospatial modelling (279 occurrence records) to resolve the taxonomic ambiguity, and identify the suitable habitat of musk deer (Moschus spp.) in Uttarkashi District of Uttarakhand and the Lahaul–Pangi landscape of Himachal Pradesh. All the captured images and DNA-based identification results confirmed the presence of only Kashmir musk deer (KDM) (Moschus cupreus) in Uttarakhand and Himachal Pradesh. The results suggest that KMD inhabit a narrow range of suitable habitats (6.9%) of the entire Western Himalayas. Since all evidence indicates that only KMD are present in the Western Himalayas, we suggest that the presence of other species of musk deer (Alpine musk deer and Himalayan musk deer) was wrongly reported. Therefore, future conservation plans and management strategies must focus only on KMD in the Western Himalayas. Full article