Search Results (262)

Background/Objectives: Accurately correlating mammographic findings with corresponding histopathologic features is considered one of the essential aspects of mammographic evaluation, guiding the next steps in cancer management and preventing overdiagnosis. The objective of this study was to evaluate patterns of mammographic microcalcifications and their association with histopathological findings related to various breast tumors. Methods: 110 out of 3603 women had microcalcification of BIRADS 3 or higher and were subjected to stereotactic/ultrasound (USG) guided biopsies, and hook-wire localization excision procedures. Ultrasound and mammography images were reviewed by experienced radiologists using the standard American College of Radiology Breast-Imaging Reporting and Data System (ACR BI-RADS). Results: Our study showed that features with a high positive predictive value (PPV) of breast malignancy were heterogeneous (75%), fine linear/branching pleomorphic microcalcifications (66.7%), linear (100%), and segmental distributions (57.1%). Features that showed a higher risk of association with ductal carcinoma in situ (DCIS) were fine linear/branching pleomorphic (odds ratio (OR): 3.952), heterogeneous microcalcifications (OR: 3.818), segmental (OR: 5.533), linear (OR: 3.696), and regional (OR: 2.929) distributions. Furthermore, the features with higher risks associated with invasive carcinoma had heterogeneous (OR: 2.022), fine linear/branching pleomorphic (OR: 1.187) microcalcifications, linear (OR: 6.2), and regional (OR: 2.543) distributions. The features of associated masses in mammograms that showed a high PPV of malignancy had high density (75%), microlobulation (100%), and spiculated margins (75%). Conclusions: We concluded that specific patterns and distributions of microcalcifications were indeed associated with a higher risk of malignancy. Those with fine linear or branching pleomorphic and segmental distribution were at a higher risk of DCIS, whereas those with heterogeneous morphology with a linear distribution were at a higher risk of invasive carcinoma. Full article

The purpose of this article is to analyze a hybrid-type iterative algorithm for a class of generalized non-expansive mappings satisfying the Garcia-Falset property in uniformly convex Banach spaces. Some existing results for such mappings have been obtained using the given algorithm. The ${\omega }^2$-stability of the iterative process is also studied. Using some examples, numerical experiments are conducted by comparing this iterative algorithm with different well-known iterative schemes. It is concluded that this iterative algorithm converges faster to the fixed point and is preferable over the previously known iterative schemes using the Garcia-Falset property. A weak solution of the Volterra–Stieltjes-type delay functional differential equation is presented to demonstrate the significance of the proposed results. Full article

Background/Objectives: Leukemia is a common cancer that arises in both children and adults when bone marrow’s hematopoietic stem cells proliferate unrestrained because of anomalies in normal cell regulatory systems. The present study focused on biological evaluation of oxazole-based oxadiazole scaffolds to evaluate the anti-proliferative effect on leukemic cancer cell lines. Methods: All novel oxazole-based oxadiazole scaffolds were synthesized and structurally characterized via ¹³C NMR, ¹H NMR, and HREI-MS. In order to identify an efficient anti-leukemia agent, the biological profiles of each compound were evaluated in comparison to the reference drug, Etoposide (IC₅₀ = 10.50 and 15.20 μM). Results: Analog 6 substituted with p-CF₃ at phenyl ring was identified with excellent inhibition against the HL-60 and PLB-985 cancer cell lines, with IC₅₀ of 8.50 and 12.50 μM. Through hydrogen bond formation, the trifluoromethyl moiety of analog 6 interacts with target tyrosine kinase enzyme (PDB-ID:4CSV). The interactive character of active ligands with target enzyme was demonstrated by molecular docking. The rate of inhibition in contrast with the drug concentration was also tested to check the inhibition percentage and inhibitor type via enzyme kinetics. Furthermore, the enzyme–ligand complex was also investigated via MD simulation along with pharmacophore modeling. DFT calculations were used to estimate the lead compounds’ relative stability and reactivity. According to ADMET investigation, there is safe toxicological profile for these compounds. Conclusions: The current study suggests that the potent compounds have significant anti-proliferative potential, and with further in vivo validation, hold promise for future optimization as potential leukemia treatments. Full article

As the global focus on sustainability intensifies, architects and engineers are increasingly seeking innovative passive strategies to improve building energy efficiency. Among these strategies, the strategic integration of louvers has garnered significant attention due to their potential to optimize building envelope performance and reduce energy consumption. Louvers effectively manage solar heat gain, mitigating the impact of extreme temperatures on indoor spaces. Consequently, louvers reduce the reliance on active HVAC systems, leading to notable energy savings and a decreased carbon footprint. This paper presents a comprehensive review of the role of louvers in enhancing building energy efficiency, highlighting their designs, efficiency, and improvement suggestions. Moreover, this review article addresses potential challenges related to louver design, such as balancing the trade-off between solar heat gain and daylighting and how to optimize louver configurations for specific building types. Approaches to overcome these challenges, including advanced modeling techniques and parametric design, are also explored to assist architects and designers in achieving the most energy-efficient outcomes. Full article

