Optimizing lornoxicam-loaded poly(lactic-co-glycolic acid) and (polyethylene glycol) nanoparticles for transdermal delivery: ex vivo/in vivo inflammation evaluation.

Aim: This study focused on developing a topical gel incorporating lornoxicam-loaded poly(lactic-co-glycolic acid) and polyethylene glycol (PLGA-PEG) blend nanoparticles to mitigate gastrointestinal (GIT) side effects and enhance therapeutic efficacy. Materials & methods: Synthesized nanoparticles were subjected to in vitro characterization, ex vivo permeation studies, and acute oral toxicity analysis post-incorporation into the gel using a S/O/W double emulsion solvent. Results & conclusion: The nanoparticles displayed a smooth, spherical morphology (170-321 nm) with increased entrapment efficiency (96.2%). LOX exhibited a permeation rate of 70-94% from the nanoparticle-infused gel, demonstrating favorable biocompatibility at the cellular level. The formulated gel, enriched with nanoparticles, holds promising prospects for drug-delivery systems and promising improved therapeutic outcomes for LOX.

[Box: see text].

Optimizing decision-making with aggregation operators for generalized intuitionistic fuzzy sets and their applications in the tech industry.

Intuitionistic fuzzy sets (IFSs) represent a significant advancement in classical fuzzy set (FS) theory. This study advances IFS theory to generalized intuitionistic fuzzy sets (GIFSBs) and introduces novel operators GIFWAA, GIFWGA, GIFOWAA, and GIFOWGA, tailored for GIFSBs. The primary aim is to enhance decision-making capabilities by introducing aggregation operators within the GIFSB framework that align with preferences for optimal outcomes. The article introduces new operators for GIFSBs characterized by attributes like idempotency, boundedness, monotonicity and commutativity, resulting in aggregated values aligned with GIFNs. A comprehensive analysis of the relationships among these operations is conducted, offering a thorough understanding of their applicability. These operators are practically demonstrated in a multiple-criteria decision-making process for evaluating startup success in the Tech Industry.

Exogenous ascorbic acid as a potent regulator of antioxidants, osmo-protectants, and lipid peroxidation in pea under salt stress.

Pea (Pisum sativum L.), a globally cultivated leguminous crop valued for its nutritional and economic significance, faces a critical challenge of soil salinity, which significantly hampers crop growth and production worldwide. A pot experiment was carried out in the Botanical Garden, The Islamia University of Bahawalpur to alleviate the negative impacts of sodium chloride (NaCl) on pea through foliar application of ascorbic acid (AsA). Two pea varieties Meteor (V1) and Sarsabz (V2) were tested against salinity, i.e. 0 mM NaCl (Control) and 100 mM NaCl. Three levels of ascorbic acid 0 (Control), 5 and 10 mM were applied through foliar spray. The experimental design was completely randomized (CRD) with three replicates. Salt stress resulted in the suppression of growth, photosynthetic activity, and yield attributes in pea plants. However, the application of AsA treatments effectively alleviated these inhibitory effects. Under stress conditions, the application of AsA treatment led to a substantial increase in chlorophyll a (41.1%), chl. b (56.1%), total chl. contents (44.6%) and carotenoids (58.4%). Under salt stress, there was an increase in Na+ accumulation, lipid peroxidation, and the generation of reactive oxygen species (ROS). However, the application of AsA increased the contents of proline (26.9%), endogenous AsA (23.1%), total soluble sugars (17.1%), total phenolics (29.7%), and enzymatic antioxidants i.e. SOD (22.3%), POD (34.1%) and CAT (39%) in both varieties under stress. Salinity reduced the yield attributes while foliarly applied AsA increased the pod length (38.7%), number of pods per plant (40%) and 100 seed weight (45.2%). To sum up, the application of AsA alleviated salt-induced damage in pea plants by enhancing photosynthetic pigments, both enzymatic and non-enzymatic activities, maintaining ion homeostasis, and reducing excessive ROS accumulation through the limitation of lipid peroxidation. Overall, V2 (Sarsabz) performed better as compared to the V1 (Meteor).

