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Users' web information needs are increasingly exploratory, seeking to navigate unfamiliar domains and discover knowledge. However, existing search engines struggle with ambiguous queries, leading to irrelevant results. To address this, we propose an architecture that autonomously extracts domain knowledge from initial queries. This system transforms queries into a semantic model, suggesting relevant queries to aid exploration. Evaluated against Google, our architecture achieved 89 % accuracy in automated query recommendation, with 85.4 % system usability and an ''A'' ranking. This approach enhances exploratory search by facilitating clearer, more effective query formulation, thus improving information retrieval for users.

This study investigates the process of isolating and characterizing cellulose from Oil Palm Empty Fruit Bunch (OPEFB) fibers collected from Sime Darby Plantation, Selangor. The OPEFB fibers underwent a sequence of chemical processes including dewaxing, alkali pretreatment and bleaching, to isolate the cellulose. The resulting cellulose was analyzed for its composition, crystallinity and yield of hydrolysis products. Comparative analysis with recent studies indicates that the cellulose content of the isolated fibers falls within the reported range, with relatively lower lignin content suggesting a successful lignin removal during chemical treatments. The crystallinity index of the cellulose significantly increased after the post-treatment, reaching 76.43%, which is higher than some reported values. The hydrolysis of the isolated cellulose from OPEFB yielded levulinic acid (LA) levels comparable to commercial cellulose, with the OPEFB-based cellulose producing an LA yield of 8.98% lower than the 9.73% from commercial cellulose. This study highlights the potential of OPEFB as a viable source of high-quality cellulose for the production of sugars and LA.

Abstract Fernandoa adenophylla, due to the presence of phytochemicals, has various beneficial properties and is used in folk medicine to treat many conditions. This study aimed to isolate indanone derivative from F. adenophylla root heartwood and assess in-vitro anti-inflammatory and anti-diabetic characteristics at varying concentrations. Heat-induced hemolysis and glucose uptake by yeast cells assays were conducted to evaluate these properties. Besides, docking analyses were performed on four molecular targets. These studies were combined with molecular dynamics simulations to elucidate the time-evolving inhibitory effect of selected inhibitors within the active pockets of the target proteins (COX-1 and COX-2). Indanone derivative (10–100 µM) inhibited the lysis of human red blood cells from 9.12 ± 0.75 to 72.82 ± 4.36% and, at 5–100 µM concentrations, it significantly increased the yeast cells’ glucose uptake (5.16 ± 1.28% to 76.59 ± 1.62%). Concluding, the isolated indanone might act as an anti-diabetic agent by interacting with critical amino acid residues of 5′ adenosine monophosphate-activated protein kinase (AMPK), and it showed a binding affinity with anti-inflammatory targets COX-1, COX-2, and TNF-α. Besides, the obtained results may help to consider the indanone derivative isolated from F. adenophylla as a promising candidate for drug delivery, subject to outcomes of further in vivo and clinical studies.

Background: Pistacia chinensis is extensively employed in traditional medicine. This study aimed to isolate and evaluate the therapeutic effects of 3’4’78-tetrahydroxy-3-methoxyflavone from P. chinensis crude extract. Materials and Methods: The study utilized column chromatography for isolation. The plant extract and its isolated compound were assessed for in vivo analgesic (hot plate model), anti-inflammatory (carrageenan-induced paw edema), sedative (open field model), and muscle relaxing properties (inclined plane and traction test). Results: In the thermal-induced analgesic model, a significant analgesic effect was observed for the extract (25, 50, and 100 mg/kg) and the isolated compound (2.5, 5, 10, and 15 mg/kg) at higher doses. The extract (100 mg/kg) significantly prolonged latency time (21.98 seconds) after 120 minutes of administration. The isolated compound elevated the latency time (20.03 seconds) after 30 minutes, remaining significant up to 120 minutes with a latency time of 24.11 seconds. The anti-inflammatory effect showed a reduction in inflammatory reactions by 50.23% (extract) and 67.09% (compound) after the fifth hour of treatment. Both samples demonstrated significant sedative effects, with the extract hindering movement by 54.11 lines crossed compared to the negative control (180.99 lines). The isolated compound reduced the number of lines crossed to 15.23±SEM compared to the negative control. Both samples were also significant muscle relaxants. Docking studies indicated that the compound’s therapeutic effect is due to inhibiting COX and nociceptive pathways. Conclusion: The isolated compound from Pistacia chinensis exhibits significant analgesic, anti-inflammatory, sedative, and muscle relaxing properties, with potential therapeutic applications by inhibiting COX and nociceptive pathways.

This study investigated the potential of blockchain technology to transform Electronic Health Record (EHR) administration, integrity, and security. EHRs store vital health information such as medical history, diagnosis, prescriptions, and imaging findings, which may be shared with healthcare professionals to improve patient care. The existing EHR systems have a centralized framework. These centralized systems have a single point of failure, data management, integrity, and security concerns. Blockchain technology provides a solution to these problems by delivering benefits such as safety, privacy, secrecy, and decentralization. This study presents a framework for adopting blockchain technology in EHR systems, providing a comprehensive, modular, and straightforward approach. Our proposed framework addresses the constraints of existing EHR systems by providing a platform for connected and interoperable EHRs. The proposed blockchain-based patient health records management framework demonstrates the potential to address the limitations of current centralized health records systems. It offers benefits such as data privacy and security, interoperability, audibility, decentralization, and automation through the use of smart contracts. The proposed framework is implemented in Ethereum. The evaluation, i.e., cost and performance results, show that this solution is reasonable and may be used on any blockchain network, whether it is permissioned or permissionless.