This study investigates the critical roles of green innovation adoption (GIA) and green technology adoption (GTA) in advancing the digital economy (DE). It explores how creative enterprises (CE) and financial capability (FC) mediate and moderate the relationships between green innovation, technology adoption, and the digital economy. Data were collected from 400 respondents in the automotive industry in China through a structured survey questionnaire. Structural Equation Modeling (SEM) was conducted using Smart PLS 4.0 to analyze the data and test the proposed hypotheses. The findings indicate that green innovation and technology adoption significantly and positively impact the digital economy. Moreover, these factors positively influence creative enterprises, enhancing the digital economy. Creative enterprises were also found to mediate the relationship between green innovation/technology adoption and the digital economy. In addition, financial capability significantly moderated the link between creative enterprises and the digital economy. This research contributes to the literature by examining the synergistic effects of environmental sustainability, innovation adoption, and technological integration within the digital economy. It provides actionable insights into embedding sustainable practices in the evolving digital landscape while highlighting the intricate dynamics among innovation, technology adoption, and financial resources in driving economic transformation. This study contributes to the literature by exploring the synergistic effects of green innovation, technology adoption, and financial capability in driving the digital economy, focusing on creative enterprises as a mediating factor. It provides actionable insights for integrating sustainability into the digital landscape, offering a novel framework for economic transformation in the automotive industry. Full article

Adopting innovative, systematically structured, and sustainable human resource management (SHRM) practices is essential for enhancing logistics agility and deriving sustainable development in logistics operations. This study examines the influence of sustainable human resources management practices on logistics agility with a mediating role of artificial intelligence (AI) in China’s logistics industry. Given the rapid growth and technological advancements in China’s logistics sector, this study employed quantitative research and convenience sampling techniques to collect data from 341 employees working in the industry. Smart PLS was used to test the proposed hypotheses through structural equation modeling (SEM). The study’s findings reveal that reward management, training and development, job appraisal, and teamwork significantly enhance logistics agility, while recruitment and selection show an insignificant impact. Similarly, the results reveal that sustainable HRM practices and artificial intelligence positively and significantly influence logistics agility. In addition, artificial intelligence substantially mediates the relationship between sustainable HRM practices and logistics agility. These findings offer valuable insights for HRM and logistics management, highlighting how AI can strengthen sustainable HRM practices to foster agility and improve logistics performance. The findings are particularly relevant for practitioners and policymakers aiming to enhance sustainability and efficiency in the logistics sector. Full article

Flowers are one of the most important organs in plants. Their development serves as a key indicator of the transition from vegetative to reproductive growth and is regulated by various internal signals and environmental factors. NAC (NAM, ATAF, CUC) transcription factors (TFs) play a crucial regulatory role in floral organ development; however, research on the analysis and identification of the NAC TF family in Chinese cabbage (Brassica rapa L.) remains limited. In this study, we performed a comprehensive genome-wide analysis of NACs in B. rapa and identified 279 members of the BrNAC gene family. Their physicochemical properties, domain structure, collinearity relation, and cis-regulatory elements were evaluated. Phylogenetic analysis indicates that NAC proteins from Arabidopsis, B. rapa, B. oleracea, and B. nigra can be classified into seven distinct clades. BrNACs exhibit a tissue-specific expression, and nine BrNACs being specifically expressed in the inflorescence. Furthermore, nine flower-related BrNACs were selected for RT-qPCR analysis to validate their expression profiles. BrNAC2s has been cloned to investigate their subcellular localization, and examine the expression patterns of their promoters in Arabidopsis inflorescences. BrNAC2a and BrNAC2c are highly expressed in stamens while BrNAC2b exhibits elevated expression in pistils and pedicel. Collectively, our findings enhance the understanding of the BrNAC family and provide a foundation for future studies on the molecular mechanisms of BrNACs in floral development. Full article

