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Shahid Shah,1 Muhammad Hanif,2 Hafeez Ullah Khan,3 Faiz Ullah Khan,4 Ghulam Abbas,5 Haris Khurram,6 Ahmed Khames,7 Mohamed A Abdelgawad,8 Amira SA Said,9,10 Mohammed AS Abourehab,11 Safirah Maheen,3 Usman Rashid Chand,1 Muhammad Haris1 1Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Government College University Faisalabad, Faisalabad, Pakistan; 2Department of Pharmaceutics, Faculty of Pharmacy, Bahauddin Zakariya University Multan, Multan, Pakistan; 3College of Pharmacy, Department of Pharmaceutics, University of Sargodha, Sargodha, Pakistan; 4Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi’an Jiaotong University, Xi’an, People’s Republic of China; 5Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University Faisalabad, Faisalabad, Pakistan; 6National University of Computer and Emerging Sciences, Chiniot-Faisalabad Campus, Chiniot, Pakistan; 7Department of Pharmaceutics and Industrial Pharmacy, College of Pharmacy, Taif University, Taif, 21944, Saudi Arabia; 8Department of Pharmaceutical Chemistry, College of Pharmacy, Jouf University, Sakaka, Al Jouf, 72341, Saudi Arabia; 9Clinical Pharmacy Department, Faculty of Pharmacy, Beni-Suef, Egypt; 10Clinical Pharmacy Department, College of Pharmacy, Al Ain University, Al Ain, Abu Dhabi, United Arab Emirates; 11Department of Pharmaceutics, Faculty of Pharmacy, Umm Al-Qura University, Makkah, 21955, Saudi ArabiaCorrespondence: Shahid Shah; Ghulam Abbas, Email Shahid.waris555@gmail.com; ghulamabbas@gcuf.edu.pkBackground: Pharmacogenomics (PGx) is essential for optimizing drug therapy and reducing unwanted drug side effects. Our aim was to determine the knowledge, attitude and practice of senior pharmacy students in Punjab, Pakistan towards PGx.Methods: A cross-sectional study was conducted among 511 undergraduate pharmacy students from different universities in Punjab, Pakistan. A validated and pilot-tested structured questionnaire was administered to respondents to assess their knowledge, attitude, and practice regarding PGx. Descriptive statistics and multivariate logistic regression model were used to describe the results of the study. A p-value of less than 0.05 was considered statistically significant.Results: A total of 511 students (58.9% females and 41.1% males) responded to the survey. Most (87.7%) of the students knew that the drug response could be affected by genetic variations. Mean knowledge score of the students was 12.6. Good basic knowledge positively and significantly (p=0.01) affected students’ PGx test knowledge and attitudes. Most (> 70%) of students believed that human genetics affected the drug response due to interindividual variation and ethnic variation. Mean attitude score of the students was 5.23. The majority of students (> 92%) wanted to learn more about PGx and thought it could help them choose the right drug. Students’ knowledge was positively and significantly (p=0.01) affected by a good attitude. Mean practice score of the students was 11.95. When trying to solve a drug-related case study question, about 31.5% of students implemented the idea of human genetic variation. Only 28.8% of students attended a lecture related to the effects of genetic variations on drug therapy. Good practice positively and significantly (p=0.01) affected students’ knowledge of PGx tests.Conclusion: The senior pharmacy students had good knowledge and attitudes towards PGx. However, the practice of PGx needs to be improved to facilitate the application of PGx in clinical practice in Pakistan.Keywords: pharmacogenomics, knowledge, attitude, practice

Muhammad Hanif,1 Shahid Shah,2 Akhtar Rasul,3 Ghulam Abbas,3 Muhammad Zaman,4 Muhammad Wahab Amjad,5 Maria Abdul Ghafoor Raja,5 Hafeez Ullah Khan,6 Mehran Ashfaq,3 Omeira Iqbal3 1Department of Pharmaceutics, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, Pakistan; 2Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, Pakistan; 3Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, Pakistan; 4Faculty of Pharmacy, University of Central Punjab, Lahore, Pakistan; 5Department of Pharmaceutics, Faculty of Pharmacy, Northern Border University, Rafha, Saudi Arabia; 6College of Pharmacy, University of Sargodha, Sargodha, PakistanCorrespondence: Ghulam AbbasDepartment of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, PakistanEmail ghulamabbas@gcuf.edu.pkBackground: Bisphosphonates have very low bioavailability and cause irritation of the esophagus and stomach. This study was planned to improve the oral bioavailability of ibandronate through the formation of a raft in the stomach. Bisphosphonate-induced irritation of the esophagus and stomach is prevented by the formation of a raft.Materials and Methods: The nanostructured raft was developed through the use of nanosized citrus pectin (NCP). The particle size of NCP was measured by zeta sizer and SEM. The percentage of NCP and the neutralization profile of raft was studied. The ibandronate, polymers, and the developed formulation were characterized by FTIR, XRD, TGA, and DSC. The release of ibandronate was studied in 0.1 N HCl, 0.5 N HCl, 1 N HCl, and simulated gastric fluid (SGF) and a cell viability study was performed using Caco-2 cells. The PPR5 formulation and Bonish 150 mg tablets were selected as test and reference formulations, respectively, for pharmacokinetic study. Twelve healthy albino rats were taken and divided into two groups using a Latin square crossover design, and the blood samples were collected for 24 hours.Results: The SEM image showed that the particle size of NCP was 159 nm. The raft of PPR5 showed 94% NCP and 45 minutes duration of neutralization. The FTIR and XRD showed chemical stability and a uniform distribution of ibandronate in the raft. The TGA and DSC indicated the thermal stability of formulation. The release of 99.87% ibandronate at 20 minutes was observed in the SGF. The values of Cmax for the reference and test formulations were 493± 0.237 ng/mL and 653± 0.097 ng/mL, respectively. The AUC(0-t) of the reference and test formulations was 3708.25± 3.418 ng/mL.h and 6899.25± 3.467 ng/mL.h, respectively.Conclusion: The NCP has been successfully prepared from citrus pectin and has shown effective porous raft formation. The bioavailability of the ibandronate from newly developed PPR5 was higher than the already marketed formulation.Keywords: nanosized citrus pectin, raft, in vitro release, cell viability, pharmacokinetics