The current study was designed to investigate the potential of a synthetic therapeutic agent for better management of pain and inflammation, exhibiting minimal to non-existent ulcerogenic effects. The effect of 1-(2-chlorobenzoyl)-3-(2,3-dichlorophenyl) thiourea was assessed through model systems of nociception and anti-inflammatory activities in mice. In addition, the ulcerogenic potential was evaluated in rats using the NSAID-induced pyloric ligation model, followed by histopathological and biochemical analysis. The test was conducted on eight groups of albino rats, comprising of group I (normal saline), groups II and III (aspirin® at doses of 100 mg/kg and 150 mg/kg, respectively), groups IV and V (indomethacin at doses of 100 mg/kg and 150 mg/kg, respectively), and groups VI, VII, and VIII (lead-compound at 15 mg/kg, 30 mg/kg and 45 mg/kg doses, respectively). Furthermore, molecular docking analyses were performed to predict potential molecular target site interactions. The results showed that the lead-compound, administered at doses of 15, 30, and 45 mg/kg, yielded significant reductions in chemically and thermally induced nociceptive pain, aligning with the levels observed for aspirin® and tramadol. The compound also effectively suppressed inflammatory response in the carrageenan-induced paw edema model. As for the ulcerogenic effects, the compound groups displayed no considerable alterations compared to the aspirin® and indomethacin groups, which displayed substantial increases in ulcer scores, total acidity, free acidity, and gastric juice volume, and a decrease in gastric juice pH. In conclusion, these findings suggest that our test compound exhibits potent antinociceptive, anti-inflammatory properties and is devoid of ulcerogenic effects.

Objective The COVID-19 pandemic accelerated changes to clinical research methodology, with clinical studies being carried out via online/remote means. This mixed-methods study aimed to identify which digital tools are currently used across all stages of clinical research by stakeholders in clinical, health and social care research and investigate their experience using digital tools.Design Two online surveys followed by semistructured interviews were conducted. Interviews were audiorecorded, transcribed and analysed thematically.Setting, participants To explore the digital tools used since the pandemic, survey participants (researchers and related staff (n=41), research and development staff (n=25)), needed to have worked on clinical, health or social care research studies over the past 2 years (2020–2022) in an employing organisation based in the West Midlands region of England (due to funding from a regional clinical research network (CRN)). Survey participants had the opportunity to participate in an online qualitative interview to explore their experiences of digital tools in greater depth (n=8).Results Six themes were identified in the qualitative interviews: ‘definition of a digital tool in clinical research’; ‘impact of the COVID-19 pandemic’; ‘perceived benefits/drawbacks of digital tools’; ‘selection of a digital tool’; ‘barriers and overcoming barriers’ and ‘future digital tool use’. The context of each theme is discussed, based on the interview results.Conclusions Findings demonstrate how digital tools are becoming embedded in clinical research, as well as the breadth of tools used across different research stages. The majority of participants viewed the tools positively, noting their ability to enhance research efficiency. Several considerations were highlighted; concerns about digital exclusion; need for collaboration with digital expertise/clinical staff, research on tool effectiveness and recommendations to aid future tool selection. There is a need for the development of resources to help optimise the selection and use of appropriate digital tools for clinical research staff and participants.

Trans fatty acids are specific unsaturated fats found in processed foods that undergo hydrogenation, leading to hepatic disorders such as metabolic-associated fatty liver disease (MAFLD) and conditions like CVD and CKD. The effects of different food samples containing trans fatty acids (elaidic and oleic acid) on the liver, heart, and kidney through antioxidant enzyme activity were investigated in animal models. Liver function tests (ALT, ALP, AST, and LDH), heart biomarker levels (CPK, TC, HDL, LDL, and triglycerides), and kidney biomarker levels (serum creatinine, blood urea nitrogen, and serum uric acid) were examined in serum of rabbits and the histopathology of liver tissues. Results showed that these biomarkers were more elevated in the Mujahid Ghee group than in the normal control, oleic acid, and Kausar Ghee groups. The concentration of antioxidant markers such as peroxidase, glutathione, catalase, thiobarbituric acid reactive substances, and superoxide dismutase were lower in the Mujahid Ghee group. HPLC showed that Mujahid Ghee had the highest quantified value of elaidic acid among all selected samples. Overall, this study demonstrated that elaidic acid in its purest form aggravated MAFLD in rabbit livers and provoked CVK and CVD.

In recent years, the industrial network has seen a number of high-impact attacks. To counter these threats, several security systems have been implemented to detect attacks on industrial networks. However, these systems solely address issues once they have already transpired and do not proactively prevent them from occurring in the first place. The identification of malicious attacks is crucial for industrial networks, as these attacks can lead to system malfunctions, network disruptions, data corruption, and the theft of sensitive information. To ensure the effectiveness of detection in industrial networks, which necessitate continuous operation and undergo changes over time, intrusion detection algorithms should possess the capability to automatically adapt to these changes. Several researchers have focused on the automatic detection of these attacks, in which deep learning (DL) and machine learning algorithms play a prominent role. This study proposes a hybrid model that combines two DL algorithms, namely convolutional neural networks (CNN) and deep belief networks (DBN), for intrusion detection in industrial networks. To evaluate the effectiveness of the proposed model, we utilized the Multi-Step Cyber Attack (MSCAD) dataset and employed various evaluation metrics.