Mapping the Meltdown Behavior of Frozen Dairy Desserts.

The meltdown test is an efficient tool widely and commonly used to characterize structural changes in frozen desserts resulting from different ingredients and processing conditions. The meltdown is commonly determined by a gravimetric test, and it is used to obtain the onset (Mon), rate (Mrate), and maximum (MMax) meltdown. However, these parameters are calculated ambiguously due to the inconsistency in the methodology. This work aims at modeling the meltdown curves (weight vs time) of different commercial samples (36 commercial samples). Samples of commercial frozen desserts (40-60 g) was placed on a 304 stainless wire cloth (1.50 mm opening size and 52% open area) suspended about 15 cm above of an analytical balance, and the dripped portion of the melted ice cream was continuously recorded throughout the duration of the test. The meltdown test was conducted at room temperature. Each meltdown test generated more between 3000 to 4000 data points and was modeled using 4 equations: The logistic model, the Gompertz model, the Richard model, and the Hill model. All the meltdown curves were sigmoidal in shape, regardless of the type of frozen dessert. The experimental meltdown curves were adequately represented by the Logistic model, judging by several criteria (R2 = 0.999, adjusted RAdj2 = 0.999, Akaike probability = 6582, and F-value = 1.88 × 106). Thus, the Logistic model was shown to be an effective tool for predicting the meltdown curves of frozen desserts, and it can be used to define unambiguously the onset, rate, and maximum meltdown. Moreover, a dimensionless response (meltdown behavior, MBe) that combines Mon, Mrate, and MMax was developed and used for mapping the meltdown of different commercial frozen desserts.

Investigating the internal structure of multiple mini interviews-A perspective from Pakistan.

BACKGROUND: Healthcare professionals require many personal attributes in addition to cognitive abilities and psychomotor skills for competent practice. Multiple Mini- Interviews are being employed globally to assess personality attributes of candidates for selection in health professions education at all level of entry; these attributes are namely, communication skills, critical thinking, honesty, responsibility, health advocacy, empathy and sanctity of life. Considering the high stakes involved for students, faculty, institutions and the society, rigorous quality assurance mechanisms similar to those used for student assessment must be employed for student selection, throughout the continuum of medical education. It is a difficult undertaking as these psychological constructs are difficult to define and measure. Though considered to yield reliable and valid scores, studies providing multiple evidences of internal structure especially dimensionality of Multiple Mini-Interviews are sparse giving rise to questions if they are measuring a single or multiple constructs and even if they are measuring what they are purported to be measuring. OBJECTIVE: The main objective is to provide statistical support of the multi-dimensional nature of our Multiple Mini Interviews, hypothesized a-priori, through CFA. Another objective is to provide multiple evidences for the internal structure. Our study highlights the link between content and internal structure evidences of the constructs, thus establishing that our Multiple Mini Interviews measure what they were intended to measure. METHOD: After securing permission from the Institutional review board, an a-priori seven factor-model was hypothesized based on the attributes considered most essential for the graduating student of the institution. After operationally defining the attributes through extensive literature search, scenarios were constructed to assess them. A 5-point rating scale was used to rate each item on the station. A total 259 students participated in the multiple mini interviews over a period of three days. A training workshop had been arranged for the participating faculty. RESULTS: The reliability coefficient using Cronbach's alpha were calculated (range from 0.73 to 0.94), Standard Error of Measurement (ranged from 0.80 to1.64), and item to station-total correlation ranged from 0.43-0.50 to 0.75-0.83. Inter-station correlation was also determined. Confirmatory factor analysis endorsed the results of Exploratory factor analysis in the study revealing a seven model fit with multiple indices of Goodness-of-fit statistics such as Root mean square error of approximation (RMSEA) value 0.05, Standardized root mean square residual (SRMR) value with less than 0.08. All these indices showed that model fit is good. The Confirmatory factor analysis confirmed the multi-dimensional nature of our MMIs and also confirmed that our stations measured the attributes that they were supposed to measure. CONCLUSION: This study adds to the validity evidence of Multiple Mini-Interviews, in selection of candidates, with required personality traits for healthcare profession. It provides the evidence for the multi-dimensional structure of Multiple Mini interviews administered with multiple evidences for its internal structure and demonstrates the independence of different constructs being measured.

pH-sensitive docetaxel-loaded chitosan/thiolated hyaluronic acid polymeric nanoparticles for colorectal cancer.

