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Effects of irrigation systems and water management strategies on soil chemical properties and citrus tree productivity in clayey soils
Abstract The growing demand for irrigated crops, coupled with water scarcity and climate change, has made the adoption of efficient irrigation systems and water-saving strategies essential. However, concerns remain regarding the long-term effects of localized soil wetting and deficit irrigation (DI) on soil health and crop productivity, particularly in clayey soils. In that concern, a three-season study was conducted on citrus trees in clayey soils at the Faculty of Agriculture farm, Benha University, Egypt, to evaluate the application effects of surface (FDI) and subsurface drip irrigation (SDI) systems, with and without deficit irrigation, on soil properties and crop yield, compared to traditional flood irrigation (FI). Treatments was conducted as Deficit surface drip irrigation (DFDI), Deficit sub-surface drip irrigation (DSDI), full surface drip irrigation (FFDI) and full sub-surface drip irrigation (FSDI). Under full water requirements (FWR), FSDI outperformed FFDI and FI in terms of water savings (31.58%), water use efficiency (WUE) (58.87%), nutrient uptake (N-P-K) (2.44, 10.52, and 5.69%, respectively), and yield (8.70%), with the lowest rates of deterioration over time. In contrast flood irrigation, despite its higher water consumption, it maintained lower levels of root-zone salinity, alkalinity, and sodicity. Under deficit irrigation (DI), DSDI achieved the highest water savings (48.68%), followed by DFDI at 45.82%. However, applying DI caused the highest deterioration rates over time under both irrigation systems for all studied parameters.
A case report of bacteriophage therapy for the treatment of lung infection due to carbapenem-resistant Pseudomonas aeruginosa
The strategy of vitamin supplementation in Chinese patients with gastric cancer after gastrectomy: a prospective cohort study
Co-delivery of NGF and BMP-2 via thermosensitive pluronic F127 hydrogel enhances chondrogenesis and cartilage repair
Impact of residential cooking and heating on temporal changes of black carbon in rural India
Investigating C7 modified tetrandrine derivatives for synthesis anti-hepatocellular carcinoma activity and mechanistic insights
Abstract Hepatocellular carcinoma (HCC) remains a significant global health challenge, with drug therapy being a critical treatment approach. However, the development of drug resistance and the occurrence of adverse reactions to existing medications have made the creation of new HCC treatments urgent. Tetrandrine, a bisbenzylisoquinoline alkaloid from natural products, has shown great potential in this area. Yet, systematic comparative studies on different tetrandrine modification sites (such as C-7 and C-14) are lacking, which has hindered the simultaneous optimization of its antitumor activity and synthetic feasibility. In this study, we focused on a C-7 modification strategy and designed and synthesized 38 novel tetrandrine sulfonate derivatives (including 31 new compounds) through an efficient one-step reaction. The in vitro antiproliferative activities of these derivatives were evaluated against four HCC cell lines (HepG-2, SMMC-7721, SK-Hep-1, and QGY-7701), and a systematic comparison with previously reported C-14 sulfonate derivatives was conducted. The results showed that all the C-7 derivatives exhibited good antiproliferative activities against HCC. Notably, compound 15 demonstrated significant antiproliferative activity against all tested cell lines, with IC50 values ranging from 3.28 to 6.16 µM, which is superior to the first-line clinical drug 5-fluorouracil. Mechanistic studies revealed that compound 15 exerts its antitumor effects by regulating the balance of Bcl-2 and Bax proteins, triggering the release of cytochrome C from mitochondria, and subsequently activating the caspase-3-dependent apoptosis pathway. The results of target prediction showed that PDGFRA, FLT1, PIK3CD and MET might be the main targets of compound 15 against hepatocellular carcinoma. Although C-14 sulfonate derivatives showed slightly higher in vitro activity, C-7 derivatives (particularly compound 15) exhibited significant advantages in synthetic efficiency (one-step reaction), ease of purification, environmental friendliness, and scalability for industrial production. In conclusion, this study has established C-7 sulfonation as an efficient strategy for developing tetrandrine-based anti-HCC agents. With its remarkable antitumor activity, excellent synthetic process characteristics, and clear apoptosis-inducing mechanism, compound 15 has emerged as a highly promising clinical candidate. This C-7 modification platform provides a viable path for transforming natural product derivatives into clinical therapies for HCC treatment.
