Jinnah University for Women

The rise in antibiotic resistance has created an urgent need for alternative strategies to combat multidrug-resistant (MDR) bacterial infections. Silver nanoparticles (AgNPs) possess unique antibacterial properties, making them a promising option in biomedical applications. This study explores the green synthesis of silver nanoparticles (AgNPs) using Citrus sinensis peel extract and their synergistic potential with cefotaxime against multidrug-resistant (MDR) clinical isolates. For the optimization of AgNPs synthesis, Plackett–Burman experimental design (PBD) was implemented that demonstrated incubation time, temperature and extract: AgNO3 ratio as significant factors. The UV–Vis spectroscopy analysis revealed a characteristic absorbance peak of CS-AgNPs at 470 nm. The size of biosynthesized AgNPs was analyzed using Scanning Electron Microscopy (SEM), that showed size range of 50–60 nm with spherical shaped morphology. Fourier Transform Infrared Spectroscopy (FTIR) analysis found different functional groups involved in the stabilization and capping of AgNPs, as indicated by the peaks at 2925 cm⁻¹, 1630 cm⁻¹, 1100 cm⁻¹ and 1016 cm⁻¹ revealing –CH stretching aliphatic carbon, the carboxyl group, OH group and C–O–C group, respectively. The cytotoxicity of the synthesized CS-AgNPs and its synergistic effect with cefotaxime (CTX) antibiotic was analyzed with MTT assay. The combination of CS-AgNPs and CTX showed significant decrease in cytotoxicity compared to CS-AgNPs alone. Antibacterial activity of CS-AgNPs against MDR clinical isolates was performed using minimum inhibitory concentration (MIC) method. The MIC of CS-AgNPs was observed within 3.125–12.5 µg/ml range. Synergism assay of CS-AgNPs with CTX was also evaluated to determine the fractional inhibitory concentration (FIC) index. Clinical isolates (E. coli), S-11, S-14, S-16, S-19, and S-20 showed FIC in the range of 0.162–0.402 indicating synergism whereas, S-04, S-06, S-10, S-15 and S-21 showed the FIC in the range of 0.644–0.804 indicating the additive effect. The MDR E. coli clinical isolates S-11, S-16, S14, S-19 and S-20 demonstrated 65–85% biofilm inhibition which was significantly (p ≤ 0.001) high in all tested isolates. Significant (p ≤ 0.001) eradication of preformed biofilm in the range of 60–78% was also observed in S-16 clinical isolate.

Background The prevalence of potentially inappropriate medications (PIMs) in older adults populations is a significant concern, often leading to adverse drug events and increased health-care utilization. Objective In the present study, we aim to evaluate the prevalence of PIMs among hospitalized older adults patients in Pakistan using STOPP (Screening Tool of Older Persons’ Prescriptions) criteria version 3. Methodology A prospective observational study was conducted at a tertiary-care hospital in Karachi over 1 year from March 2023 to March 2024. Patients aged 60 years and above, prescribed at least one medication, were included. Data on demographics, comorbidities, and medications were collected and analyzed using the STOPP criteria to identify PIMs. Statistical analysis was performed using IBM SPSS Statistics version 21. To find the variables linked to PIM use, multivariable logistic regression analysis was used. The 95% CI and adjusted odds ratio (aOR) were used to measure the statistical association’s strength. A p-value of less than 0.05 was deemed statistically significant. Results Among 450 participants, the median age was 67 years, with a predominance of male patients (55.3%). The prevalence of PIM use was 56.6%, and a total of 388 instances of PIM use were identified according to STOPP criteria version 3. Acetylsalicylic acid (18%) and pheniramine (11%) were the most frequent inappropriately prescribed medications. The multivariable logistic regression analysis revealed that polypharmacy and the presence of one or more comorbidities primarily influence the PIM use. Conclusion The findings highlight a critical need for improved prescribing practices in the older adults population in Pakistan. Utilizing screening tools like the STOPP criteria can significantly enhance medication safety and optimize pharmacotherapy in this vulnerable group.