Aim: This study aimed to develop and evaluate pH-sensitive docetaxel-loaded thiolated hyaluronic acid (HA-SH) nanoparticles (NPs) for targeted treatment of colon cancer. Materials & methods: HA-SH, synthesized via oxidation and subsequent covalent linkage to cysteamine, served as the precursor for developing HA-SH NPs through polyelectrolyte complexation involving chitosan and thiol-bearing HA. Results & conclusion: HA-SH NPs displayed favorable characteristics, with small particle sizes (184-270 nm), positive zeta potential (15.4-18.6 mV) and high entrapment efficiency (91.66-95.02%). In vitro, NPs demonstrated potent mucoadhesion and enhanced cytotoxicity compared with free docetaxel. In vivo assessments confirmed safety and biocompatibility, suggesting HA-SH NPs as promising pH-sensitive drug carriers with enhanced antitumor activity for colorectal cancer treatments.

An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients.

In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to provide timely healthcare and diagnosis within a smart framework. This system tracks patients' health by utilizing an Arduino microcontroller, a small and affordable computer that reads data from various sensors, to gather data. Once collected, the data are processed, analyzed, and transmitted to a web page for remote access via an IoT-compatible Wi-Fi module. In cases of emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken to monitor the health of critical COVID-19 patients in isolation. The system employs fuzzy logic to recommend medical treatments for patients. Sudden changes in these medical conditions are remotely reported through a web page to healthcare providers, relatives, or friends. This intelligent system assists healthcare professionals in making informed decisions based on the patient's condition.

Investigating seasonal air quality variations consequent to the urban vegetation in the metropolis of Faisalabad, Pakistan.

Urban atmospheric pollution is global problem and and have become increasingly critical in big cities around the world. Issue of toxic emissions has gained significant attention in the scientific community as the release of pollutants into the atmosphere rising continuously. Although, the Pakistani government has started the Pakistan Clean Air Program to control ambient air quality however, the desired air quality levels are yet to be reached. Since the process of mapping the dispersion of atmospheric pollutants in urban areas is intricate due to its dependence on multiple factors, such as urban vegetation and weather conditions. Therefore, present research focuses on two essential items: (1) the relationship between urban vegetation and atmospheric variables (temperature, relative humidity (RH), sound intensity (SI), CO, CO2, and particulate matter (PM0.5, PM1.0, and PM2.5) and (2) the effect of seasonal change on concentration and magnitude of atmospheric variables. A geographic Information System (GIS) was utilized to map urban atmospheric variables dispersion in the residential areas of Faisalabad, Pakistan. Pearson correlation and principal component analyses were performed to establish the relationship between urban atmospheric pollutants, urban vegetation, and seasonal variation. The results showed a positive correlation between urban vegetation, metrological factors, and most of the atmospheric pollutants. Furthermore, PM concentration showed a significant correlation with temperature and urban vegetation cover. GIS distribution maps for PM0.5, PM1.0, PM2.5, and CO2 pollutants showed the highest concentration of pollutants in poorly to the moderated vegetated areas. Therefore, it can be concluded that urban vegetation requires a rigorous design, planning, and cost-benefit analysis to maximize its positive environmental effects.

Simultaneous decontamination of phosphorus and bisphenol A from livestock wastewater with boehmite-modified carbon composite.

