The Scientific World Journal最新文献

In countries that have food security problems like Ethiopia, anchote (Coccinia abyssinica (Lam.) Cogn) holds promising potentials for food, feed, and industrial uses. Efficient utilization of such crops through in vitro propagation is limited due to constraints associated with growth medium components. The present study was therefore conducted to evaluate the effectiveness of Ensete flour (bulla) as a substitute of agar for micropropagation of anchote using nodal explants. The experiment was conducted using different combinations of bulla and agar as a solidifying agent under completely randomized design (CRD) with factorial arrangement. The earliest and highest shoot initiation was observed when a combination of 75 g/L bulla and 2 g/L agar and 65 g/L bulla and 2.8 g/L agar was used as a solidifying agent, respectively. The highest average shoot number, 8.4 and 6.2, was recorded when 75 g/L bulla and 2 g/L agar and 65 g/L bulla and 2.8 g/L agar were used for micropropagation of red and white accessions, respectively. The maximum leaf counts were registered when the MS medium was supplemented with 75 g/L bulla and 2 g/L agar for red (7.6) and 65 g/L bulla and 2.8 g/L agar for white (7.0) accessions. The number of roots was the highest (12.6 and 12.4) on a growth medium supplemented with 65 g/L bulla and 2.8 g/L agar and 75 g/L bulla and 2 g/L agar for white and red accessions, respectively. The present finding showed that bulla has promising potential to substitute agar in plant tissue growth medium; however, characterization of its starch and identifying the primary active components are required.

Placing an intracanal medicament helps in the disinfection of primary root canals, and nanoparticles enhance the material properties by increasing the physical and chemical reactivity. The study was aimed at assessing the efficacy of calcium hydroxide+calcium hydroxide nanoparticles and zinc oxide+zinc oxide nanoparticles as an intracanal medicament when compared with calcium hydroxide and zinc oxide eugenol in terms of antibacterial efficacy and penetration depth. Forty extracted human primary teeth were included in the study. Of these, 40 teeth were divided into two subgroups-Group A (to assess antibacterial efficacy) and Group B (to assess penetration depth). The teeth in Group A were contaminated with an Enterococcus faecalis biofilm for 7 days, and CFU count was determined. Calcium hydroxide (A1), calcium hydroxide with calcium hydroxide nanoparticles (A2), zinc oxide with zinc oxide nanoparticles (A3), and zinc oxide eugenol (A4) were placed in the canals. CFU count was determined on Day 7 and Day 14. The teeth in Group B were also divided into calcium hydroxide (B1), calcium hydroxide with calcium hydroxide nanoparticles (B2), zinc oxide with zinc oxide nanoparticles (B3), and zinc oxide eugenol (B4) groups. Two teeth from each group were subjected to SEM analysis. A statistically significant difference was noted in the CFU count reduction on Day 7 in Group A2, Group A3, and Group A4. The highest penetration depth was noted in Group B2. The authors concluded that the antibacterial efficacy and penetration depth into dentin improved on incorporating calcium hydroxide and zinc oxide nanoparticles. Based on this conclusion, the authors recommend further in vivo studies with nanoparticles incorporated intracanal medicaments in primary teeth to determine their safety of use and feasibility in a clinical scenario.

Substance abuse among healthcare students is a growing issue across various regions, including the Middle East. Here, we investigate its prevalence and correlates in Jordan. The study utilized an online questionnaire consisting of demographics, attitudes toward substance abuse, the Drug Abuse Screening Test (DAST-10), and the prevalence and types of substances of abuse reported by the participants. A total of 465 students participated, including males (41.3%) and females (58.7%). The results revealed a high prevalence of substance abuse (13.76%), which correlated with DAST-10 scores (ρ = 0.442, p < 0.01) and was associated with experiencing suicidal thoughts (p < 0.01). Higher odds (p < 0.05) for substance abuse were observed with smoking (OR = 1.81), working (OR = 2.02), attending private universities (OR = 2.03), studying pharmacy compared to medicine, dentistry, and nursing (OR = 4.85) and being a second year student (OR = 3.23). However, it was not associated with gender, age, marital status, living arrangement, attended high school, GPA, and attending a course covering CNS drugs. In terms of attitudes, substance abuse was associated (p < 0.05) with the following: not believing that substance abusers should be punished or that childhood or friends contribute to substance abuse, believing that abusers cannot fully recover, and still wanting to interact with a healthcare provider who has a history of substance abuse. Lastly, seven drugs of abuse classes were identified, and the main reported class was benzodiazepines (22.6%). In conclusion, substance abuse is prevalent among healthcare students in Jordan and is associated with various demographic and attitude factors, which should be taken into consideration for developing interventional and preventative strategies to mitigate this issue.