Background: A substantial number of hospital admissions end in patient-initiated departure before medical treatment is complete. Whether "before medically advised" (BMA) discharge increases the risk of subsequent drug overdose remains uncertain., Methods: We performed a retrospective cohort study using administrative health data from a 20% random sample of residents of British Columbia, Canada. We focused on nonelective, nonobstetric hospital stays occurring between 2015 and 2019. We used survival analysis to compare the rate of fatal or nonfatal illicit drug overdose in the first 30 days after BMA discharge versus the rate after physician-advised discharge., Results: Overall, 6440 of 189 808 (3.4%) hospital stays ended in BMA discharge. Among 820 overdoses occurring in the first 30 days after any hospital discharge, 755 (92%) involved patients with a history of substance use disorder. Unadjusted overdose rates were 10-fold higher after BMA discharge than after physician-advised discharge, and BMA discharge was associated with subsequent overdose even after adjustment for potential confounders (crude incidence, 2.8% v. 0.3%; adjusted hazard ratio [HR] 1.58; 95% confidence interval [CI] 1.31-1.89). Before medically advised discharge was associated with increases in subsequent emergency department visits (adjusted HR 1.92; 95% CI 1.83-2.02) and unplanned hospital readmissions (adjusted HR 2.07; 95% CI 1.96-2.19), but there was no significant association with the uncommon outcomes of fatal overdose and all-cause mortality., Interpretation: Before medically advised departure is associated with an increased risk of drug overdose in the first 30 days after discharge. Improved treatment of substance use disorder, expanded access to overdose prevention services, and new means of postdeparture outreach should be explored to reduce this risk., Competing Interests: Competing interests:: Jeffrey Brubacher reports receiving grants from the Canadian Institutes of Health Research (CIHR), Public Safety Canada, Transport Canada, British Columbia Ministry of Public Safety and Solicitor General, and Saskatchewan Government Insurance. Alexis Crabtree is an employee of the BC Centre for Disease Control, an agency of the BC Provincial Health Services Authority. Jessica Moe reports receiving grants or contracts from the Vancouver Physician Staff Association, the Canadian Association of Emergency Physicians/Schwartz-Reisman Emergency Medicine Institute, the Health Canada Substance Use and Addictions Program, CIHR (team grant: Partnerships for Cannabis Policy Evaluation; project grants: Opioid Overdose-Related Cardiac Arrest, Evaluating Microdosing in Emergency Departments, and Drug Overdose after Departure from Hospital Against Medical Advice; training grants: Clinical Trials Training Platforms), and the BC Centre for Disease Control (STARTS grant). Dr. Moe has also received the Vancouver Coastal Health Research Institute Mentored Clinician Scientist Award. Amanda Slaunwhite reports receiving project grant funds from Health Canada, CIHR, the Public Health Agency of Canada, the Community Action Initiative, the province of British Columbia, and Michael Smith Health Research BC (all payments made to the University of British Columbia or Provincial Health Services Authority for staff, trainee, or other project costs). Dr. Slaunwhite has also served on the Board of Directors of Unlocking the Gates and Moms Stop the Harm (unpaid). John Staples reports receiving salary support from a Michael Smith Health Research BC Health Professional–Investigator Award and the UBC Division of General Internal Medicine’s Academic Investment Fund. No other competing interests were declared., (© 2024 CMA Impact Inc. or its licensors.)

Colorectal cancer (CRC), with the incidence and mortality rising on a yearly basis, greatly threatens people's health. It is considered an important hallmark of tumorigenesis that aberrant glucose metabolism in cancer cells, particularly the Warburg effect. In CRC, the Warburg effect predominantly influences cancer development and progression via its involvement in the glycolytic pathway regarding cell metabolism. The critical mechanisms underlying this process include key glycolytic enzymes, transport proteins, regulatory molecules, and signaling pathways. Furthermore, targeting the reprogrammed glucose metabolism in cancer cells can be potentially used for CRC treatment. However, the mechanisms driving CRC onset and progression, especially in relation to glucose metabolism reprogramming, are not fully understood and represent an emerging field of research. The review aims at providing new insights into the role that glucose metabolism reprogramming plays in the progression of CRC progression together with its resistance to treatment. Ultimately, these insights strive to diminish the risks of CRC metastasis and recurrence., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

The Astragalus grahamianus (AG) Royle ex. Benth is traditionally used for the treatment of various human disorders. The current research work is aimed to explore the neuroprotective anti-Parkinson effects of various fractions of Astragalus grahamianus (A. grahamianus). Fine powder of Astragalus grahamianus was extracted with 70% methanol and then fractionated with various solvents on the basis of polarity. Standard protocols were used to investigate the bioactive constituents present in the various plant fractions. In-vitro antioxidant potential of various fractions was checked using diverse free radicals. In-vivo rats model was used to determined the neuroprotective effects of methanol fraction of A. grahamianus. The results revealed that various fractions of A. grahamianus contain flavonoids, cardiac glycosides, steroids, gums, terpenes, proteins, and carbohydrates except chloroform fraction lake the presence of steroids, cardiac glycosides, gums and saponins, aqueous fraction of steroids, terpenoids, gums and saponins, n-Hexane fraction steroids, carbohydrates, alkaloids, gums and flavonoids. The highest amount of total phenolic contents was found in AGME (32.67 ± 2.3 mg GAE / g). The AGME also showed enhanced free radicals cations potential against DPPH, ABTS and H2O2, respectively. The correlation between AOA (antioxidant activity) and TPC (total phenolic contents) revealed to be substantial. Relative R2 values for ABTS, H2O2, and DPPH activity are 0.9974, 0.9845, and 0.9678, respectively. The in-vivo neuroprotective activities showed significant results. Our findings highlight significant antioxidant, and neuroprotective possessions of AGME attributed to powerful bioactive compounds.