In this work, a novel boehmite-modified carbon adsorbent (BMCC) derived from moldy corn was used for simultaneous removal of P and bisphenol A (BPA) from livestock wastewater. The results showed that BMCC had a high specific surface area (308.82 m2/g) with boehmite nanoparticles anchored on its surface. BMCC showed high P and BPA decontamination capabilities (40.98 mg/g for P and 54.65 mg/g for BPA by Langmuir model). The adsorbed amount of P declined as pH increased from 4 to 10, while the adsorbed amount of BPA remained steady until pH increased to 10. After 6 cycles of BMCC use, the P and BPA adsorption efficiencies reduced by 21.75 % and 19.41 %, respectively. The adsorption of P was dominated by electrostatic attraction and complexation, while the adsorption of BPA was controlled by hydrogen bonding, electrostatic interaction, and π-π association. In conclusion, BMCC is an effective treatment for decontaminating P- and BPA-contaminated livestock wastewater.

Schwann Cells Do Not Promote Myogenic Differentiation in the EPI Loop Model.

In skeletal muscle tissue engineering, innervation and vascularization play an essential role in the establishment of functional skeletal muscle. For adequate three-dimensional assembly, biocompatible aligned nanofibers are beneficial as matrices for cell seeding. The aim of this study was to analyze the impact of Schwann cells (SC) on myoblast (Mb) and adipogenic mesenchymal stromal cell (ADSC) cocultures on poly-ɛ-caprolactone (PCL)-collagen I-nanofibers in vivo. Human Mb/ADSC cocultures, as well as Mb/ADSC/SC cocultures, were seeded onto PCL-collagen I-nanofiber scaffolds and implanted into the innervated arteriovenous loop model (EPI loop model) of immunodeficient rats for 4 weeks. Histological staining and gene expression were used to compare their capacity for vascularization, immunological response, myogenic differentiation, and innervation. After 4 weeks, both Mb/ADSC and Mb/ADSC/SC coculture systems showed similar amounts and distribution of vascularization, as well as immunological activity. Myogenic differentiation could be observed in both groups through histological staining (desmin, myosin heavy chain) and gene expression (MYOD, MYH3, ACTA1) without significant difference between groups. Expression of CHRNB and LAMB2 also implied neuromuscular junction formation. Our study suggests that the addition of SC did not significantly impact myogenesis and innervation in this model. The implanted motor nerve branch may have played a more significant role than the presence of SC.

Multicomponent synthesis of pyrido[2,3-b]pyrazine derivatives: electrochemical DNA sensing, nonlinear optical properties and biological activity.

We synthesized novel pyrido[2,3-b]pyrazin based heterocyclic compounds (4-7) and their chemical structures were ascertained by spectral techniques (NMR, FT-IR). Besides experimental investigation, density functional theory (DFT) computations with B3LYP/6-31G(d,p) level of theory were executed to obtain spectroscopic and electronic properties. Nonlinear optical (NLO) properties, frontier molecular orbitals (FMOs), UV-visible, vibrational analysis, natural bond orbitals (NBOs), transition density matrix (TDM) and density of states (DOS) analyses of molecules (4-7) were accomplished at B3LYP/6-31G (d,p) level. Global reactivity parameters (GRPs) were correlated with the band gap (Egap) values; compound 7 with lower Egap (3.444 eV), exhibited smaller value of hardness (1.722 eV) with greater softness value (0.290 eV-1). The dipole moment (µ), average polarizability 〈α〉, first (ßtot) and second 〈γ〉 hyper-polarizabilities were calculated for compounds (4-7). Compound 7 showed less Egap, highest absorption wavelength and remarkable NLO response. The highest 〈α〉, ßtot and 〈γ〉 values for compound 7 were observed as 3.90 × 10-23, 15.6 × 10-30 and 6.63 × 10-35 esu, respectively. High NLO response revealed that pyrido[2,3-b]pyrazin based heterocyclic compounds had very remarkable contributions towards NLO technological applications. Further compounds (4-7) are utilized for the first time in electrochemical sensing of DNA, in vitro antioxidant and antiurease activity.