Inflammation is a protective response to a variety of infectious agents. To develop a new anti-inflammatory drug, we explored a pharmacologically important thiazole scaffold in this study. In a multi-step synthetic approach, we synthesized seven new thiazole derivatives (5a–5g). Initially, we examined the in vitro anti-inflammatory potentials of our compounds using COX-1, COX-2, and 5-LOX enzyme assays. After in vitro confirmation, the potential compounds were subjected to in vivo analgesic and anti-inflammatory studies. The hot plate method was used for analgesia, and carrageenan-induced inflammation was also assayed. Overall, all our compounds proved to be potent inhibitors of COX-2 compared to celecoxib (IC50 0.05 μM), exhibiting IC50 values in the range of 0.76–9.01 μM .Compounds 5b, 5d, and 5e were dominant and selective COX-2 inhibitors with the lowest IC50 values and selectivity index (SI) values of 42, 112, and 124, respectively. Similarly, in the COX-1 assay, our compounds were relatively less potent but still encouraging. Standard aspirin exhibited an IC50 value of 15.32 μM. In the 5-LOX results, once again, compounds 5d and 5e were dominant with IC50 values of 23.08 and 38.46 μM, respectively. Standard zileuton exhibited an IC50 value of 11.00 μM. Based on the COX/LOX and SI potencies, the compounds 5d and 5e were subjected to in vivo analgesic and anti-inflammatory studies. Compounds 5d and 5e at concentrations of 5, 10, and 20 mg/kg body weight were significant in animal models. Furthermore, we explored the potential role of compounds 5d and 5e in various phlogistic agents. Similarly, both compounds 5d and 5e were also significantly potent in the anti-nociceptive assay. The molecular docking interactions of these two compounds with the target proteins of COX and LOX further strengthened their potential for use in COX/LOX pathway inhibitions.

Objective: Traditionally, Olea ferruginea Royle (Oleaceae) has been used as a painkiller and antidiabetic in various ailments. To provide a scientific background to this folklore the current study was designed to anti-inflammatory and antidiabetic effects of one of the isolated compound from this plant. Methods: Ferruginan A was isolated from the ethyl acetate extract of Olea ferruginea bark. This isolated molecule was subjected to in-vitro anti-inflammatory and antidiabetic effects using HRBCs and glucose uptake tests. The compound was also tested for molecular docking and ADMET study. Results: Regarding the anti-inflammatory effect, the tested compound demonstrated a 69.82 % inhibition at a concentration of 100 µg/mL, while the Ferruginan A (100 µl/mL) increased the uptake of glucose (3.79–71.86 %) in the yeast cell. Similarly, the zone of inhibition values of Ferruginan A (24.98 mm) against Escherichia coli were found to be comparable to standard (Imipenem: 31.09 mm). The mechanism of antidiabetic and anti-inflammatory effects was explored by using docking simulations performed on four molecular targets related to diabetes and inflammation. The results showed that the isolated compound may act as an antidiabetic agent by inhibiting the 5′ Adenosine monophosphate-activated protein kinase (AMPK). While it also showed inhibition of anti-inflammatory targets COX-1, COX-2, and Tumor necrosis factor alpha (TNF-α). The ADMET prediction study revealed that isolated compound possesses favorable ADMET profile. Conclusion: It was concluded that Ferruginan A might be a significant anti-inflammatory and antidiabetic molecule.

Medicinal plants are the main source of active chemical constituents responsible for curing or mitigating various ailments. To discover new, safe, and effective drug candidates the isolation and screening of natural products are essential. In the current research work, lapachol was isolated from Fernandoa adenophylla, which was evaluated for anti-inflammatory effect followed by molecular docking. The isolated compound was tested for anti-inflammatory effects using in vitro (HRBC assay) and in vivo (xylene-induced ear edema) experimental models. Various concentrations of lapachol demonstrated anti-inflammatory effects with a percent potential of 77.96 at 100 μM. Different concentrations of Lapachol demonstrated a dose-dependent anti-edematous effect with a maximum percent effect of 77.9 % at a higher dose. The histopathological study revealed that the application of xylene led to a significant increase in ear thickness, along with clear signs of ear edema and infiltration of inflammatory cells, as well as epidermal hyperplasia of the dermis when compared to the control group. However, treatment with the investigated compound showed a significant reduction in ear thickness and pathological differences comparable to those observed in the group treated with diclofenac. Density functional theory calculations are accomplished to gain insight into structural and spectroscopic properties. Geometry optimization, FMO, and MEP analyses are performed. Overall, the molecular docking results indicate that lapachol has potential as a COX inhibitor by binding to the active sites of both COX-1 and COX-2 enzymes.