Bioplastics are the polymers synthesized from either microorganisms or they can be manufactured using low cost agricultural biomass. They are gaining considerable attention nowadays due to their biodegradability and provision of utilizing waste material. Bacteria are versatile microorganisms capable of synthesizing a polymer known as Polyhydroxybutyrates (PHBs), which are inclusion bodies that bacteria accumulate as backup materials when they develop under various stressors. PHBs are chosen as substitutes for natural environmental conditions for the manufacturing of biodegradable polymers due to their rapid degradability. This effort aimed to identify putative PHB-synthesizing bacteria and assess PHB productivity with the help of agro-residues as carbon residues. The goal of this investigation was to isolate bacteria that synthesize bioplastic from plastic waste dump soil. Following the collection of soil samples, bacterial strains were isolated using culture-based techniques. Four of the ten isolated bacterial strains were shown to be capable of producing bioplastic. Sudan-black staining was used for bioplastic manufacturing screening. The bacterial strain that has shown to be the hyper-producer of PHB was identified by 16S rDNA sequencing as Bacillus cereus ARD-03. For maximum production of PHB, the optimal pH, temperature, and time course of fermentation were found to be 7.5, 30 °C, and 24 h respectively. When Bacillus cereus ARD-03 was fed on 4 g% of each of the agricultural wastes including sugarcane bagasse, waste paper, and rose petals, weight of PHB produced was calculated as 1.577 g/dL, 0.304 g/dL, and 13.161 g/dL respectively. Fourier Transform Infrared Spectroscopy (FTIR) was used to characterize the isolated polymer that confirmed the production of Polyhydroxybutyrate (PHB). The Bacillus cereus ARD-03 isolated in this study, can be utilized to produce PHB based bioplastic economically from agro-residues that can reduce the cost of and ease the substrates’ disposal issues.

Introduction Alzheimer’s disease is a progressive neurodegenerative disorder challenging early diagnosis and treatment. Recent advancements in deep learning algorithms applied to multimodal brain imaging offer promising solutions for improving diagnostic accuracy and predicting disease progression. Method This narrative review synthesizes current literature on deep learning applications in Alzheimer’s disease diagnosis using multimodal neuroimaging. The review process involved a comprehensive search of relevant databases (PubMed, Embase, Google Scholar and ClinicalTrials.gov), selection of pertinent studies, and critical analysis of findings. We employed a best-evidence approach, prioritizing high-quality studies and identifying consistent patterns across the literature. Results Deep learning architectures, including convolutional neural networks, recurrent neural networks, and transformer-based models, have shown remarkable potential in analyzing multimodal neuroimaging data. These models can effectively process structural and functional imaging modalities, extracting relevant features and patterns associated with Alzheimer’s pathology. Integration of multiple imaging modalities has demonstrated improved diagnostic accuracy compared to single-modality approaches. Deep learning models have also shown promise in predictive modeling, identifying potential biomarkers and forecasting disease progression. Discussion While deep learning approaches show great potential, several challenges remain. Data heterogeneity, small sample sizes, and limited generalizability across diverse populations are significant hurdles. The clinical translation of these models requires careful consideration of interpretability, transparency, and ethical implications. The future of AI in neurodiagnostics for Alzheimer’s disease looks promising, with potential applications in personalized treatment strategies.

Stroke-induced hemiplegia is a major cause of long-term disability, often leading to lower limb deformities and abnormal gait. Ankle-foot orthoses (AFO) have shown effectiveness in improving these conditions, but limited research explores the benefits of combining AFO therapy with balance training. This study aimed to explore the effects of combining balance training exercises with orthotic intervention on various gait characteristics in stroke patients with lower limb paralysis. This randomized controlled trial (RCT) involved 32 patients, 12–18 weeks post-stroke, randomized into two groups: balance training only (n = 16) and balance training with orthotics (n = 16). Gait performance was evaluated at baseline and post intervention using the Timed Up and Go Test (TUG) and 10-Meter Walk Tests. The combination therapy group showed significant improvements in gait parameters. For the 10-Meter Walk Test, the mean pre-intervention speed was 0.31 ± 0.03 m/s, and post-intervention speed was 0.40 ± 0.03 m/s. In the TUG test, mean pre-intervention time was 27.04 ± 2.04 s, and post-intervention time was 20.55 ± 2.30 s (p < 0.05). These improvements were greater than those observed in the balance-only group. The combination of balance training and AFO therapy significantly improves gait in chronic hemiplegic stroke patients. This approach offers a promising rehabilitation strategy to enhance functional mobility and quality of life in stroke survivors.