A novel extension of the exponential distribution with application in modeling complex lifetime and environmental data
Rapid inactivation of aerosolised influenza virus using low-concentration gaseous hypochlorous acid
Abstract Effective infection control measures are crucial for limiting pathogen transmission, including aerosol infections. Several instances of the use of hypochlorous acid solution spray to inactivate airborne viruses have been reported. However, its effectiveness in controlling infections in aerosol transmission scenarios remains unclear. We evaluated the efficacy of gaseous hypochlorous acid [HOCl(g)], which is safe for occupied environments, in infection control. Exposure to 10–20 ppb HOCl(g) for several seconds significantly reduced the infectivity of aerosolised H1N1 influenza A virus in water-rich droplets by 2.09–2.79 logs. However, no significant reduction occurred in dry aerosols after water evaporation. A stronger inactivation effect was noted at 50% compared to 30% relative humidity, with a 3.06-fold increase in effectiveness. Comparative analysis with a reactive oxygen species gas (O₃), possessing lower liquid-phase solubility than HOCl(g), suggested that aerosol water content facilitates HOCl-mediated virucidal activity. Viral infectivity decreased by 2.34 logs under 20-ppb conditions, even in the presence of 0.3% mucin. These findings underscore the effectiveness of HOCl(g) against aerosolised H1N1 influenza A virus and its potential for infection control.
Efficacy of ultrasound-guided myofascial hydrodissection technique in myofascial pain syndrome of upper trapezius: a randomized controlled trial
Bearing fault diagnosis method based on SAGAN and improved ResNet
Modeling corium pool stratification and focusing effect in APR1400 using a multiphase CFD framework
Red meat consumption in higher healthy eating index diets is associated with brain health critical nutritional adequacy, and fecal microbial diversity
Machine learning-based models for screening of anemia and leukemia using features of complete blood count reports
Abstract Complete blood count (CBC) report features are routinely used to screen a wide array of hematological disorders. However, the complexity of disease overlap increases the probability of neglecting the underlying patterns between these features, and the heterogeneity associated with the subjective assessment of CBC reports often lead to random clinical testing. Such disease prediction analyses can be enhanced by the incorporation of machine learning (ML) algorithms for efficient handling of CBC features. Hybrid synthetic data are generated based on the statistical distribution of features to overcome the constraint of small sample size (N = 287). To the extent of our knowledge, our study is the first to employ hybrid synthetic data for modeling hematological parameters. Six ML models i.e., decision tree, random forest, support vector machine, logistic regression, gradient boosting machine, and multilayer perceptron are tested for disease prediction. This research presents ML-based models for the screening of two common blood disorders – anemia and leukemia, using CBC report features. A ‘fingerprint’ of 14 out of 21 features based on both statistical and clinical relevance is selected for model development. Exceptional performance has been observed by the random forest algorithm with 98% accuracy and 97, 98, 99, and 2% macro-averages of precision, recall, specificity, and miss-rate respectively for all classes. However, external validation of the model reveal poor generalizability on a different demographic dataset, as the model obtained an accuracy of 74%. The proposed methodology may serve as an efficient support system for the screening of anemia and leukemia. However, extensive optimization with regards to its generalizability are warranted.