Isoxazole belongs to the class of five-membered heterocyclic compounds. The process of developing new drugs has significantly gained attention due to inadequate pharmacokinetic and safety attributes of the available drugs. This study aimed to design a new diverse array of ten novel isoxazole derivatives via Claisen Schmidt condensation reaction. In vitro COX-1/2 anti-inflammatory assay, in silico molecular docking of potent compounds, Molecular docking simulation, and SwissADME pharmacokinetic profile were investigated in this research. The in vitro COX-1 and COX-2 enzyme inhibitory assay showed that almost all the tested compounds exhibited anti-inflammatory effects whereas C6, C5, and C3 were found to be the most potent COX-2 enzyme inhibitors among the tested compounds and are good candidates for selective COX-2 inhibitors. In silico molecular docking studies coupled with molecular dynamic simulation has been done to rationalize the time-evolved mode of interaction of selected inhibitor inside the active pockets of target COX-2. The binding orientations and binding energy results also showed the selectivity of compounds towards COX-2. Physicochemical properties, pharmacokinetic profile, lipophilicity, water solubility, drug metabolism, drug-likeness properties, and medicinal chemistry of the synthesized isoxazole derivatives were assessed. The SwissADME (absorption, distribution, metabolism, and excretion) database was used to assess the physicochemical properties and drug-likeness properties of the synthesized isoxazole derivatives. All the compounds were shown high GI absorption except Compound 7 (C7). Compound 1 (C1) and Compound 2 (C2) were found to cross the blood-brain barrier (BBB). Lipinski’s rule of five is not violated by any of the ten synthesized isoxazole derivatives. It was predicted with the SwissADME database that C2, C5, C6, C7, and C8 are potent inhibitors of cytochrome (CYP) subtype CYP-2C19. A subtype of CYP-2C9 was inhibited by C4 and C7. The medicinal chemistry of all the compounds C1-C10 showed no PAIN (Pan assay interference compounds) alerts. The improved gastrointestinal (GI) absorption and BBB permeability of C1 and C2 can provide a future prospective for new researchers in the medicinal field to investigate the compounds for the management of chronic diseases. The synthesized isoxazole compounds showed excellent in vitro COX-1/2 enzymes anti-inflammatory investigations, in silico studies, good physicochemical properties, and improved pharmacokinetic profile which will be further investigated via in vivo anti-inflammatory activities. Moreover, to further support our findings of the computational research and in vitro studies, an in-vivo pharmacokinetic profile is suggested in the future.

Nowadays, the growth of multimedia content over the web is exponential. The fingerprints are inconspicuously embedded in multimedia content. The fingerprints can be exploited to trace divergent information from multimedia resources. Sampling fingerprints, particularly from multimedia resources, is challenging since they are complex, heterogeneous, and diverse. This research proposed an approach to sample fingerprints from multimedia resources. Our approach partitions the multimedia content space into converged clusters using variations of Canberra distance and identifies the most diverged samples using Kullback-Leibler (KL) divergence. The resultant clusters represent the information belonging to particular concepts and the diverged samples within the clusters represent multimedia fingerprints. The fingerprint sampling process is leveraged using unsupervised learning algorithms, instantiated across various multimedia descriptors, and tested over standard multimedia datasets. The average results obtained over various standard visual and acoustic datasets reveal 80%, 77%, and 78% accuracy, precision, and recall, respectively, surpassing most of the existing baseline clustering methods such as K-Means, Mean-Shift, and DBSCAN. Furthermore, the rigorousness of the proposed algorithm clustering is evaluated using the internal clustering stability silhouette coefficient and the fingerprint diversity scores. The results unveil a maximum of 94% diversity score. The proposed variation of Canberra distance and KL divergence provides the most stable performance (SD=0.02) and creates promising implications in future multimedia retrieval, summarization, and exploration activities.

Abstract Nano-biotechnology-based clinical applications to cure health-related issues have gained huge attention among the scientific community and hold great promise to limit cancer metastasis. In this study, green-derived silver nanoparticles were synthesized by using leaf extract of Litchi chinensis. Characterization of biosynthesized silver nanoparticles was performed by using UV–Vis spectroscopy, FTIR, XRD, EDS, and SEM analysis. The clinical application of green-drive nanoparticles was investigated by using MCF-7 cancer cell lines. MCF-7 breast cancer cell lines were analyzed against three different treatments. (i) Silver nanoparticles (AgNPs), (ii) miR34a mimics and (iii) Co-delivery of AgNPs and miR34a mimics. Cell viability was determined by MTT assay and, extraction of mRNA and cDNA synthesis were performed after successful cellular transfection. qRT-PCR was done for expression analysis of DR4 and DR5 upon exogenous delivery of all 3 treatments. Results indicate that L. chinensis leaves have a significant amount of phenolic and flavonoid contents and also possess massive antioxidant activity. The diameter of nanoparticles was observed in the range of 41–55 nm. It was concluded that green-derived silver nanoparticles can be a potential contributing agent for cancer prevention and are reported to upregulate the expression of DR4 and DR5 by 0.8-folds and 3.7-folds, respectively.

The existing image search engines allow web users to explore images from the grids. The traditional interaction is linear and lookup-based. Notably, scanning web search results is horizontal-vertical and cannot support in-depth browsing. This research emphasizes the significance of a multidimensional exploration scheme over traditional grid layouts in visually exploring web image search results. This research aims to antecedent the implications of visualization and related in-depth browsing via a multidimensional cubic graph representation over a search engine result page (SERP). Furthermore, this research uncovers usability issues in the traditional grid and 3-dimensional web image search space. We provide multidimensional cubic visualization and nonlinear in-depth browsing of web image search results. The proposed approach employs textual annotations and descriptions to represent results in cubic graphs that further support in-depth browsing via a search user interface (SUI) design. It allows nonlinear navigation in web image search results and enables exploration, browsing, visualization, previewing/viewing, and accessing images in a nonlinear, interactive, and usable way. The usability tests and detailed statistical significance analysis confirm the efficacy of cubic presentation over grid layouts. The investigation reveals improvement in overall user satisfaction, screen design, information & terminology, and system capability in exploring web image search results.