During the current COVID-19 pandemic, many digital solutions around the world have been proposed to cope with the deadly virus but the role of mobile-based applications is dominant one. In Pakistan, during the current COVID-19 pandemic, an array of mobile health applications (apps) and platforms have been launched to grapple with the impacts of the COVID-19 situation. In this survey, our major focus is to explore and analyze the starring role of mobile apps based on the features and functionalities to tackle the COVID-19 disease, particularly in Pakistan. In this study, over fifty (50) mobile apps have been scrapped from the well-known three different sources i.e. Google Play Store, iOS Play Store, and web source. We developed our own data set after searching through the different play stores. We have designed two criteria such that the first criteria are known as eligibility criteria, while the second one is known as assessment criteria. The features and functions of each mobile app are pinpointed and discussed against the parameters of the assessment criteria. The major parameters of assessment criteria are: (i) Home monitoring; (ii) COVID-19 awareness; (iii) contact tracing; (iv) telemedicine; (v) health education; (vi) COVID-19 surveillance; (vii) self-assessment; (viii) security; and (ix) accessibility. This study conducted exploratory analysis and quantitative meta-data analysis by adopting PRISMA guidelines. This survey article is not only discussing the function and features of each COVID-19-centered app in Pakistan, but it also sheds light on the limitations of every mobile app as well. The results of this survey might be helpful for the mobile developers to review the current app products and enhance the existing mobile platforms targeted towards the COVID-19 pandemic. This is the first attempt of its kind to present a state-of-the-art survey of the COVID-19-centered mobile health apps in Pakistan., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The current COVID-19 pandemic has affected almost every aspect of life but its impact on the healthcare landscape is conspicuously adverse. However, digital technologies played a significant contribution in coping with the challenges spawned by this pandemic. In this list of applied digital technologies, the role of immersive technologies in battling COVID-19 is notice-worthy. Immersive technologies consisting of virtual reality (VR), augmented reality (AR), mixed reality (MR), extended reality (XR), metaverse, gamification, etc. have shown enormous market growth within the healthcare system, particularly with the emergence of pandemics. These technologies supplemented interactivity, immersive experience, 3D modeling, touching sensory elements, simulation, and feedback mechanisms to tackle the COVID-19 disease in healthcare systems. Keeping in view the applicability and significance of immersive technological advancement, the major aim of this study is to identify and highlight the role of immersive technologies concerning handling COVID-19 in the healthcare setup. The contribution of immersive technologies in the healthcare domain for the different purposes such as medical education, medical training, proctoring, online surgeries, stress management, social distancing, physical fitness, drug manufacturing and designing, and cognitive rehabilitation is highlighted. A comprehensive and in-depth analysis of the collected studies has been performed to understand the current research work and future research directions. A state-of-the-artwork is presented to identify and discuss the various issues involving the adoption of immersive technologies in the healthcare area. Furthermore, the solutions to these emerging challenges and issues have been provided based on an extensive literature study. The results of this study show that immersive technologies have the considerable potential to provide massive support to stakeholders in the healthcare system during current COVID-19 situation and future pandemics., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mugahed A. Al-antari reports financial support and administrative support were provided by Sejong University. Mugahed A. Al-antari reports financial support, administrative support, and article publishing charges were provided by National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

A simplified synthetic approach involving sulfonylation followed by amino group alkylation produced new 2-aminothiazole derivatives. UV/Vis, infrared, and NMR spectroscopies confirmed their structures. Compounds 36 , 22 , 34 , and 35 showed strong inhibition against Jack bean and Bacillus Pasteurii urease, with IC 50 values from 14.06 to 20.21 μM/mL. Compounds 20 , 26 , 21 , 29 , 30 , 31 , and 32 exhibited potent inhibitory effects against α-glucosidase and α-amylase, with IC 50 values between 20.34 and 37.20 μM/mL. Compounds 33 , 26 , and 27 demonstrated potent DPPH scavenging, with IC 50 values around 34.4-39.2 μM/mL. FMO analysis showed compounds 21 , 22 , 24 , and 25 having parallel aromatic ring systems due to π cloud interactions, while compounds 32 and 38 had distinct electronic density distributions. Compound 22 had HOMO and LUMO energy gaps of 5.805 eV, with bromo and fluoro substitutions in compounds 21 and 24 slightly increasing the gaps to 6.089 eV and 6.078 eV, respectively. Nitro groups in compounds 25 and 32 reduced the gaps to 0.384 eV and 1.187 eV. All compounds demonstrated high gastrointestinal absorption, non-permeability to the blood-brain barrier, and optimal skin permeation (Log Kp between -5.83 and -6.54 cm/s). Compounds 22 , 24 , and 38 had promising QED scores of 0.719, 0.707, and 0.860, respectively, with synthetic accessibility scores from 2.057 to 2.517. ADMET predictions indicated minimal toxicity, cardiovascular safety, and significant inhibitory potential for CYP enzymes. Strong in silico binding affinities (binding energies -5.75 to -7.63 kcal/mol) and metabolic stability suggest these derivatives are promising candidates for further drug development., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

The current study goal was to improve mucoadhesive potential and ocular pharmacokinetics of nanoparticles of thiolated xyloglucan (TXGN) containing moxifloxacin (MXF). Thiolation of xyloglucan (XGN) was achieved with esterification with 3-mercaptopropionic acid. TXGN was characterized by NMR and FTIR analysis. The nanoparticles of TXGN were prepared using ionic-gelation method and evaluate the antibacterial properties. TXGN and nanoparticles were determined to possess 0.06 and 0.08 mmol of thiol groups/mg of polymer by Ellman's method. The ex-vivo bioadhesion time of TXGN and nanoparticles was higher than XGN in a comparative assessment of their mucoadhesive properties. The creation of a disulfide link between mucus and TXGN is responsible for the enhanced mucoadhesive properties of TXGN (1-fold) and nanoparticles (2-fold) over XGN. Improved MXF penetration in nanoparticulate formulation (80 %) based on TXGN was demonstrated in an ex-vivo permeation research utilizing rabbit cornea. Dissolution study showed 95 % release of MXF from nanoparticles. SEM images of nanoparticles showed spherical shape and cell viability assay showed nontoxic behavior when tested on RPE cell line. Antibacterial analysis revealed a zone of inhibition of 31.5 ± 0.5 mm for MXF, while NXM3 exhibited an expanded zone of 35.5 ± 0.4 mm (p < 0.001). In conclusion, thiolation of XGN improves its bioadhesion, permeation, ocular-retention and pharmacokinetics of MXF., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The intensification of the Internet of Health Things devices created security concerns due to the limitations of these devices and the nature of the healthcare data. While dealing with the security challenges, several authentication schemes, protocols, processes, and standards have been adopted. Consequently, making the right decision regarding the installation of a secure authentication solution or procedure becomes tricky and challenging due to the large number of security protocols, complexity, and lack of understanding. The major objective of this study is to propose an IoHT-based assessment framework for evaluating and prioritizing authentication schemes in the healthcare domain. Initially, in the proposed work, the security issues related to authentication are collected from the literature and consulting experts' groups. In the second step, features of various authentication schemes are collected under the supervision of an Internet of Things security expert using the Delphi approach. The collected features are used to design suitable criteria for assessment and then Graph Theory and Matrix approach applies for the evaluation of authentication alternatives. Finally, the proposed framework is tested and validated to ensure the results are consistent and accurate by using other multi-criteria decision-making methods. The framework produces promising results such as 93%, 94%, and 95% for precision, accuracy, and recall, respectively in comparison to the existing approaches in this area. The proposed framework can be picked as a guideline by healthcare security experts and stakeholders for the evaluation and decision-making related to authentication issues in IoHT systems., (© 2024. The Author(s).)