Objective Potentially inappropriate prescribing is a global health issue with catastrophic consequences in the elderly population. Healthcare providers play a critical role in medication optimisation in elderly patients. The present study aims to explore the perceptions of healthcare professionals (prescribers) regarding the complexities of inappropriate prescribing practices in the elderly population. Design A qualitative study using semistructured interviews was conducted. All the data were transcribed verbatim and analysed via Braun and Clarke’s thematic analysis approach. Setting Prescribers working in a tertiary care hospital in Karachi, Pakistan. Participants Prescribers having more than 5 years of experience in elderly prescribing. Participants were selected using purposive sampling, and recruitment continued until the point of data saturation, meaning no new major themes emerged. Results 13 prescribers, five females and eight males with an average experience of 15.3 years, were interviewed. The interviews lasted for an average of 15 min. The analysis revealed three primary themes: (1) inappropriate prescribing, characterised by knowledge and awareness of inappropriate prescribing and its assessment tools; (2) complexities in elderly prescribing, highlighting patient factors such as comorbidities, polypharmacy, psychological issues and socioeconomic challenges, as well as prescriber factors; and (3) interventions to improve prescribing, emphasising the role of pharmacists in enhancing medication safety, the importance of effective patient–prescriber relationships through counselling and the need for regulatory measures to monitor prescribing behaviours. Inadequate knowledge of standardised assessment tools such as the Screening Tool to Alert to Right Treatment/Screening Tool of Older Persons’ Prescriptions criteria, time constraints faced by prescribers and fragmented healthcare systems were some of the barriers identified by the respondents in medication optimisation for elderly individuals. Conclusion The findings highlight the need for enhanced education on standardised assessment tools and the implementation of targeted interventions. A key recommendation is the integration of clinical pharmacists into care teams to optimise prescribing practices.

Background Web-based pharmacy apps facilitate the electronic exchange of health-related supplies. They are digital platforms that run on websites and smartphones. Pakistan is experiencing significant progress in smartphone integration and digital services, leading to the expansion of the online pharmacy business. However, concerns remain over the legitimacy and precision of these apps. Objective The aim of this study was to undertake a thorough assessment of digital pharmacy apps accessible in Pakistan. Specifically, our focus was on apps accessible via the Google Play Store and the iOS App Store. To fulfill this objective, an evaluation of these apps was performed using the Mobile App Rating Scale (MARS). Methods A research investigation was conducted to analyze the online pharmacy apps in Pakistan. Initially, 50 apps were identified, but 10 were excluded for not meeting pre-established criteria, 10 were excluded for being in languages other than English, and 7 could not be downloaded. All paid and non-English apps were also excluded. A total of 23 apps were selected for the study, acquired via the Google Play Store and iOS App Store. The evaluation was conducted by 2 researchers who maintained independence from one another by using the MARS. Results Initially, 50 apps were identified, of which 27 were excluded for not meeting the predetermined criteria. A total of 23 apps were selected for the study, acquired via the Google Play Store and iOS App Store. Strong positive correlations between higher user engagement and better app functionality and information quality were observed. The average rating of the 23 apps ranged between 2.64 and 4.00 on a scale up to 5. The aesthetics dimension had the highest mean score of 3.6, while the information dimension had the lowest mean score of 3.2. For credibility and reliability, different tests (intraclass correlation, Cohen κ, Krippendorff α, and Cronbach α) on each dimension of the MARS were performed by using SPSS Statistics 27. The intraclass correlation of all MARS dimensions ranged from 0.702‐0.913 (95% CI 0.521‐0.943), the Cohen κ of all MARS dimensions ranged from 0.388‐0.907 (95% CI 0.151‐0.994), the Krippendorff α of all MARS dimensions ranged from 0.705‐0.979 (95% CI 0.657‐0.923), and Cronbach α had a lower score of 0.821 in the information dimension and a higher score of .911 in the subjective quality dimension of the MARS. Conclusion This study evaluated online pharmacy apps in Pakistan by using the MARS. It is the first study on online pharmacy apps in Pakistan. The findings of the evaluation have provided insights into the reliability and efficacy of these apps.