The treatment of living organisms is a critical aspect of various environmental and industrial applications, ranging from wastewater treatment to aquaculture. In recent years, algal-based hollow fiber membrane bioreactors (AHFMBRs) have emerged as a promising technology for the sustainable and efficient treatment of living organisms. This review provides a comprehensive examination of AHFMBRs, exploring their integration with algae and hollow fiber membrane systems for diverse applications. It also examines the applications of AHFMBRs in various areas, such as nutrient removal, wastewater treatment, bioremediation, and removal of pharmaceuticals and personal care products. The paper discusses the advantages and challenges associated with AHFMBRs, highlights their performance assessment and optimization strategies, and investigates their environmental impacts and sustainability considerations. The study emphasizes the potential of AHFMBRs in achieving enhanced nutrient removal, bioremediation, and pharmaceutical removal while also addressing important considerations such as energy consumption, resource efficiency, and ecological implications. Additionally, it identifies key challenges and offers insights into future research directions. Through a systematic analysis of relevant studies, this review aims to contribute to the understanding and advancement of algal-based hollow fiber membrane bioreactors as a viable solution for the treatment of living organisms.

Abstract Aim The study was planned to investigate the phytochemicals, antidiabetic and antioxidant studies of A. consanguineum. Methods The preliminary studies were performed on crude extract and different solvent fractions. Based on the potency, the chloroform fraction was semi-purified to phyto-fractions CHF-1 – 5. Furthermore, CHF-3 was subjected to isolation of pure compounds using column chromatography. The α-glucosidase, α-amylase and antioxidant assays (DPPH, ABTS, H2O2) were performed on all samples. The in-vivo experiments on compounds 1 and 2 were also performed using oral glucose tolerance test. Docking studies were performed on α-glucosidase and α-amylase targets. Results Among all fractions, the chloroform fraction exhibited excellent activities profile giving IC50 values of 824, 55, 117, 58 and 85 μg/ml against α-glucosidase, α-amylase, DPPH, ABTS and H2O2 targets respectively. Among the five semi-purified chloroform phyto-fractions (CHF-1-5), CHF-3 was the leading fraction in activities giving IC50 values of 85.54, 61.19 and 26.58 μg/ml against α-glucosidase, α-amylase and DPPH respectively. Based on the overall potency and physical amount of CHF-3, it was subjected to purification to get compounds 1 and 2. The two compounds were also found potent in in-vitro activities. The observed IC50 values for compound 1 were 7.93, 28.01 and 6.19 μg/ml against α-glucosidase, α-amylase and DPPH respectively. Similarly, the compound 2 exhibited IC50 of 14.63, 24.82 and 7.654 μg/ml against α-glucosidase, α-amylase and DPPH respectively. Compounds 1 and 2 were potent in decreasing the blood glucose levels in experimental animals. Compounds 1 and 2 also showed interactions with the respective enzymes with molecular docking. Conclusions We can conclude that A. Consanguineum is a rich source of natural antidiabetic agents. Bioguided isolation of compound 1 and 2 showed potential inhibitions in all tested in-vitro antidiabetic targets. Further, both the compounds were also able to decrease the blood glucose levels in experimental animals.

Sugar palm (Arenga Pinnata) fiber is abundant in Malaysia which necessitates its utilization as a source of agricultural waste for industrial development. This paper aims at characterizing the sugar palm fiber to explore its silica content as a potential renewable material. The sugar palm fiber was carbonized, and the ash obtained was characterized via X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), energy dispersive spectroscopy (EDS) and field emission scanning electron microscope (FESESM). The presence of amorphous silica (SiO2) with an average particle size of 41.25 nm was revealed by X-ray diffraction. Fourier transform infrared spectroscopy indicated the presence of functional groups such as silane and siloxane groups, and thermogravimetric analysis and differential scanning calorimetry identified the main degradation stages of the sugar palm fiber ash, and the decomposition of hemicellulose, lignin, cellulose, and carbonate to other oxides. The energy dispersive spectroscopy of the sugar palm fiber ash confirmed silica to be of the highest amount than other elements. Sugar palm fiber ash has been found as a possible silica substitute and a prospective industrial resource.

Alzheimer’s disease (AD) is a complex, multifactorial and most prevalent progressive neurodegenerative ailment. Its multifactorial and complex nature causes the lack of disease modifying drugs. Hence, multi-target drug design strategies have been adopted to halt the progression of AD. In current research, we applied multitarget strategy to tackle multifactorial nature of AD. Rational design and synthesis of framework of hybrids containing Pyrimidine/pyrrolidine-sertraline scaffolds were carried out. The synthesized compounds were further evaluated for their in-vitro enzyme inhibition potential against cholinesterases, monoamine oxidases and β-site amyloid precursor protein cleaving enzyme-1 (BACE-1). Compound 19 emerged as an optimal multipotent hybrid with IC50 values of 0.07 µM, 0.09 µM, 0.63 µM, 0.21 µM and 0.73 µM against AChE, BChE, MAO-A, MAO-B and BACE-1 respectively. After in-vivo cytotoxicity and in-vitro PAMPA blood brain barrier permeation assays, a number of widely used behavioral assessment tests were also performed for the evaluation of memory and learning.Determination of biochemical parameters showed low levels of acetylcholinesterase by the treatment with synthesized compounds. Furthermore, levels of neurotransmitters such as serotonin, dopamine and noradrenaline were also analyzed. Increased neurotransmitter levels showed the improved short and long-term memory as well as enhanced learning behavior. Docking studies on the target enzymes showed correlation with the experimental in-vitro enzyme inhibition results.