The research article in hand provides a new mechanism that deals with the investigation of the triangular analytical fuzzy solutions (TAFS) of the two-dimensional fuzzy fractional order wave equation (2-D FFWE) through the Hukuhara conformable fractional derivative (HCFD) along with the concept of [ g H ] and [ g H - p ] differentiability. The mechanism consists of a fuzzy traveling wave method coupled with additive operating splitting (AOS). The procedure for the aforesaid mechanism starts with the extension of the HCFD to the fuzzy conformable fractional derivative (FCFD). Furthermore, some properties of FCFD that play a vital role in this study like, ( [ i - g H ] , [ i i - g H ] , [ i - p ] , [ i i - p ] ) -differentiability, switching point, fuzzy chain rule, and traveling wave method are discussed in detail. Further, fuzzy traveling wave method coupled with the procedure of the additive operating splitting (AOS) method is adopted to investigate the triangular analytical fuzzy solution of the Two-dimensional fuzzy wave equation (2-D FWE). Finally, some examples are provided that support our arguments., Competing Interests: There does not exist conflict of interest, (© 2024 The Author(s).)

Flurbiprofen (FBP), a nonsteroidal anti-inflammatory drug (NSAID), is commonly used to treat the pain of rheumatoid arthritis, but in prolonged use it causes gastric irritation and ulcer. To avoid these adverse events of NSAIDs, the simultaneous administration of H 2 receptor antagonists such as ranitidine hydrochloride (RHCl) is obligatory. Here, we developed composite oral fast-disintegrating films (ODFs) containing FBP along with RHCl to provide a gastroprotective effect as well as to enhance the solubility and bioavailability of FBP. The ternary solid dispersion (TSD) of FBP was fabricated with Syloid ® 244FP and poloxamer ® 188 using the solvent evaporation technique. The synthesized FBP-TSD (coded as TSD) was loaded alone (S1) and in combination with plain RHCl (S2) in the composite ODFs based on hydroxypropyl methyl cellulose E5 (HPMC E5). The synthesized composite ODFs were evaluated by in vitro (thickness, folding endurance, tensile strength, disintegration, SEM, FTIR, XRD and release study) and in vivo (analgesic, anti-inflammatory activity, pro-inflammatory cytokines and gastroprotective assay) studies. The in vitro characterization revealed that TSD preserved its integrity and was effectively loaded in S1 and S2 with optimal compatibility. The films were durable and flexible with a disintegration time ≈15 s. The release profile at pH 6.8 showed that the solid dispersion of FBP improved the drug solubility and release when compared with pure FBP. After in vitro studies, it was observed that the analgesic and anti-inflammatory activity of S2 was higher than that of pure FBP and other synthesized formulations (TSD and S1). Similarly, the level of cytokines (TNF-α and IL-6) was also markedly reduced by S2. Furthermore, a gastroprotective assay confirmed that S2 has a higher safety profile in comparison to pure FBP and other synthesized formulations (TSD and S1). Thus, composite ODF (S2) can effectively enhance the FBP solubility and its therapeutic efficacy, along with its gastroprotective effect.

Droughts and prevailing arid conditions have a significant impacts on the natural environment, agriculture, and human life. To analyze the regional characteristics of drought in Baluchistan province, the aridity index (AI) and standardized potential evapotranspiration index (SPEI) were used in. The study analyzed the rainfall, temperature, and potential evapotranspiration (PET) data and the same were used for the calculation of AI as well as SPEI to find out the drought spells during the study period. The linear regression and Mann-Kendall test were applied to calculate the trend in AI as well as in SPEI results. The AI results revealed that most of the meteorological stations are arid and semi-arid, where the highest increasing aridity is noted at Kalat (0.0065/year). The results of the SPEI at 1 and 6-months identified the extreme to severe drought spell during 1998-2002 in all meteorological stations of Baluchistan province. The distinct drought spells identified from the SPEI results were in the years 1998-2003, 2006-2010, 2015-2016 and 2019. The drought frequency results showed highest frequency percentage at Lasbella (46%) of extreme to severe drought. The Mann-Kendall trend results showed negative trend in monthly AI and 1-month SPEI results and most significant trend was observed in April and October months, this shows that aridity and drought in the region are decreasing to some extent except Dalbandin and Lasbella observed increasing trend in winter season (November to January months) and Kalat met-station observed increasing trend in June. Prior investigation and planning of drought situations can help in controlling the far-reaching consequences on environment and human society., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Rafiq et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The supply chain management (SCM) of COVID-19 vaccine is the most daunting task for logistics and supply managers due to temperature sensitivity and complex logistics process. Therefore, several technologies have been applied but the complexity of COVID-19 vaccine makes the Internet of Things (IoT) a strong use case due to its multiple features support like excursion notification, data sharing, connectivity management, secure shipping, real-time tracking and monitoring etc. All these features can only feasible through choosing and deploying the right IoT platform. However, selection of right IoT platform is also a major concern due to lack of experience and technical knowledge of supply chain managers and diversified landscape of IoT platforms. Therefore, we introduce a decision making model for evaluation and decision making of IoT platforms that fits for logistics and transportation (L&T) process of COVID-19 vaccine. This study initially identifies the major challenges addressed during the SCM of COVID-19 vaccine and then provides reasonable solution by presenting the assessment model for selection of rational IoT platform. The proposed model applies hybrid Multi Criteria Decision Making (MCDM) approach for evaluation. It also adopts Estimation-Talk-Estimation (ETE) approach for response collection during the survey. As, this is first kind of model so the proposed model is validated and tested by conducting a survey with experts. The results of the proposed decision making model are also verified by Simple Additive Weighting (SAW) technique which indicates higher results accuracy and reliability of the proposed model. Similarly, the proposed model yields the best possible results and it can be judged by the precision, accuracy and recall values i.e. 93%, 93% and 94% respectively. The survey-based testing also suggests that this model can be adopted in practical scenarios to deal with complexities which may arise during the decision making of IoT platform for COVID-19 SCM process., (© 2023. Springer Nature Limited.)