Heavy metals and natural radioactive isotopes in phosphate and compound fertilisers and their impact on human health
Abstract The paper presents the results of heavy metals (Ni, Cr, Pb, Cd, Zn and Cu) and natural radioactive isotopes (238U, 226Ra, 232Th and 40K) in phosphate and compound fertilisers produced in Poland. Heavy metals in the mineral fertilisers were determined by atomic absorption spectrophotometry in the acetylene-air flame. The content of natural radioactive isotopes was determined using gamma-ray and alpha spectrometry techniques. The average heavy metal content of the tested fertilisers was 154 ± 17, 154 ± 30, 5.43 ± 0.43, 7.87 ± 1.95, 197 ± 19 and 26 ± 7 mg $$\cdot$$ kg− 1 for Ni, Cr, Pb, Cd, Zn and Cu, respectively. Whereas, the average concentrations of natural radioactive isotopes in the studied samples for 238U, 226Ra and 40K were respectively in the range of 715 ± 259, 549 ± 170 and 2472 ± 759 Bq $$\cdot$$ kg− 1, and were higher than their average content in the Earth’s crust, in contrast to the average concentration of the 232Th isotope (12 ± 2 Bq $$\cdot$$ kg− 1) in the tested samples compared to the average concentration in the Earth’s crust. To assess the health exposure of people in direct contact with fertilisers (factory workers, people working in fertiliser loading and unloading, transporters, storekeepers or farmers), basic radiological protection parameters such as radium equivalent activity (Raeq), outdoor dose rate (Dout), indoor dose rate (Din), annual outdoor effective dose and annual indoors effective dose (Eout and Ein) and total annual effective dose (Etot) were determined. It was observed that the calculated radiological hazard parameters for all samples exceeded the worldwide average values.
Comparative analysis of illumina and oxford nanopore sequencing platforms for 16S rRNA profiling of respiratory microbial communities
Association of diabetic ketoacidosis and retinopathy in patients with type 2 diabetes: a nationwide cohort study
Intelligent regulation of university faculty interdisciplinary collaboration networks based on complex network topology evolution and stochastic differential equations
Abstract This study develops a comprehensive theoretical framework integrating complex network topology evolution with stochastic differential equation modeling to characterize and intelligently regulate interdisciplinary collaboration dynamics among university faculty, addressing personnel establishment verification and classified management challenges. The proposed approach addresses persistent barriers in academic collaboration by combining discrete network structural changes with continuous collaboration intensity dynamics under stochastic perturbations. The framework incorporates heterogeneous faculty characteristics, multi-dimensional collaboration attributes, and reinforcement learning-based intelligent regulation mechanisms for dynamic network optimization. Experimental validation demonstrates superior performance compared to conventional methods, achieving 89.3% prediction accuracy and significant improvements in network efficiency, collaboration diversity, and resource utilization. The intelligent regulation mechanism successfully enhances interdisciplinary bridge formation by 34% while maintaining structural stability across diverse institutional scenarios. The mathematical framework captures both deterministic trends and random fluctuations inherent in real-world collaboration systems, providingacademic administrators with quantitative tools for optimizing university faculty collaboration networks through classified management approaches and enhancing research productivity while supporting personnel establishment verification processes. Results confirm robust scalability properties and adaptability to varying environmental conditions, making the approach suitable for practical implementation in academic institutions with different organizational structures and operational constraints.
Optimizing control and management of hybrid power system, consisting PV-wind and battery-super capacitor, using COOT algorithm
Photophysical behaviour, solvatochromism, and silver nanoparticle-induced superquenching of (E, E)-2,5-Bis(3,4,5-trimethoxystyryl) pyrazine with DFT calculations
Abstract The fluorescence quantum yield (ϕf), electronic transition dipole moment (µ12), molar absorptivity (ε), and fluorescence lifetime (τf) of (E, E)-2,5-Bis(3,4,5-trimethoxystyryl) Pyrazine (BTMSP) were studied in various mediums. The medium’s polarity significantly affects fluorescence spectra, showing that the BTMSP is more polar in an excited state. Exciton emission was found in solid crystals of BTMSP at 550 nm upon excitation at 400 nm. The dipole moments of the ground and excited states were evaluated based on the Stokes shift and solvent polarity, showing a higher polarity of 6.22 Debye for the excited state than 2.02 Debye for the ground state. pKa and pKa* values for BTMSP have been determined as 1.95 and 10.88, respectively, indicating the higher basicity of the excited state. The green fluorescence (462–525 nm) was caused by the laser activity of BTMSP dye (0.5 mM) in DMSO, DMF, CH3CN, and dioxane when excited at 337.1 nm by a pulsed nitrogen laser. Fluorescence superquenching of BTMSP was detected using silver nanoparticles (AgNPs) in dynamic and static pathways. The Geometric and electrical structures of BTMSP dye were investigated using DFT methodologies. The outcomes of the experiments and the hypothesis were both consistent. The emission spectra of BTMSP are also studied in cationic and anionic surfactants to determine the critical micelle concentration.