The Global Dilemma of Soil Legacy Phosphorus and Its Improvement Strategies under Recent Changes in Agro-Ecosystem Sustainability.

Phosphorus (P) is one of the six key elements in plant nutrition and effectively plays a vital role in all major metabolic activities. It is an essential nutrient for plants linked to human food production. Although abundantly present in both organic and inorganic forms in soil, more than 40% of cultivated soils are commonly deficient in P concentration. Then, the P inadequacy is a challenge to a sustainable farming system to improve the food production for an increasing population. It is expected that the whole world population will rise to 9 billion by 2050 and, therefore, it is necessary at the same time for agricultural strategies broadly to expand food production up to 80% to 90% by handling the global dilemma which has affected the environment by climatic changes. Furthermore, the phosphate rock annually produced about 5 million metric tons of phosphate fertilizers per year. About 9.5 Mt of phosphorus enters human food through crops and animals such as milk, egg, meat, and fish and is then utilized, and 3.5 Mt P is physically consumed by the human population. Various new techniques and current agricultural practices are said to be improving P-deficient environments, which might help meet the food requirements of an increasing population. However, 4.4% and 3.4% of the dry biomass of wheat and chickpea, respectively, were increased under intercropping practices, which was higher than that in the monocropping system. A wide range of studies showed that green manure crops, especially legumes, improve the soil-available P content of the soil. It is noted that inoculation of arbuscular mycorrhizal fungi could decrease the recommended phosphate fertilizer rate nearly 80%. Agricultural management techniques to improve soil legacy P use by crops include maintaining soil pH by liming, crop rotation, intercropping, planting cover crops, and the consumption of modern fertilizers, in addition to the use of more efficient crop varieties and inoculation with P-solubilizing microorganisms. Therefore, exploring the residual phosphorus in the soil is imperative to reduce the demand for industrial fertilizers while promoting long-term sustainability on a global scale.

An Interdigital Microwave Sensor Based on Differential Structure for Dielectric Constant Characteristics Measurement.

In this work, a microwave resonator sensor with a unique configuration consisting of three resonators and two feedlines is proposed. This novel design aims to improve the performance and functionality of microwave resonator sensors for various applications. The frequency response of the sensor to materials with different dielectric constants is simulated. The results show that the most sensitive region of the sensor is located on the first interdigital structure, and placing the materials in other regions would enhance the linear correlation of its frequency response. The sensor also exhibits the ability to distinguish whether the same material has defects and the ability to qualitatively detect subtle changes in dielectric constant. Finally, the proposed sensor is fabricated and measured under the condition consistent with the simulation environment. The measured results are basically consistent with the simulation results, which confirms the potential of this sensor in detecting dielectric constants and resolving materials with defects, and the response of the sensor to the materials under test demonstrates its potential in measuring different thicknesses and loss tangents.

Impact of Self-Efficacy and Perfectionism on Academic Procrastination among University Students in Pakistan.

This study aimed to evaluate the impact of self-efficacy and perfectionism on academic procrastination among university students and its differences among genders in Pakistan. It was hypothesized that self-efficacy and perfectionism would significantly impact academic procrastination and that there is a significant difference in students' views concerning their gender. The sample comprised 405 university students, 104 male and 301 female. The study used the general self-efficacy scale, the multidimensional perfectionism scale, and the academic procrastination scale to measure the constructs. SmartPLS 4 was applied for the analysis of the data. The results indicated that all three variables-self-efficacy, perfectionism, and academic procrastination-were present among university students. Perfectionism showed a significant effect on academic procrastination. However, self-efficacy showed no significant effect on academic procrastination. Further, no significant difference was found in students' views concerning their gender. The findings provide significant evidence for stakeholders to improve academic procrastination among university students.

Looking at both sides, outcomes of positive workplace relational systems: A phenomenological study.