The current study focused on the fabrication of a well-designed, biocompatible, physically stable, non-irritating and highly porous gelatin scaffold loaded with controlled-release triamcinolone acetonide (TA) and econazole nitrate (EN) co-loaded into mesoporous silica nanoparticles (EN-TA-loaded MSNs) to provide a better long-lasting antifungal therapeutic effect with minimal unfavorable effects. Optimization of the MSNs-loaded scaffold was performed using central composite rotatable design (CCRD), where the effect of gelatin concentration (X1), plasticizer (X2) and freezing time (X3) on the entrapment of EN (Y1) and TA (Y2) and on the release of EN (Y3) and TA (Y4) from the scaffold were studied. The significant compatibility of all formulation ingredients with both drugs was established from XRD, DSC and FT-IR spectra analyses while SEM and zeta studies represented a very precise unvarying distribution of the loaded MSNs in the porous structure of the scaffold. The stability of the optimized scaffold was confirmed from zeta potential analysis (-16.20 mV), and it exhibited higher entrapment efficiency (94%) and the slower (34%) release of both drugs. During in vitro and in vivo antifungal studies against Candida albicans , the MSNs-loaded scaffold was comparatively superior in the eradication of fungal infections as a greater zone of inhibition was observed for the optimized scaffold (16.91 mm) as compared to the pure drugs suspension (14.10 mm). Similarly, the MSNs-loaded scaffold showed a decreased cytotoxicity because the cell survival rate in the scaffold presence was 89% while the cell survival rate was 85% in the case of the pure drugs, and the MSNs-loaded scaffold did not indicate any grade of erythema on the skin in comparison to the pure medicinal agents. Conclusively, the scaffold-loaded nanoparticles containing the combined therapy appear to possess a strong prospective for enhancing patients' adherence and therapy tolerance by yielding improved synergistic antifungal efficacy at a low dose with abridged toxicity and augmented wound-healing impact.

The COVID-19 pandemic ravaged almost every walk of life but it triggered many challenges for the healthcare system, globally. Different cutting-edge technologies such as Internet of things (IoT), machine learning, Virtual Reality (VR), Big data, Blockchain etc. have been adopted to cope with this menace. In this regard, various surveys have been conducted to highlight the importance of these technologies. However, among these technologies, the role of mobile computing is of paramount importance which is not found in the existing literature. Hence, this survey in mainly targeted to highlight the significant role of mobile computing in alleviating the impacts of COVID-19 in healthcare sector . The major applications of mobile computing such as software-based solutions, hardware-based solutions and wireless communication-based support for diagnosis, prevention, self-symptom reporting, contact tracing, social distancing, telemedicine and treatment related to coronavirus are discussed in detailed and comprehensive fashion. A state-of-the-art work is presented to identify the challenges along with possible solutions in adoption of mobile computing with respect to COVID-19 pandemic. Hopefully, this research will help the researchers, policymakers and healthcare professionals to understand the current research gaps and future research directions in this domain. To the best level of our knowledge, this is the first survey of its type to address the COVID-19 pandemic by exploring the holistic contribution of mobile computing technologies in healthcare area., Competing Interests: We declare that this article has not been published previously and is not simultaneously submitted for publication in another journal or conference. We have no conflicts of interests to disclose., (© 2023 The Author(s).)

The low-temperature sintering of (Bi 0.5 Na 0.5 )TiO 3 -based ceramics can be achieved by sintering aid CuO. Piezoelectric ceramics (1 - x )[0.90(Bi 0.5 Na 0.5 )TiO 3 - 0.10SrTiO 3 ] - x CuO (BNT-ST-Cu) with x = 0, 0.01, 0.02, 0.03, and 0.04 were prepared through the mixed oxide route. A tetragonal structure was indexed for the undoped sample. Its structure was found to be changed to a pseudocubic when Cu was added. For undoped Cu samples, the sintering temperature ( T s ) for sufficient densification was 1160 °C. However, T s was reduced to 1090-1120 °C for Cu-added specimens. Field emission scanning electron microscopy (FE-SEM) showed a uniform and dense grain morphology for all samples. The maximum dielectric constant temperature ( T m ) was decreased with the doping concentration of Cu and applied frequency. The strain was increased with Cu concentration and had the maximum value of 500 pm/V for the sample x = 0.02 with symmetric and slim strain loops., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Explainable artificial intelligence (XAI) is of paramount importance to various domains, including healthcare, fitness, skill assessment, and personal assistants, to understand and explain the decision-making process of the artificial intelligence (AI) model. Smart homes embedded with smart devices and sensors enabled many context-aware applications to recognize physical activities. This study presents XAI-HAR , a novel XAI-empowered human activity recognition (HAR) approach based on key features identified from the data collected from sensors located at different places in a smart home. XAI-HAR identifies a set of new features (i.e., the total number of sensors used in a specific activity), as physical key features selection (PKFS) based on weighting criteria. Next, it presents statistical key features selection (SKFS) (i.e., mean, standard deviation) to handle the outliers and higher class variance. The proposed XAI-HAR is evaluated using machine learning models, namely, random forest (RF), K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), naive Bayes (NB) and deep learning models such as deep neural network (DNN), convolution neural network (CNN), and CNN-based long short-term memory (CNN-LSTM). Experiments demonstrate the superior performance of XAI-HAR using RF classifier over all other machine learning and deep learning models. For explainability, XAI-HAR uses Local Interpretable Model Agnostic (LIME) with an RF classifier. XAI-HAR achieves 0.96% of F-score for health and dementia classification and 0.95 and 0.97% for activity recognition of dementia and healthy individuals, respectively., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Javed, Khan, Alomari, Sarwar, Asim, Almadhor and Khan.)

This study examined how selenium-supplemented diets affected the performance of naked neck chickens. The birds were fed both organic and inorganic selenium at 0.30 ppm, while the control diet did not include any additional selenium. A total of 225 one-day-old naked neck chicks were randomly divided into 3 experimental groups, each of which was replicated 5 times (replicates) and contained 15 birds. This was done using a completely randomized design. The data was collected after growth, meat quality, and blood profile parameters were assessed. The findings showed that the birds fed inorganic selenium in the diet displayed increased (P < 0.05) feed intake followed by those administered organic selenium and the control diet. On the other hand, birds fed organic selenium in the diet showed enhanced body weight gain and better feed conversion ratio (P < 0.05). Similarly, organic selenium supplementation increased (P < 0.05) breast and thigh weight compared to inorganic selenium, but no other metrics, such as dressing percentage, drumstick weight, liver weight, gizzard weight, heart weight, or wing weight, significantly differed between treatments (P > 0.05). When compared to birds fed inorganic Se and control diet, the birds fed organic Se had greater (P < 0.05) blood levels of total protein and globulin. Additionally, it was discovered that organic Se-fed birds had greater (P < 0.05) blood Se concentrations than control and inorganic Se-fed birds. However, no differences between treatments were found in albumin, glucose, cholesterol, triglycerides, or uric acid (P > 0.05). In conclusion, adding Se-enriched yeast, as an organic selenium source, to diets may enhance the poor growth and slaughter characteristics of naked neck chicks without negatively affecting blood chemistry., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

We know that in today's advanced world, artificial intelligence (AI) and machine learning (ML)-grounded methodologies are playing a very optimistic role in performing difficult and time-consuming activities very conveniently and quickly. However, for the training and testing of these procedures, the main factor is the availability of a huge amount of data, called big data. With the emerging techniques of the Internet of Everything (IoE) and the Internet of Things (IoT), it is very feasible to collect a large volume of data with the help of smart and intelligent sensors. Based on these smart sensing devices, very innovative and intelligent hardware components can be made for prediction and recognition purposes. A detailed discussion was carried out on the development and employment of various detectors for providing people with effective services, especially in the case of smart cities. With these devices, a very healthy and intelligent environment can be created for people to live in safely and happily. With the use of modern technologies in integration with smart sensors, it is possible to use energy resources very productively. Smart vehicles can be developed to sense any emergency, to avoid injuries and fatal accidents. These sensors can be very helpful in management and monitoring activities for the enhancement of productivity. Several significant aspects are obtained from the available literature, and significant articles are selected from the literature to properly examine the uses of sensor technology for the development of smart infrastructure. The analytical hierarchy process (AHP) is used to give these attributes weights. Finally, the weights are used with the multi-objective optimization on the basis of ratio analysis (MOORA) technique to provide the different options in their order of importance.