This study investigates the effects of two commercially available enzymes; proteases (Shapeit & Neutrase) and lipases (Lipopan FBG & Lipopan Extra) each at 30, 60, and 90 ppm, on dough rheological properties and cookie quality. Significant gluten breakdown was observed in flour treatment having protease at 90 ppm, reducing the gluten index from 74.0 ± 0.86 (control) to 55.0 ± 0.52 (Shapeit) and 36.0 ± 0.48 (Neutrase). Dough development time (DDT) declined from 5.7 ± 0.067 (control) to 3.9 ± 0.056 min with Shapeit at 90 ppm, whereas it increased for lipase-treated dough upto 6.1 ± 0.058 min especially using Lipopan FBG. Likewise, dough stability time (DST) improved from 7.7 ± 0.14 to 8.2 ± 0.22% in Lipopan FBG (90 ppm) and Lipopan xtra (60 ppm). Visco-amylograph study displayed lesser peak viscosity for dough with protease, whereas lipase treatments revealed steadier change in viscosity. Scanning electron micrographs (SEMs) showed that lipase treatments improved lipid-starch links, but protease disrupted gluten-starch bonding. The sensory test exposed the ideal enzyme levels for improved cookie texture, and overall acceptance was 60 ppm Shapeit or 30 ppm Lipopan FBG addition in wheat flour. These outcomes showed that enzyme applications may provide baking industries to improve product attributes.

Osteoarthritis is the most common condition that results in impairment and has the greatest impact on the medial compartment of the knee joint. To lower medial knee loading (MKL), which helps to lessen discomfort and other symptoms, a number of footwear adjustments are used. This study aimed to compare the effects of two different types of footwear insoles on pain and physical function of knee osteoarthritis patients and their association with walking speed. A double-blinded randomized clinical trial (RCT) was conducted, with trial registration number NCT04536519. Data were recorded at baseline, and after 8, 16, and 24 weeks from 60 medial knee osteoarthritis patients after dividing into two groups: group A received a lateral heel wedge insole (LHWI) with medial arch support, while group B only received lateral heel wedge insole (LHWI). Data was analyzed using one-way analysis of variance (ANOVA) and repeated measures ANOVA. Both groups showed significant reduction in pain and improved physical function and walking speed but more pronounced results were recorded for group A (lateral heel wedge insole with medial arch support). Pearson correlation showed that the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) pain and physical function scores were inversely correlated to walking speed of patient. The study concluded that patients using LHWI with medial arch support insole showed better improvements in knee OA-related pain and physical function as compared to individuals using LHWI alone. Also, the WOMAC pain and physical function scores were negatively correlated to walking speed of individual which shows that patients having low knee pain and less difficulty in physical function walk with high speed.

Due to the significant advantages of nanoparticles over conventional systems, there is growing interest in using them for drug delivery and pharmaceutical research. This is especially relevant for statins, which are primarily used to lower cholesterol but generally have low bioavailability. This paper investigates the use of a single emulsion solvent evaporation method to create the necessary solid lipid nanoparticles (SWLNPs) of sugarcane wax dispersed with atorvastatin (ATV). ATV is a well-known drug for having a low oral bioavailability, particularly because of first-pass metabolism. Sugarcane wax is a biocompatible, economical as well as resourceful raw material and is utilized in this work to synthesis nanoparticles. X-ray diffraction analysis (XRD) revealed that the synthesized nanoparticles had a mean particle size of around 258 nm and a crystallinity of around 60%. In addition to that Fourier transform infrared (FTIR) method of spectroscopy was also carried out to further investigate and characterize the nanoparticles. In order to understand the effects of ATV together with sugarcane wax lipid nanoparticles, in vivo studies in rats were carried out to investigate and find total cholesterol (TC), low-density lipoprotein (LDL), triglycerides (TG), and very low-density lipoprotein (VLDL). The ATV loaded sugarcane wax nanoparticles treatment significantly reduced TC, VLDL, TG, and LDL levels compared to free ATV, demonstrating enhanced anti-hyperlipidemic activity. Overall, ATV loaded sugarcane wax lipid nanoparticles showed improved therapeutic efficiency with a reduced dose. Greenness assessment was performed using AGREE tool revealing excellent greenness of the proposed technique.