A modern service firm-a complex interaction of humans, technology, and corporate culture driven by knowledge and digitalization-is susceptible to intellectual stress (istress) as do humans. This is because both have intellectual capability-intellectual capital (IC) for service firms and competence for humans. However, studies on the istress of firms are famished. As with humans, addressing this issue will help improve the value production capability and competitiveness of service firms. This study sets for itself two objectives: (i) identify the intellectual stressors (istressors) and inhibitors of istress on service firms and (ii) develop and validate a model for the diagnosis and management of istress in service firms. Mediating the transactional theory of stress and coping (TTSC) model, a conceptual model was formulated. The candidate constructs and indicators of the model were extracted from the literature via systematic and scoping reviews. These constructs were aggregated and streamlined into a questionnaire consisting of 108 indicator questions. The questionnaire was randomly administered online using Google Forms. A total of 185 (55.89%) valid individual responses were codified and loaded into SmartPLS4 for PLS-SEM assessments of the conceptual model including its ablated forms. The standard istressors and inhibitors of istress on firms have been validly identified. The istress value for the service industry has been estimated as -0.323. An operational model for service firm's istress diagnosis and management, christened MISS, has been developed and validated. MISS is capable of reverting istress of service firms from distress to eustress. The MISS implementation guide is also presented.

This study investigated the effects of a combination of cassiavera and morel berry ethanol extracts (CMBEs) on diabetic rats, focusing on blood glucose levels, lipid profiles, immune and inflammatory markers, and pancreatic histopathology. Twenty male albino Wistar rats were divided into four groups: Group A (normal rats), Group B (diabetic rats), Group C (diabetic rats treated with metformin), and Group D (diabetic rats treated with CMBE). Parameters such as the IC₅₀ of CMBE, body weight, blood glucose levels, lipid profile, immune markers (leukocyte percentage, total count, and macrophage activity), inflammatory markers (TNF-α and IL-6), and pancreatic histopathology of rats were assessed for 7 weeks. Statistical analysis was performed using one-way analysis of variance followed by Duncan's multiple range test, with a significance level of α = 5%. The results revealed an IC₅₀ value of 18.5338 ppm for CMBE. Weight gain was observed in all groups except Group B, in which rats lost weight. CMBE was notably effective in lowering blood glucose levels in diabetic rats, with rats in Group D exhibiting higher HDL cholesterol levels and total leukocyte counts compared with those in Group C. Furthermore, CMBE significantly reduced TNF-α and IL-6 levels, exhibiting promising potential in promoting pancreatic repair. This study highlights the potential of a combination of Cassiavera and Morel Berry extract as an effective antidiabetic agent, suggesting it as a valuable addition to functional food formulations.

Background: Extensive ongoing research is aimed at enhancing the efficacy of inferior alveolar nerve block (IANB). Even though magnesium itself is not a primary analgesic, it has been shown to increase the effects of analgesics when used as an adjuvant or a supplement. Magnesium sulphate (MgSO₄) has reportedly been used to supplement regional blocks and spinal anaesthesia in various surgical procedures. Building on the concept of MgSO₄ as an analgesic adjuvant, our study aimed to assess its efficacy in increasing IANB success and controlling postsurgical pain. The split-mouth study evaluated the effectiveness of adding MgSO₄ to 2% lignocaine in improving block success and offering postsurgical pain relief after the transalveolar extraction of impacted mandibular third molars (MTMs). Methodology: We carried out a double-blinded, randomized, split-mouth study in 26 patients having bilateral impacted MTM. Patients presenting with impacted MTM bilaterally with a Pederson's score of ≤ 6 were included. The primary outcomes evaluated were the onset time, duration of anaesthesia, need for additional injections, and burning sensation during injection. The secondary outcomes assessed included postoperative pain relief and the quantity of rescue analgesics required. Results: The test side showed a significantly longer duration of analgesia than the control side (p < 0.001). The MgSO₄ group showed a lesser requirement for additional injections; however, it was not found to be statistically significant (0.289). No significant differences were seen in postoperative pain and the number of rescue analgesics. Conclusion: The addition of MgSO₄ to 2% lidocaine resulted in a significantly longer duration of analgesia. Trial Registration: CTRI identifier: CTRI/2018/05/013842.