Big data has revolutionized the world by providing tremendous opportunities for a variety of applications. It contains a gigantic amount of data, especially a plethora of data types that has been significantly useful in diverse research domains. In healthcare domain, the researchers use computational devices to extract enriched relevant information from this data and develop smart applications to solve real-life problems in a timely fashion. Electronic health (eHealth) and mobile health (mHealth) facilities alongwith the availability of new computational models have enabled the doctors and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. Digital transformation of healthcare systems by using of information system, medical technology, handheld and smart wearable devices has posed many challenges to researchers and caretakers in the form of storage, minimizing treatment cost, and processing time (to extract enriched information, and minimize error rates to make optimum decisions). In this research work, the existing literature is analysed and assessed, to identify gaps that result in affecting the overall performance of the available healthcare applications. Also, it aims to suggest enhanced solutions to address these gaps. In this comprehensive systematic research work, the existing literature reported during 2011 to 2021, is thoroughly analysed for identifying the efforts made to facilitate the doctors and practitioners for diagnosing diseases using healthcare big data analytics. A set of rresearch questions are formulated to analyse the relevant articles for identifying the key features and optimum management solutions, and laterally use these analyses to achieve effective outcomes. The results of this systematic mapping conclude that despite of hard efforts made in the domains of healthcare big data analytics, the newer hybrid machine learning based systems and cloud computing-based models should be adapted to reduce treatment cost, simulation time and achieve improved quality of care. This systematic mapping will also result in enhancing the capabilities of doctors, practitioners, researchers, and policymakers to use this study as evidence for future research., (© 2022. The Author(s).)

The purpose of the study was to devise the superporous hydrogels (SPHs) of mefenamic acid (MA) to acquire the sustained action of the MA in the body. The superporous hydrogels of mefenamic acid were formulated by employing the gas blowing method. The central composite rotatable design (CCRD) was applied to optimize the effect of independent formulation factors like acrylic acid (AC), HPMC and glycerol (GLY) over dependent variables like porosity, viscosity, drug content and swelling ratio of superporous hydrogels in water, phosphate buffer (pH 6.8) and in 0.1N HCl (pH 1.2). A number of characteristics such as void fraction, surface morphology by Scanning electron microscopy (SEM) and in vitro drug release study were governed along with physico-chemical analysis by Fourier transform infrared spectroscopy (FTIR), Differential scanning calorimetry (DSC) and appraised statistically by employing the ANOVA. The comparative analgesic activity of optimized superporous hydrogel formulation SPH17 was also analyzed by using tail flick method. The Fourier transform infrared spectroscopy and Differential scanning calorimetry studies approved the physical compatibility between the polymers and the drug. The Scanning electron microscopy study specified micrographic insight about the structure of formed formulations comprising presence of pores, fibers and drug-hole aggregates. The superporous hydrogels were detected to be low dense as they expressed density lower than 0.75 g/cc. The decrease in concentration of the polymers and cross linker contributed towards the increase in the void fraction of the superporous hydrogel formulations. The optimized formulation SPH 17 exhibited a highly sustained release of MA for up to 10 h in the both 0.1 N HCl and phosphate buffer (66.6%) media. The non-fickian release of drug revealed the coupling of the diffusion and polymer relaxation mechanism of the drug release from the formulations. The obtained outcomes suggested that analgesic effect of SPH 17 was significantly ( p < 0.05) higher than that of simple suspension of mefenamic acid and total analgesic effect duration for superporous hydrogel was also doubled as compared to the duration of analgesic effect produced by drug suspension. The successfully formulated SPH with HPMC K100M as a gelling agent had sustained the action of the mefenamic acid (MF) by improving its poor solubility and permeability. The introduction of inter-penetrating polymeric network (acrylic acid) using glycerol as a cross linker impart increased residence time to superporous hydrogels which ultimately enhanced the feasibility of using superporous hydrogel as oral sustained release devices particularly for gastric retention., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Khan, Aziz, Maheen, Khan, Andleeb, Younis, Haider, Haider, Akhtar and Shafqat.)

The present study is aimed to determine the efficacy and dose response of the nuciferine (1), norcoclaurine (2) and crude extract of Nelumbo nucifera in managements of diabetes, Alzheimer disease and related allergies. Experimentally, alloxan (100 mg/kg body weight (b.w.))-induced diabetic rats (200−250 g) were divided into seven groups (n = 6). Group I: normal control, Group II: diabetic control, Group III: standard treated with glibenclamide and Group lV-VII: treated with methanolic crude extracts (100, 200 mg/kg), nuciferine and norcoclaurine (10 mg/kg b.w.) for 15 days. Different tests were performed, including blood glucose, body weights and antioxidant enzyme assays, i.e., superoxide dismutase (SOD), catalase test (CAT), lipid peroxidation assay (TBARS), glutathione assay (GSH) and acetylcholinesterase (AChE) assay. Nuciferine and norcoclaurine significantly reduced blood glucose (p < 0.05) and restored body weight in diabetic rats. Moreover, nuciferine and norcoclaurine (10 mg/kg) significantly recovered the antioxidant enzymes (SOD, CAT, GPx and GSH) which decreased during induced diabetes. Significant increase in TBARS was also observed in the diabetic group and nuciferine as well as norcoclaurine (10 mg/kg) inhibited the increase in TBARS in diabetic animals (p < 0.05), as compared to glibenclamide. AChE activity was significantly recovered by nuciferine and norcoclaurine (10 mg/kg) both in the blood and brain of the diabetic group (p < 0.05). Nuciferine and norcoclaurine showed potent inhibitory effects against α-glucosidase and α-amylase with IC50, 19.06 ± 0.03, 15.03 ± 0.09 μM and 24.07 ± 0.05, 18.04 ± 0.021 μM, as confirmed by molecular docking studies. This study concludes that nuciferine and norcoclaurine significantly improve memory and could be considered as an effective phytomedicine for diabetes, Alzheimer’s disease (AD) and oxidative stress.