Relational systems are like a gear wheel in organizational processes that keeps employees connected and moving. These relationships are developed and maintained within the work environment for task accomplishment. But these relational systems are originating other outcomes that directly and indirectly affect the organizational process. The present study aimed to explore the outcomes of positive workplace relational systems. Under qualitative phenomenological approach followed a classical content analysis technique employed to analyze the data collected from 20 Bank employees through semi-structured interviews. The data analysis revealed that outcomes of positive relational systems varied depending on the duration and quality of relationships. Organizational culture identified as an important factor that influences the quality of relationships and their outcomes. The data analysis revealed that positive workplace relational systems along with positive behavioral outcomes also develop negative outcomes among employees such as perception of organizational politics. This study argued that outcomes of positive workplace relational systems depend on the perception and need satisfaction of participants. The result highlighted the important areas for individuals and organizations to consider in the context of relationship management, developing interpersonal skills in employees, and encouraging relationship generosity. It will help to enhance the well-being of employees and improve organizational performance.

Assessing the effects of limestone dust and lead pollution on the ecophysiology of some selected urban tree species.

Soil and air pollution caused by heavy metals and limestone dust are prevalent in urban environments and they are an alarming threat to the environment and humans. This study was designed to investigate the changes in morphological and physiological traits of three urban tree species seedlings (Bombax ceiba, Conocarpus lancifolius, and Eucalyptus camaldulensis) under the individual as well as synergetic effects of heavy metal lead (Pb) and limestone dust toxicities. The tree species were grown under controlled environmental conditions with nine treatments consisting of three levels of dust (0, 10, and 20 g) and three levels of Pb contaminated water irrigation (0, 5, and 10 mg L-1). The results depicted that the growth was maximum in T1 and minimum in T9 for all selected tree species. B. ceiba performed better under the same levels of Pb and limestone dust pollution as compared with the other two tree species. The B. ceiba tree species proved to be the most tolerant to Pb and limestone pollution by efficiently demolishing oxidative bursts by triggering SOD, POD, CAT, and proline contents under different levels of lead and dust pollution. The photosynthetic rate, stomatal conductance, evapotranspiration rate, and transpiration rate were negatively influenced in all three tree species in response to different levels of lead and dust applications. The photosynthetic rate was 1.7%, 3.1%, 7.0%, 11.03%, 16.2%, 23.8%, 24.8%, and 30.7%, and the stomatal conductance was 5%, 10.5%, 23.5%, 40%, 50.01%, 61.5%, 75%, and 90.9%, greater in T2, T3, T4, T5, T6, T7, T8, and T9 plants of B. ceiba, respectively, as compared to T1. Based on the findings, among these three tree species, B. ceiba is strongly recommended for planting in heavy metal and limestone dust-polluted areas followed by E. camaldulensis and C. lancifolius due to their better performance and efficient dust and heavy metal-scavenging capability.

Multi-Agent Reinforcement Learning for Traffic Flow Management of Autonomous Vehicles.

Intelligent traffic management systems have become one of the main applications of Intelligent Transportation Systems (ITS). There is a growing interest in Reinforcement Learning (RL) based control methods in ITS applications such as autonomous driving and traffic management solutions. Deep learning helps in approximating substantially complex nonlinear functions from complicated data sets and tackling complex control issues. In this paper, we propose an approach based on Multi-Agent Reinforcement Learning (MARL) and smart routing to improve the flow of autonomous vehicles on road networks. We evaluate Multi-Agent Advantage Actor-Critic (MA2C) and Independent Advantage Actor-Critical (IA2C), recently suggested Multi-Agent Reinforcement Learning techniques with smart routing for traffic signal optimization to determine its potential. We investigate the framework offered by non-Markov decision processes, enabling a more in-depth understanding of the algorithms. We conduct a critical analysis to observe the robustness and effectiveness of the method. The method's efficacy and reliability are demonstrated by simulations using SUMO, a software modeling tool for traffic simulations. We used a road network that contains seven intersections. Our findings show that MA2C, when trained on pseudo-random vehicle flows, is a viable methodology that outperforms competing techniques.