Background: Traditional medicinal plants are used worldwide to treat human ailments. One of the ailments used to treat medicinal plants through traditional medical practices is the evil eye. This systematic review aimed to compile and document ethnobotanical studies on the treatment of evil eye illnesses in Ethiopia. Methods: A web-based systematic literature search was performed using electronic databases. All studies with complete ethnobotanical information regarding the plants used to treat the illness were included. A total of 53 articles that met the inclusion criteria were used to compile and document this review. The number of plant species and families, parts used, habits, modes of preparation, and routes of administration was tabulated and summarized using an Excel spreadsheet and descriptive statistics. Results and Discussion: Ethnomedicinal use of 146 plant species belonging to 65 families has been reported and documented for the treatment of evil eye illness in Ethiopia. Fabaceae (22 species) and Asteraceae (13 species) were the most commonly used families in terms of the species count. The dominant habit was shrubs (41%), followed by herbs (31%). Roots (37.13%) and leaves (22.77%) were the first and second most commonly used plant parts, respectively. The most commonly used route of medicinal plant preparation was nasal (35.14%), followed by dermal (22.83%), and oral (18.84%) methods. Carissa spinarum L. (Apocynaceae), Withania somnifera (L.) Dunal (Solanaceae), Ruta chalepensis L. (Rutaceae), Allium sativum L. (Amaryllidaceae), and Capparis tomentosa Lam. (Capparaceae) are among the most utilized plant species for the treatment of evil eye illnesses. Conclusion and Recommendations: This review shows that many medicinal plants are used to treat evil eye illnesses in traditional medical practices in Ethiopia. Hence, further investigation of commonly utilized plant species for the same purpose is recommended. In addition, the documentation of indigenous herbal knowledge and conservation of commonly utilized traditional medicinal plants should be strengthened.

Heavy metal pollution is plundering the well-being of people in Bangladesh, a developing country in South Asia, which is also striving to secure green energy resources. This comprehensive review highlights the use of phytoremediation technology to both clean up heavy metal pollution and produce bioenergy in Bangladesh. It emphasizes the dual benefits of removing contaminants from the environment while generating sustainable energy sources. We identified 16 species of hyperaccumulators with potential as bioenergy sources, including second-generation bioethanol, biodiesel, biofuels, biogas, and bioelectricity. This effort supports the adaptability of Sustainable Development Goal 7-access to affordable, reliable, sustainable, and modern energy for all-and is aimed at helping Bangladesh achieve its target of generating 15% of total electricity from renewable sources by 2041. These species were effective in accumulating heavy metals from contaminated soils and wastewater. Bioenergy plants with hyperaccumulating activities can address the issue of biomass disposal by converting bioenergy production after the remediation process of chemical pollutants, leading to bioeconomic technology and increasing the acceptance of large-scale applications. Using advanced biotechnological approaches, it is possible to improve hyperaccumulating activities such as absorbing, accumulating, biodegrading, or immobilizing heavy metals. The review further provides recommendations, including funding initiatives, public awareness campaigns, collaborative efforts, policy development, and capacity building to enhance the development and implementation of phytoremediation technology using bioenergetic plants in Bangladesh, thereby unlocking its bioeconomic potential.

The investigation and diagnosis of hematologic malignancy using blood cell image analysis are major and emerging subjects that lie at the intersection of artificial intelligence and medical research. This survey systematically examines the state-of-the-art in blood cancer detection through image-based analysis, aimed at identifying the most effective computational strategies and highlighting emerging trends. This review focuses on three principal objectives, namely, to categorize and compare traditional machine learning (ML), deep learning (DL), and hybrid learning approaches; to evaluate performance metrics such as accuracy, precision, recall, and area under the ROC curve; and to identify methodological gaps and propose directions for future research. Methodologically, we organize the literature by categorizing the malignancy types-leukemia, lymphoma, and multiple myeloma-and particularizing the preprocessing steps, feature extraction techniques, network architectures, and ensemble strategies employed. For ML methods, we discuss classical classifiers including support vector machines and random forests; for DL, we analyze convolutional neural networks (e.g., AlexNet, VGG, and ResNet) and transformer-based models; and for hybrid systems, we examine combinations of CNNs with attention mechanisms or traditional classifiers. Our synthesis reveals that DL models consistently outperform ML baselines, achieving classification accuracies above 95% in benchmark datasets, with hybrid models pushing peak accuracy to 99.7%. However, challenges remain in data scarcity, class imbalance, and generalizability to clinical settings. We conclude by recommending the integration of multimodal data, semisupervised learning, and rigorous external validation to advance toward deployable diagnostic tools. This survey also provides a comprehensive roadmap for researchers and clinicians striving to harness AI for reliable hematologic cancer detection.

In the current study, we conducted a theoretical study to derive the Lorentz transformation between inertial frames of reference moving in two-dimensional spacetime continuum. The invariance of the space-time interval equation, with use of the derived two-dimensional transformations, yields the notion of 2 + 2-dimensional spacetime continuum which consists of two space and two time coordinates. The velocity addition formulas, Lorentz transformations of energy and momentum are then investigated in 2 + 2-dimensional spacetime frame. Additionally, we investigated the concept of four-vector in 2 + 2 dimensions and further discussed their transformation based on the matrix equation, which is fully consistent with the Lorentz invariant energy-momentum relation.