The presence of ammonium ions in urine, along with basic pH in the presence of urease-producing bacteria, promotes the production of struvite stones. This causes renal malfunction, which is manifested by symptoms such as fever, nausea, vomiting, and blood in the urine. The involvement of urease in stone formation makes it a good target for finding urease enzyme inhibitors, which have the potential to be developed as lead drugs against kidney stones in the future. The documented ethnopharmacology of coumarin 2-one against bacterial, fungal and viral strains encouraged us to synthesize new derivatives of coumarins by reacting aromatic aldehydes with 4-aminocoumarin. The synthesized compounds (2a to 11a) were evaluated for their antimicrobial, in vitro, and in silico properties against the urease enzyme. The study also covers in vivo determination of the synthesized compounds with respect to different types of induced ulcers. The molecular docking study along with extended MD simulations (100 ns each) and MMPBSA study confirmed the potential inhibitory candidates as evident from computed ∆Gbind (3a = −11.62 and 5a = −12.08 Kcal/mol) against the urease enzyme. The in silico analyses were augmented by an enzymatic assay, which revealed that compounds 3a and 5a had strong inhibitory action, with IC50 of 0.412 µM (64.0% inhibition) and 0.322 µM (77.7% inhibition), respectively, compared to standard (Thiourea) with 82% inhibition at 0.14 µM. Moreover, the most active compound, 5a, was further tested in vivo for antiulcer activity by different types of induced ulcers, including pyloric ligation-, ethanol-, aspirin-, and histamine-induced ulcers. Compound 5a effectively reduced gastric acidity, lipid peroxidation, and ulceration in a rat model while also inhibiting gastric ATPase activity, which makes it a promising candidate for ulcer treatment. As a result of the current research, 3a and 5a may be used as new molecules for developing potent urease inhibitors. Additionally, the compound 3a showed antibacterial activity against Staphylococcus aureus and Salmonella typhimurium, with zones of inhibition of 41 ± 0.9 mm and 35 ± 0.9 mm, respectively. Compound 7a showed antibacterial activity against Staphylococcus aureus and Salmonella typhimurium, with zones of inhibition of 30 ± 0.8 mm and 42 ± 0.8 mm, respectively. These results prove that the synthesized compounds also possess good antibacterial potential against Gram-positive and Gram-negative bacterial strains.

The effectiveness of all antibiotics in the β-lactam group to cure bacterial infections has been impaired by the introduction of the New Delhi Metallo-β-lactamase (NDM-1) enzyme. Attempts have been made to discover a potent chemical as an inhibitor to this enzyme in order to restore the efficacy of antibiotics. However, it has been a challenging task to develop broad-spectrum inhibitors of metallo-β-lactamases. Lack of sequence homology across metallo-β-lactamases (MBLs), the rapidly evolving active site of the enzyme, and structural similarities between human enzymes and metallo-β-lactamases, are the primary causes for the difficulty in the development of these inhibitors. Therefore, it is imperative to concentrate on the discovery of an effective NDM-1 inhibitor. This study used various in silico approaches, including molecular docking and molecular dynamics simulations, to investigate the potential of phytochemicals to inhibit the NDM-1 enzyme. For this purpose, a library of about 59,000 phytochemicals was created from the literature and other databases, including FoodB, IMPPAT, and Phenol-Explorer. A physiochemical and pharmacokinetics analysis was performed to determine possible toxicity and mutagenicity of the ligands. Following the virtual screening, phytochemicals were assessed for their binding with NDM-1using docking scores, RMSD values, and other critical parameters. The docking score was determined by selecting the best conformation of the protein–ligand complex. Three phytochemicals, i.e., butein (polyphenol), monodemethylcurcumin (polyphenol), and rosmarinic acid (polyphenol) were identified as result of pharmacokinetics and molecular docking studies. Furthermore, molecular dynamics simulations were performed to determine structural stabilities of the protein–ligand complexes. Monodemethylcurcumin, butein, and rosmarinic acid were identified as potential inhibitors of NDM-1 based on their low RMSD, RMSF, hydrogen bond count, average Coulomb–Schrödinger interaction energy, and Lennard–Jones–Schrödinger interaction energy. The present investigation suggested that these phytochemicals might be promising candidates for future NDM-1 medication development to respond to antibiotic resistance.

Due to growing environmental awareness and demands, many efforts were implemented for the transformation of waste materials into highly efficient adsorption capacity materials. In this work, efforts were made to convert the Sindh clay and quartz into an efficient composite for dye removal from polluted water. The synthesized composites were characterized using FT-IR, BET, SEM, and XRD. The synthesized composite showed a crystalline structure with specific characteristics, including a specific surface area of 7.20 m2/g and a pore diameter of 3.27 nm. The formation of iron cyanide hydrate (2030 cm−1) and iron oxides (418 cm−1) were depicted through Fourier transform infrared spectroscopy analysis. The micrographs obtained show that the unmodified quartz sample has a flattened and elongated shape compared to the modified quartz sample, which has aggregated and coarse morphology. The effects of several factors, such as temperature, contact time, and initial dye concentration, were studied. Kinetic models were also applied to determine the probable route of the adsorption process. For adsorption equilibrium analysis, the Dubinin–Radushkevich, Langmuir, Freundlich, Temkin, and Harkin–Juraisotherm models were employed. The Freundlich isotherm model and pseudo-first-order model best described the adsorption of dyes onto the clay composites. R2 values were close to 1 or more than 0.9, showing which equation fits the experimental data. The produced composite demonstrated good reusability, maintaining over 90% of the adsorption capacity after five reaction cycles without the need for reactivation.