With the quick evolution of medical technology, the era of big data in medicine is quickly approaching. The analysis and mining of these data significantly influence the prediction, monitoring, diagnosis, and treatment of tumor disorders. Since it has a wide range of traits, a low survival rate, and an aggressive nature, brain tumor is regarded as the deadliest and most devastating disease. Misdiagnosed brain tumors lead to inadequate medical treatment, reducing the patient's life chances. Brain tumor detection is highly challenging due to the capacity to distinguish between aberrant and normal tissues. Effective therapy and long-term survival are made possible for the patient by a correct diagnosis. Despite extensive research, there are still certain limitations in detecting brain tumors because of the unusual distribution pattern of the lesions. Finding a region with a small number of lesions can be difficult because small areas tend to look healthy. It directly reduces the classification accuracy, and extracting and choosing informative features is challenging. A significant role is played by automatically classifying early-stage brain tumors utilizing deep and machine learning approaches. This paper proposes a hybrid deep learning model Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) for classifying and predicting brain tumors through Magnetic Resonance Images (MRI). We experiment on an MRI brain image dataset. First, the data is preprocessed efficiently, and then, the Convolutional Neural Network (CNN) is applied to extract the significant features from images. The proposed model predicts the brain tumor with a significant classification accuracy of 99.1%, a precision of 98.8%, recall of 98.9%, and F1-measure of 99.0%., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Alsubai, Khan, Alqahtani, Sha, Abbas and Mohammad.)

Public health is a major concern globally, owing to the presence of industrial dyes in the effluent. Nanoparticles with green synthesis are an enthralling research field with various applications. This study deals with investigating the photocatalytic potential of Fe-oxide nanoparticles (FeO-NPs) for the degradation of methylene blue dye and their potential biomedical investigations. Biosynthesis using Anthemis tomentosa flower extract showed to be an effective method for the synthesis of FeO-NPs. The freshly prepared FeO-NPs were characterized through UV/Vis spectroscopy showing clear peak at 318 nm. The prepared FeO-NPs were of smaller size and spherical shape having large surface area and porosity with no aggregations. The FeO-NPs were characterized using XRD, FTIR, HRTEM, SEM and EDX. The HRTEM results showed that the particle size of FeO-NPs was 60-90 nm. The antimicrobial properties of FeO-NPs were investigated against two bacterial Staphylococcus aureus 13 (±0.8) and Klebsiella pneumoniae 6(±0.6) and three fungal species Aspergillus Niger, Aspergillus flavus, and Aspergillus fumigatus exhibiting a maximum reduction of 57% 47% and 50%, respectively. Moreover, FeO-NPs exhibited high antioxidant properties evaluated against ascorbic acid. Overall, this study showed high photocatalytic, antimicrobial, and antioxidant properties of FeO-NPs owing to their small size and large surface area. However, the ecotoxicity study of methylene blue degradation products showed potential toxicity to aquatic organisms., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The significant proliferation in the mobile health applications (Apps) amidst Coronaviruses disease 2019 (COVID-19) resulted in decision making problems for healthcare professionals, decision makers and mobile users in Pakistan. This decision making process is also hampered by mobile app trade-offs, multiple features support, evolving healthcare needs and varying vendors. In this regard, evaluation model for mobile apps is presented which completes in three different phases. In first phase, features-based criteria is designed by leveraging Delphi method, and twenty (20) mobile apps are selected from app stores. In second stage, empirical evaluation is performed by using hybrid multi criteria decision approaches like CRiteria Importance Through Inter-criteria Correlation (CRITIC) method has been used for assigning weights to criteria features; and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been used for assessment of mobile app alternatives. In last step, decision making is performed to select the best mobile app for COVID-19 situations. The results suggest that proposed model can be adopted as a guideline by mobile app subscribers, patients and healthcare professionals., Competing Interests: None., (© 2022 Elsevier Ltd. All rights reserved.)

The social media has made the world a global world and we, in addition to, as part of physical society, are now part of the virtual society as well. There has been the generation of a large amount of information over the social web. By way of increasing online information, new opportunities emerged, and diverse issues have been raised, which have attracted researchers to address these research problems. In this current age, where online business and e-commerce are part of our daily lives, recommender systems (RSs) are very effective for information filtering. RSs play a significant role in our lives by assisting users in recommending items and services what they may be interesting in to purchase or avail. In this research work, our goal is to predict the users' ratings for various items, which are an active research area in collaborative filtering (CF). In this work, we have explored various similarity measures based on user-user and item-item rating predictions on different datasets by applying collaborative filtering approaches. The comparison of item-item and user-user CF algorithms such as user K-Nearest Neighbour using cosine; similarity, Pearson correlation as well as item-based K-NN using these measures with baseline approaches and matrix-based methods such as Matrix factorization (MF), biased MF, and factor wise MF has been carried out. For empirical-based comparison analysis, diverse approaches have been selected such as slope one, random, and global average, and it revealed that item-item K-NN using Pearson correlation has outperformed all other applied approaches. For the experiments, three real world and widely used datasets of MovieLens 1M, CiaoDVD, and MovieLens 100k have been used. The empirical-based results have been evaluated by using standard performance evaluation measures of RMSE and MAE., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Sofia Nudrat et al.)

Recently, the novel coronavirus disease 2019 (COVID-19) has posed many challenges to the research community by presenting grievous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that results in a huge number of mortalities and high morbidities worldwide. Furthermore, the symptoms-based variations in virus type add new challenges for the research and practitioners to combat. COVID-19-infected patients comprise trenchant radiographic visual features, including dry cough, fever, dyspnea, fatigue, etc. Chest X-ray is considered a simple and non-invasive clinical adjutant that performs a key role in the identification of these ocular responses related to COVID-19 infection. Nevertheless, the defined availability of proficient radiologists to understand the X-ray images and the elusive aspects of disease radiographic replies to remnant the biggest bottlenecks in manual diagnosis. To address these issues, the proposed research study presents a hybrid deep learning model for the accurate diagnosing of Delta-type COVID-19 infection using X-ray images. This hybrid model comprises visual geometry group 16 (VGG16) and a support vector machine (SVM), where the VGG16 is accustomed to the identification process, while the SVM is used for the severity-based analysis of the infected people. An overall accuracy rate of 97.37% is recorded for the assumed model. Other performance metrics such as the area under the curve (AUC), precision, F-score, misclassification rate, and confusion matrix are used for validation and analysis purposes. Finally, the applicability of the presumed model is assimilated with other relevant techniques. The high identification rates shine the applicability of the formulated hybrid model in the targeted research domain., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Khan, Khan and Nazir.)