Mango (Mangifera Indica L.), a key horticultural crop, particularly in Pakistan, has been primarily studied locally using low- to medium-resolution satellite imagery, usually focusing on a particular phenological stage. The large canopy size, complex tree structure, and unique phenology of mango trees further accentuate intrinsic challenges posed by low-spatiotemporal-resolution data. The absence of mango-specific vegetation indices compounds the problem of accurate health classification and yield estimation at the tree level. To overcome these issues, this study utilizes high-resolution multi-spectral UAV imagery collected from two mango orchards in Multan, Pakistan, throughout the annual phenological cycle. It introduces MangiSpectra, an integrated two-staged framework based on Long Short-Term Memory (LSTM) networks. In the first stage, nine conventional and three mango-specific vegetation indices derived from UAV imagery were processed through fine-tuned LSTM networks to classify the health of individual mango trees. In the second stage, associated data such as the trees’ age, variety, canopy volume, height, and weather data were combined with predicted health classes for yield estimation through a decision tree algorithm. Three mango-specific indices, namely the Mango Tree Yellowness Index (MTYI), Weighted Yellowness Index (WYI), and Normalized Automatic Flowering Detection Index (NAFDI), were developed to measure the degree of canopy covered by flowers to enhance the robustness of the framework. In addition, a Cumulative Health Index (CHI) derived from imagery analysis after every flight is also proposed for proactive orchard management. MangiSpectra outperformed the comparative benchmarks of AdaBoost and Random Forest in health classification by achieving 93% accuracy and AUC scores of 0.85, 0.96, and 0.92 for the healthy, moderate and weak classes, respectively. Yield estimation accuracy was reasonable with $R^2=0.21$, and $\mathrm{RMSE}=50.18$. Results underscore MangiSpectra’s potential as a scalable precision agriculture tool for sustainable mango orchard management, which can be improved further by fine-tuning algorithms using ground-based spectrometry, IoT-based orchard monitoring systems, computer vision-based counting of fruit on control trees, and smartphone-based data collection and insight dissemination applications. Full article

Background: Cigarette smoking is a leading cause of preventable mortality, largely due to the absence of effective, non-invasive biomarkers for early disease detection. Profiling serum metabolomics to identify metabolic changes holds the potential to accelerate the detection process and identify individuals at risk of developing smoking-related diseases. Objectives: This study investigated the biochemical and metabolomic changes induced by nicotine exposure, with a focus on disruptions in amino acid, lipid, and carbohydrate metabolism. Methods: Liquid chromatography–tandem mass spectrometry (LC-MS/MS) was employed to observe significant disruptions in lipid and amino acid metabolism, along with alterations in key metabolic pathways. A total of 400 smokers and 100 non-smokers were included to evaluate the biomarkers related to insulin resistance, blood lipid profile, inflammation, and kidney and liver function. Results: The results demonstrated significantly elevated (p < 0.05) levels of glycemic markers in smokers, including fasting blood glucose; glycated hemoglobin (HbA1c); and inflammatory markers such as interleukin-6 (IL-6) and C-reactive protein (CRP). Smokers also exhibited dyslipidemia, with increased total cholesterol (154.888 ± 35.565) and LDL levels (117.545 ± 24.138). Impaired liver and kidney function was evident, with significantly higher levels (p < 0.05) of AST, ALP, ALT, blood urea nitrogen, and creatinine in smokers. A total of 930 metabolites were identified, of which 343 exhibited significant alterations (p < 0.05) in smokers compared to non-smokers. Among these, 116 metabolites were upregulated, and 127 were downregulated. Metabolomic pathway analysis revealed eight significant pathways. The study also identified three lipid metabolites specific to smokers and seven unique to non-smokers. Through LC-MS/MS, fragments of phenylalanine, tryptophan, valine, histidine, carnitine, and sphinganine were detected. Several lipidomic changes associated with insulin resistance and cardiovascular complications were observed. Cadmium (Cd) levels were higher in smokers than non-smokers (1.264 ppb vs. 0.624 ppb) and showed a strong negative correlation (R² = 0.8061, p-value = 0.015) with serum zinc (Zn), likely due to Cd displacing Zn in proteins and causing nephrotoxicity through accumulation. Conclusions: This study highlights the distinct metabolic disruptions caused by smoking that could serve as potential biomarkers for the early detection of metabolic diseases. It emphasizes the importance of metabolomics in identifying systemic indicators of smoking-related health issues, providing new opportunities for preventive and therapeutic interventions. Full article

We report super broad non-Hermitian line shape from out-of-phase and in-phase photon-phonon dressing (quantization) in Eu³⁺: NaYF₄ and Eu³⁺: BiPO₄ nanocrystals. The line shape is controlled by changing time gate position, time gate width, power, temperature, sample, photomultiplier tubes, and laser. We observed that the fluorescence (FL) line-shape contrasts are 69.23% for Eu³⁺: BiPO₄ and 43.75% for Eu³⁺: NaYF₄, owing to the stronger out-of-phase photon-phonon dressing (destructive quantization). Moreover, we observed that the spontaneous four-wave mixing (SFWM) line shape was approximately three times wider at 300 K than at 77 K for the [(12:1)-phase] Eu³⁺: NaYF₄ due to more high-frequency in-phase phonon dressing (strong constructive quantization). Furthermore, we showed that the noise line-shape width remains unchanged for Eu³⁺: BiPO₄ (16 nm) and Eu³⁺: NaYF₄ (12 nm) due to out-of-phase and in-phase photon-phonon dressing balance. Such results have potential applications in multi-channel band stop filter. Full article