Hypertensive retinopathy (HR) and diabetic retinopathy (DR) are retinal diseases closely associated with high blood pressure. The severity and duration of hypertension directly impact the prevalence of HR. The early identification and assessment of HR are crucial to preventing blindness. Currently, limited computer-aided methods are available for detecting HR and DR. These existing systems rely on traditional machine learning approaches, which require complex image processing techniques and are often limited in their application. To address this challenge, this work introduces a deep learning (DL) method called HDR-EfficientNet, which aims to provide an efficient and accurate approach to identifying various eye-related disorders, including diabetes and hypertensive retinopathy. The proposed method utilizes an EfficientNet-V2 network for end-to-end training focused on disease classification. Additionally, a spatial-channel attention method is incorporated into the approach to enhance its ability to identify specific areas of damage and differentiate between different illnesses. The HDR-EfficientNet model is developed using transfer learning, which helps overcome the challenge of imbalanced sample classes and improves the network’s generalization. Dense layers are added to the model structure to enhance the feature selection capacity. The performance of the implemented system is evaluated using a large dataset of over 36,000 augmented retinal fundus images. The results demonstrate promising accuracy, with an average area under the curve (AUC) of 0.98, a specificity (SP) of 96%, an accuracy (ACC) of 98%, and a sensitivity (SE) of 95%. These findings indicate the effectiveness of the suggested HDR-EfficientNet classifier in diagnosing HR and DR. In summary, the HDR-EfficientNet method presents a DL-based approach that offers improved accuracy and efficiency for the detection and classification of HR and DR, providing valuable support in diagnosing and managing these eye-related conditions.

In the contemporary digital landscape, web search functions as a pivotal conduit for information dissemination. Nevertheless, blind users (BUs) encounter substantial barriers in leveraging online services, attributable to intrinsic deficiencies in the information structure presented by online platforms. A critical analysis reveals that a considerable segment of BUs perceive online service access as either challenging or unfeasible, with only a fraction of search endeavors culminating successfully. This predicament stems largely from the linear nature of information interaction necessitated for BUs, a process that mandates sequential content relevancy assessment, consequently imposing cognitive strain and fostering information disorientation. Moreover, the prevailing evaluative metrics for web service efficacy—precision and recall—exhibit a glaring oversight of the nuanced behavioral and usability facets pertinent to BUs during search engine design. Addressing this, our study introduces an innovative framework to facilitate information exploration, grounded in the cognitive principles governing BUs. This framework, piloted using the Wikipedia dataset, seeks to revolutionize the search result space through categorical organization, thereby enhancing accessibility for BUs. Empirical and usability assessments, conducted on a cohort of legally blind individuals (N = 25), underscore the framework’s potential, demonstrating notable improvements in web content accessibility and system usability, with categorical accuracy standing at 84% and a usability quotient of 72.5%. This research thus holds significant promise for redefining web search paradigms to foster inclusivity and optimized user experiences for BUs.

Background: The aim of the current study was to investigate the anticancer potential of bioactive compounds isolated from the leaves of Olea ferruginea (O. ferruginea). Lignans from O. ferruginea were previously described to possess antibacterial, antileishmanial, and antioxidant properties. Nevertheless, the antiproliferative activity of cycloolivil (1), ferruginan (2), and ferruginan A (3) have not been investigated in depth. Methods: The compounds were isolated from the ethyl acetate fraction of the leaves extract of O. ferruginea. The isolated molecules were evaluated for their anticancer activity against U-87 MG malignant glioma cells. In parallel, molecular docking studies were also performed to investigate the interaction of the compounds with a duplex DNA sequence and epidermal growth factor receptor (EGFR). Results: In vitro tests showed that all three compounds inhibit U-87 MG malignant glioma cell proliferation dose-dependently in the µM range, and ferruginan A (3) was highlighted as the most promising compound of the set. Molecular docking studies showed that the compounds could interfere with double stranded DNA possessing a cisplatin 1,2-d(GpG) intrastrand cross-link and EGFR. Conclusions: Overall, the findings suggest that the tested compounds from O. ferruginea may represent a starting point for the identification of novel tools to inhibit glioma cell proliferation.

The recent advancements in the web allow users to generate multimedia content, resulting in multimedia information proliferation. Existing search engines provide access to multimedia content via a disjoint assembly of media-specific results called verticals. However, this decentralized assembly of media contents requires manual aggregation and synthesizing efforts at the user’s end, hindering the information exploration process and subsequently may cause cognitive overload, hence, demanding innovative tools to discover multimedia content. The researchers have devised numerous state-of-the-art approaches; however, analysis to confirm the efficacy has little emphasis. This study investigates users’ complex multimedia information-seeking behavior over state-of-the-art web search systems to unveil the user’s information-seeking issues. Our research employs between-subjects study and post hoc analysis strategies to analyze participants’ information-seeking characteristics. The study design adopted statistical hypothesis testing to consolidate previous user behavioral studies, confirm existing strategies, and present recommended practices for future general-purpose web search engines. The participants were assigned Google and an advanced discovery search system using the same multimedia dataset to ensure the obtained results’ credibility. The primary behavioral parameters include search efforts, multimedia content exploration, search user interface (SUI), information management and presentation, and user cognition. This study uncovers several inadequacies of the search engines in meeting users’ complex discovery needs, including 29.6% less user engagement, 43% system and searching dissatisfaction, and 32% less knowledge acquisition with 63.9% increased clicking effort on traditional search engines. The results confirmed previous user studies and suggest novel research recommendations statistically significant in multimedia information exploration-related endeavors.