Phytochemical studies on the alkaloids fraction of the entire plant of Isatis minima Bunge resulted in the alkaloids 1-4 isolation, which were first time isolated from this species. The 1D and 2D NMR spectroscopic data were used to identify their structures, and there was satisfactory compatibility of the data compared to those which were previously published. In the examined compounds 1-4 , Isaindigotidione ( 3 ) and Isaindigotone ( 4 ) were shown as an effective urease inhibitor in such a concentration-dependent way against Jack bean and Bacillus pasteurii urease, with IC 50 values 29.03 ± 0.04, 20.04 ± 0.09 and 34.03 ± 0.07, 26.13 ± 0.08  μ M, respectively. Compounds 3 and 4 were likewise shown to be an effective inhibitor against α -chymotrypsin, exhibiting IC 50 values 16.09 ± 0.07 and 22.01 ± 0.06  μ M, correspondingly. The program MOE-Dock was used to perform a molecular docking analysis to confirm probable binding modes of the active complexes of the isolated compounds 1-4 and the crystal structure of urease and α -chymotrypsin enzymes. Compound 3 was the most active, having the highest docking scores against Bacillus pasteurii urease, α -chymotrypsin, and Jack bean (-8.6876), (-7.6647), and (-13.1927)  μ M, respectively. All four alkaloids ( 1-4 ) showed significant urease and protease inhibitory potential and further these activities were confirmed with the help of molecular docking study., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Fozia Fozia et al.)

Co-encapsulated econazole nitrate-triamcinolone acetonide loaded biocompatible, physically stable, and non-irritating mesoporous silica nanoparticles (EN-TA-loaded MSNs) were prepared and optimized by using a central composite rotatable design (CCRD) for providing better therapeutic efficacy against commonly prevailed resistant fungal infections. These drugs loaded MSNs can significantly overcome the deficiencies and problems like short duration of action, requirement of frequent administration, erythema, and burning sensation and irritation associated with conventional drug delivery systems. The stability of optimized drugs loaded MSNs prepared with 100 gm of oil at pH 5.6 with a stirring time of 2 h was confirmed from a zeta potential value of -25 mV. The remarkable compatibility of formulation ingredients was depicted by X-ray diffraction (XRD), differential scanning calorimetry (DSC), and Fourier transform infrared spectroscopy (FTIR) spectra while scanning electron microscopy (SEM) and size analysis represented a very fine size distribution of nanoparticles ranging from 450-600 nm. The CCRD clearly predicted that the optimized parameters of drugs loaded MSNs have better values of percentage yield (85%), EN release (68%), and TA release (70%). Compared to pure drugs, the decreased cytotoxicity of EN-TA-loaded MSNs was quite evident because they showed a cell survival rate of 90%, while in the case of pure drugs, the survival rate was 85%. During in vivo antifungal testing against Candida albicans performed on three different groups, each consisting of six rabbits, the EN-TA-loaded MSNs were relatively superior in eradicating the fungal infection as a single animal exhibited a positive culture test. Rapid recovery of fungal infection and a better therapeutic effect of EN-TA-loaded MSN were quite evident in wound healing and histopathology studies. Likewise, on the 14th day, a larger inhibitory zone was measured for optimized nanoparticles (15.90 mm) compared to the suspension of pure drugs (13.90 mm). In skin irritation studies, MSNs did not show a grade of erythema compared to pure drugs, which showed a four-fold grade of erythema. As a result, MSNs loaded with combination therapy seem to have the potential of improving patient compliance and tolerability by providing enhanced synergistic antifungal effectiveness at a reduced dose with accelerated wound healing and reduced toxicity of therapeutics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Maheen, Younis, Khan, Salman shafqat, Ali, Rehman, Ilyas, Zafar, Shafqat, Kalam and Al-Ghamdi.)

In the current study, nitrofurazone- (NFZ) and lidocaine-loaded (LD) silica microspheres were fabricated to address pathological indications of skin infections. The microspheres were prepared by the sol-gel method applying the Box-Behnken design and evaluated for size distribution, morphology, zeta potential, physico-chemical compatibility, XRD, thermogravimetric analysis, antibacterial and cytotoxicity activities. The comparative in vitro drug release study of microspheres revealed a 30% release of NFZ and 33% of LD after 8 h. The microspheres showed 81% percentage yield (PY) and 71.9% entrapment efficiency. XRD patterns confirmed the entrapment of NFZ-LD in silica microspheres with a significant reduction in crystallinity of the drugs. Thermal and FTIR studies proved the absence of any profound interactions of the formulation ingredients. The smooth spherical microspheres had a -28 mV zeta potential and a 10-100 µm size distribution. In vitro antibacterial activities of the NFZ-LD microspheres showed an increased zone of inhibition compared to pure drug suspensions. The in vivo efficacy tested on rabbits showed a comparatively rapid wound healing with complete lack of skin irritation impact. The cytotoxicity studies revealed more acceptability of silica microspheres with negligible harm to cells. The study suggests that the NFZ- and LD-loaded silica microspheres would be an ideal system for accelerating and promoting rapid healing of various acute and chronic wounds.

The purpose of the study was to develop an SNEDDS to improve the solubility and bioavailability of pitavastatin. The solubility of pitavastatin in different oils, surfactants, and co-surfactants was determined and a pseudo-ternary phase diagram was constructed. The SNEDDS was characterized by zeta-sizer, zeta-potential, FTIR, DSC, and TGA. Release and permeation of pitavastatin from the SNEDDS was studied for 12 and 24 h, respectively. The lipolysis test, RBC lysis, effect on lipid profile, and pharmacokinetics were studied. The SPC3 formulation showed a 104 ± 1.50 nm particle size, a 0.198 polydispersity index (PDI), and a -29 zeta potential. FTIR, DSC, and TGA showed the chemical compatibility and thermal stability. The release and permeation of pitavastatin from SPC3 was 88.5 ± 2.5% and 96%, respectively. In the lipolysis test, the digestion of SPC3 yielded a high amount of pitavastatin and showed little RBC lysis. The lipid profile suggested that after 35 days of administration of the SNEDDS, there was a marked decrease in TC, LDL, and triglyceride levels. The SNEDDS of SPC3 showed an 86% viability of Caco-2 cells. Pharmacokinetics of SPC3 showed improved values of C max , T max , half-life, MRT, AUC, and AUMC compared to the reference formulation. Our study demonstrated that the SNEDDS effectively enhanced the solubility and bioavailability of a BCS class II drug.