There is substantial literature on the association between mental health problems and eczema globally, particularly in Western countries; however, limited research has been conducted in Pakistan. Therefore, this study investigates the relationship between mental health problems (operationalized as anxiety and depression) and psychological well-being among Pakistani adults diagnosed with eczema, aged 18 and over. The study employs a cross-sectional correlational research design and a purposive sampling technique. The assessment tools include the shorter versions of the DASS-21 questionnaire (depression and anxiety subscales to measure depression and anxiety among patients with eczema) and an 18-item psychological well-being questionnaire. Results indicate a positive and significant association between depression and anxiety, while these variables show a negative but non-significant correlation with psychological well-being. Additionally, depression and anxiety negatively (but not significantly) predict psychological well-being. The study highlights key implications for Pakistani adults, such as the role of mental health professionals in raising awareness through seminars, webinars, and workshops. It also emphasizes promoting psychological help-seeking behavior, government initiatives to increase awareness, and the need for psychological intervention services in affected communities, especially in areas lacking resources. Steps must be taken to improve societal welfare by providing adequate mental health facilities.

Aim: This study focuses on the synthesis and evaluation of innovative gold nanoparticles (AuNps) stabilized by short-chain ferulic acid (FA), specifically 4-hydroxy-3-methoxy-cinnamic acid. Methods: We analyzed the size and distribution of FA-TSC-AuNps and FA-NaBH4-AuNps, with the reduction kinetics of Au3 + to Au0. The electronic and optical properties of these AuNps were scrutinized using UV-visible, AFM, and FT-IR. Results: AFM distinctly showcased spherical particles, average diameters of 4 ± 1 nm for FA-TSC-AuNps and 11 ± 1 nm for FA-NaBH4-AuNps systems. In the DPPH assay, the anti-scavenging activity recorded values of: FA at 15.4% ± 0.32, FA-TSC-AuNps at an impressive 86.8% ± 0.32, and FA-NaBH4-AuNps at 61.5% ± 0.22. The ABTS assay yielded results of: FA at 13%, FA-TSC-AuNps at 70.14%, and FA-NaBH4-AuNps at a remarkable 92.8%. Catalytic investigations revealed that both facilitated the swift conversion of p-nitrophenol to p-aminophenol. Additionally successful chemo sensing capabilities were assessed, particularly in relation to ciprofloxacin antibiotic by distinct shift in color signifies the effective detection capability of both sensory systems for the drug. Moreover, with FA-TSC-AuNps exhibiting significant sensitivity toward aluminum. Conclusion: These nanoparticles suggest promising avenues for drug system modifications and enhancements, highlighting their multifaceted potential in both catalytic and chemo sensing applications.

Ephedra intermedia, a medicinally significant plant, is an important component of arid and semi‐arid ecosystems across Central and South Asia. This research sought to predict the present and future distribution of E. intermedia by applying ecological niche modeling (ENM) methods. The model incorporated comprehensive bioclimatic and edaphic variables to predict the species' habitat suitability. The results demonstrated high predictive accuracy, highlighting the importance of temperature seasonality, annual temperature range, soil pH, and nitrogen content as key species distribution determinants. The current habitat suitability map revealed core areas in Afghanistan, Pakistan, and Tajikistan mountain regions. Under future climate change scenarios (SSP2‐4.5 and SSP5‐8.5) for the 2050s and 2070s, the model projected a significant upward and northward shift in suitable habitats, coupled with a notable contraction in the extent of highly suitable areas, particularly under the high‐emission SSP5‐8.5 scenario. The predicted range shifts reflect the species' sensitivity to increasing temperatures and changing precipitation patterns. This suggests a potential loss of suitable habitats in low‐elevation and southern parts of its range. Including edaphic factors in the model provided novel insights, specifically highlighting the critical role of soil properties, such as soil pH and nitrogen content, in shaping the ecological niche of E. intermedia. These findings complement the observed upward and northward shifts in habitat suitability under future climate scenarios, emphasizing the species' reliance on high‐altitude refugia as climate conditions change. The results underscore important implications for conservation planning, suggesting that strategies should prioritize the protection of these refugial habitats while also considering measures such as habitat connectivity and assisted migration to support the species' adaptation to shifting environmental conditions.