Precipitation plays a critical role in the hydrological cycle and significantly influences the biodiversity of the Earth’s ecosystems. It also regulates socioeconomic systems by impacting agricultural production and water resources. Analyzing climate-driven changes in precipitation patterns is essential for understanding the hydrological cycle’s response to global warming. This study analyzed the projections of five general circulation models (GCMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to evaluate variations in the seasonal and annual patterns of future precipitation over the northern highlands of Pakistan (NHP). The analysis focused on precipitation variations projected for the near future (2021–2050), in comparison to the historical climate (1985–2014), utilizing two combined scenarios from the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP2-4.5 and SSP5-8.5). This study employed the multi-model ensemble (MME) approach, which demonstrated notable seasonal and annual variations in precipitation across the NHP. The average annual precipitation is expected to decrease in both scenarios, with SSP2-4.5 expecting a reduction of −21.42% and SSP5-8.5 expecting a decrease of −22.43%, compared to the historical average precipitation. In both scenarios, the seasonal precipitation patterns are similar. However, the changes are more noticeable in the spring and summer. Both SSPs predict a 15% decrease in summer precipitation, while SSP2-4.5 and SSP5-8.5 predict a 5% and 4% decrease in spring precipitation, respectively. These changes can result in more frequent and intense periods of drought, which might adversely impact agriculture, human health, the environment, hydropower generation, and the surrounding ecosystem. This study provides important insights into projected seasonal and annual precipitation changes over the NHP, which is particularly susceptible to the effects of climate change. Thus, it is crucial to understand these predicted changes in precipitation in order to develop strategies for adapting to the climate, assuring water security, and promoting sustainable agricultural practices in this area. Full article

This review explores the intricate relationship between plants and bacterial endophytes, revealing their multifaceted roles in promoting plant growth, resilience, and defense mechanisms. By selectively shaping their microbiome, plants harness diverse endophytic bacterial strains to enhance nutrient absorption, regulate hormones, mitigate damage, and contribute to overall plant health. The review underscores the potential of bacterial endophytes in self-sustaining agricultural systems, offering solutions to reduce reliance on fertilizers and pesticides. Additionally, the review highlights the importance of endophytes in enhancing plant tolerance to various environmental stresses, such as drought, salinity, extreme temperatures, and heavy metal toxicity. The review emphasizes the significance of understanding and harnessing the mutualistic relationship between plants and endophytes for maximizing agricultural yields and promoting sustainable farming practices. Full article

Exposure to heavy metals, particularly cadmium (Cd), poses significant health risks because of their toxic effects and potential for bioaccumulation in living organisms. This study examined the biochemical and metabolomic changes induced by Cd exposure in an animal model via advanced liquid chromatography with tandem mass spectrometry (LC-MS/MS) and biochemical assays to reveal significant disruptions in lipid and amino acid metabolism as well as alterations in key metabolic pathways. Cd exposure led to significant weight loss, hyperglycemia, and insulin resistance, indicating its role in metabolic disorders such as diabetes. The accumulation of Cd in the liver and kidneys, identified via ICP-OES, corresponded with elevated levels of liver (ALT, AST) and kidney (BUN, creatinine) biomarkers, suggesting organ-specific toxicity. At the metabolic level, Cd exposure caused the accumulation of lipid metabolites such as ceramides and sphingolipids, which are associated with insulin resistance and broader metabolic impairments. Amino acid metabolism was also significantly disrupted, with increased concentrations of key amino acids such as phenylalanine, tryptophan, and arginine affecting pathways such as the urea cycle and Krebs cycle. These metabolic disturbances are linked to oxidative stress, systemic inflammation, and impaired glucose regulation, as evidenced by elevated CRP and IL-6 levels. The protective effects of resveratrol (RSV) were clearly demonstrated in this study. RSV treatment ameliorated Cd-induced biochemical and metabolic alterations, as shown by improved glycemic control, restored lipid profiles, and normalized amino acid concentrations. Additionally, RSV significantly reduced inflammatory markers and improved liver and kidney function, highlighting its antioxidant properties and potential as a therapeutic agent against Cd toxicity. However, RSV did not significantly reduce Cd accumulation in organs, indicating that its protective effects are related to mitigating oxidative damage and metabolic disruption rather than promoting Cd excretion. This study enhances our understanding of the molecular mechanisms underlying Cd-induced metabolic impairments and highlights the therapeutic potential of RSV in combating Cd toxicity. These findings underscore the need for further research into heavy metal exposure and its mitigation to protect human health, particularly in areas of environmental contamination. Full article