This research work explores the role of culture in the nation branding strategies of Japan. By examining key initiatives such as the promotion of traditional culture (culinary traditions) along with contemporary cultural exports (anime), the study highlights the strategic role of culture in nation branding of Japan. Moreover, this paper explores the “Cool Japan” campaign, a strategy to share Japan’s attractiveness and appeal with global audience. This Cool Japan can be considered as the corner stone of the soft power policy of Japan. Through these efforts, Japan not only strengthens its international relations but also fortifies its national identity amidst a rapidly changing global landscape. Thus it is argued in this research work that through cool Japan campaign and cultural diplomacy (traditional and modern) Japan is able to improve its image internationally, achieve its nation cohesion and grow its economy significantly.

Smart warehousing represents a transformative advancement in supply chain management, integrating advanced technologies such as IoT, AI, and robotics to optimize operations and enhance efficiency. However, its adoption in developing economies, particularly in sectors like FMCG, faces significant challenges that require detailed exploration. This study aims to identify and prioritize the barriers to smart warehousing adoption, providing actionable insights for overcoming these obstacles. Focusing on Pakistan’s FMCG sector, a critical industry characterized by high product diversity and rapid turnover, the research offers a unique perspective on adoption challenges in a developing market context. Data were collected from 49 experts in the FMCG sector through a three-point Likert scale questionnaire, capturing perceptions on various barriers. The mean priority value (MPV) approach was employed to quantify these challenges, calculating their relative importance and determining a cut-off value to distinguish high-priority barriers. The analysis revealed key obstacles, including economic uncertainty, integration with legacy systems, skill gaps, workforce resistance, lack of infrastructure, and high capital investment costs. Other significant challenges include cybersecurity concerns, insufficient training programs, and data management complexities. These findings contribute to the literature on smart supply chains by highlighting the unique interplay of technological, organizational, and contextual factors in a developing economy.

New practices, tools, and technologies are revolutionizing supply chain operations, making them more efficient. Cutting-edge technologies such as AI, blockchain, big data, and augmented reality enhance supply chain management procedures. Supply chain organizations are leveraging these technologies to optimize inventory levels, implement smart contracting, enhance traceability and visibility, increase process speed, and improve transparency. This book chapter investigates the technological revolution poised to give supply chain management a competitive edge. It also explores how outdated systems can be modernized and integrated with advanced technology portfolios. Over the next three to five years, digital and advanced supply chain management technologies will assist people with settling on better choices or decision-making. The study examines the impact of past industrial revolutions on the supply chain industry and how they have paved the way for the current technological revolution. It explores the potential opportunities and challenges of the current technological revolution and provides recommendations for organizations to embrace these changes and remain competitive.

Innovation has been a driving force behind the development and adoption of digital technologies in supply chains. The continuous evolution of these technologies has enabled supply chains to become smarter, more efficient, and more responsive to dynamic market conditions. This chapter aims to explore how digitalization, coupled with external sources of open innovation, can drive smart supply chain management. The objectives of this chapter are to understand how leveraging open innovation can facilitate the adoption of these technologies. The chapter also seeks to identify the enablers and barriers to the successful integration of digital technologies in supply chain management. The chapter employs an integrative review of diverse existing literature to analyze the intersection of digital technologies and open innovation in supply chain management. The major findings reveal that digital technologies such as IoT, AI, and Blockchain significantly improve supply chain visibility, efficiency, and adaptability. Furthermore, open innovation plays a crucial role in fostering collaboration and knowledge exchange, leading to more innovative and resilient supply chains. This chapter contributes to the body of knowledge by highlighting the synergistic potential of open innovation and smart supply chain management. It provides insights into how organizations can leverage external knowledge and digital advancements to enhance their supply chain operations and achieve a competitive edge. By addressing these areas, the chapter offers strategic guidance for researchers and practitioners aiming to harness the full potential of digitalization and open innovation in smart supply chain management.

Obesity and associated health alarms have encouraged increased awareness in developing healthier food alternatives, such as low-fat bakery products. This study explores a sustainable plant-based approach to formulate low-fat muffins by partially replacing butter with sago flour at levels of 25, 37, and 50% (w/w). The research designed to assess the physicochemical and pasting properties of wheat-sago flour composites and their impact on the texture, color, post-baking attributes, and sensory characteristics of the muffins. Results presented that the ash content of the fat-reduced muffins significantly improved, increasing from 1.08 to 3.09%. Sago concentration significantly affected solvent retention, swelling, sedimentation properties, pasting temperature, and both peak and breakdown viscosities. At 50% fat replacement, the muffins exhibited increased density and firmness, measuring 32.67 N, compared to full-fat and lower-fat samples. Sensory evaluations by semi-trained assessors rated both full-fat and reduced-fat muffins within the liking range, with scores ranging from 8.52 to 7.42. Lightness values showed no significant difference between full-fat and reduced-fat muffins. These findings suggest that sago flour is an effective partial fat replacer in muffin formulations, enhancing nutritional value while maintaining acceptable sensory qualities, with the 25 and 37% replacements achieving the best balance of properties. Graphical abstract

In an evolutionary era of medical education, “Artificial intelligence” (AI) is applied to replicate human intellect, encompassing abilities, logical reasoning and effective problem-solving skills. Previous research has explored the attitude of medical and dental students, toward the assimilation of AI in medicine; however, a significant gap exists in appraising the understanding and concerns of pharmacy students. Therefore, the current study was designed to explore undergraduate pharmacy students’ perceptions of integrating AI into education and practice. Methods: A cross-sectional study was conducted among final-year pharmacy students from different public and private sector universities in Karachi. The sample size on 60% anticipated response rate and 99% CI was calculated to be 390. Data was collected after acquiring ethical approval using convenient sampling. Frequency and percentage of the socio-demographic features were analyzed and then goodness of fit and Pearson’s chi-squared test of correlation was applied. Results were considered significant when p < 0.05. Results: The overall response rate of the study was 67%. More than 80% of the respondents were female. The students 35% (n = 202) strongly agreed and 59% (n = 334) agreed that AI plays an important role in healthcare, (χ2 = 505.6, p < 0.001). Around 79% (n = 453, χ2 = 384.3, p < 0.001) of students agreed on the replacement of patient care specialties with AI in the future, whereas 495 students (87%, χ2 = 682.3, p < 0.001) stated that they possess a strong comprehension of the fundamental principles governing the operation of AI. More than 80% of the students were comfortable in using AI terminologies (n = 475, χ2 = 598, p < 0.001) and 93% (n = 529, χ2 = 290, p < 0.001) were sure that AI inclusion in pharmacy education will develop a positive influence into the pharmacy curriculum (95%, n = 549, χ2 = 566.9, p < 0.001). A high and positive correlation was observed between the perception and willingness of students to adopt the AI changes in teaching undergraduate students (ρ = 0.491, p < 0.001). Furthermore, the outcomes showed students at private-sector universities stood out in computer literacy compared to public-sector universities (χ2 = 6.546, p < 0.05). Conclusion: The current outcomes revealed the higher willingness of pharmacy students towards AI-infused learning. They understood the prerequisite of having both formal and informal learning experiences on the clinical application, technological constraints, and ethical considerations of the AI tools to be successful in this endeavor. The policymakers must take action to ensure that future pharmacists have a strong foundation of AI literacy and take initiatives to foster the interests and abilities of imminent pharmacists who will spearhead innovation in the field.