Abstract Background The subcontinent is famous for its variety of seasonal foods cooked in vegetable seed cooking oils at elevated heating. Oils are often of poor quality that effect to consumer health. The work, therefore, planned to examine the effects of heat on the quality of mixed canola cooking oils (MCCOs). MCCOs were analyzed by preparing volatile fatty acid methyl esters (FAMEs) and for physiochemical properties. Results A major change was observed in the FAs composition of various MCCOs as coded K-1 to K-5. MCCOs were found rich in unsaturated 9-octadecanoic acid (oleic acid C18:1) and 9, 12-octadecadienoic acid (linoleic acid C18:2) along saturated octadecanoic acid (stearic acid C18:0). Results reveals that canola oil samples are mixed in the range of 4–30% with other vegetable oils and animal fats. The quality of canola cooking oils further reduced after heating to 100 °C, 200 °C and 350 °C, respectively. Quality parameters of MCCOs were significantly altered after heating and found as color (510–520 nm to 570–600 nm), mass 220–237 g to 210–225 g, volume 250 mL to 239 mL, pH (6.76–6.89), specific gravity (0.87–0.92), refractive index (1.471–1.475), saponification value (SV) (0.7–2.5), un-saponifiable matter (2.4–9.8%) and acid value (AV) (1.20–5.0 mg KOH). Conclusion Heating of oils at elevated temperature have shown a significant effect on pH, specific gravity and un-saponifiable matter (p-value

Privacy is a serious concern related to sharing videos or images among people over the Internet. As a method to preserve images’ privacy, chaos-based image encryption algorithms have been used widely to fulfil such a requirement. However, these algorithms suffer from a low key-space, significant computational overhead, and a lag in resistance against differential attacks. This paper presents a novel chaos-based image encryption method based on permutation and substitution using a single Substitution Box (S-Box) to address issues in contemporary image encryption algorithms. The proposed encryption technique’s efficiency is validated through extensive experiments as compared to the state-of-the-art encryption algorithms using different measures and benchmarks. Precisely, the collected results demonstrate that the proposed technique is more resilient against well-known statistical attacks and performs well under plaintext attacks. Indeed, the proposed scheme exhibits very high sensitivity concerning the plaintext attack. A minor change in the encryption key or the plain text would result in a completely different encrypted image.

The proliferation of multimedia content is transforming users’ information needs from simple lookup-based information retrieval to more complex exploratory and discovery searches. The exploratory search paradigm requires nonlinear access to diverse multimedia documents, which jeopardizes the traditional precision-oriented Search Engine Results Pages (SERP) equipped with media-specific linear lookup lists called verticals. The existing vertical aggregation approaches are instantiated on a specific dataset and are not readily accessible on the web for comparison and reproducibility purposes. Therefore, this article aims to publicize the novel state-of-the-art discovery software aggregating multimedia content to aid the discovery process in exploratory searches. AMED software performs deep semantic analysis, clustering, and summarization on SERP verticals to provide multimedia documents-based traversal. These multimedia documents are further connected to a nonlinear graph based on similarity measures and presented on interactive Search User Interfaces (SUIs) that keep the users captivated within the search space. The empirical evaluation of the proposed data model achieves 99% accuracy score, outperforming the existing aggregation techniques. The further between-subjects (N = 44) usability analysis between the designed SUIs and the Google (baseline) search engine reveals 29.6% better user engagement, 43% more search satisfaction, and 32% more knowledge acquisition with 63.9% reduced clicking efforts.

In this study, the newly synthesized compound (Succ-5) was analyzed through spectral methods, seen for potential receptor targets via molecular docking, and pre-clinically evaluated for therapeutic effects and safety profile using biochemical and histopathological techniques. The biochemical analysis included assessment of cardiac biomarkers, hepatic enzymes, and lipid profiles, while histopathology included evaluation of cardiac and liver tissues. The toxic dose was determined pre-clinically, followed by dividing albino rats into five treatment groups (each having n = 6). The control group received oral saline for eight days. The 5-FU (5-Fluorouracil) group received oral saline for 8 days and 5-FU (150 mg/kg I.P.) on day 5. The atenolol group was administered with atenolol (20 mg/kg) for 8 days and 5-FU (150 mg/kg I.P.) on day 5. Two groups of rats were administered with the test compound (Succ-5) at doses of 5 mg/kg I.P and 10 mg/kg I.P (for 8-days), followed by 5-FU (150 mg/kg I.P.) on day 5. Elevated serum levels of CK-MB (creatinine kinase myocardial band), cTnI (troponin I), LDH (lactate dehydrogenase), lipid profile, and selected liver enzymes including ALP (alkaline phosphatase), ALT (alanine transaminase), AST (aspartate aminotransferase), BT (bilirubin total) and BD (direct bilirubin) were associated with 5-FU toxicity. After administration of the test compound at the mentioned doses, these biomarkers significantly decreased. Likewise, histological examination revealed 5-FU damaged the heart and hepatic tissues, which were also considerably recovered following administration of the test compound. Immunohistochemistry of heart tissue also revealed the low expression of COX-2 and TNF-α in Succ-5 treated groups compared to toxic group. Dose-response evaluation showed that a dose of 10 mg/kg provided better results than 5 mg/kg. The analysis of binding energy values computed via docking simulations showed that Succ-5 interacts with the human beta2-adrenergic G protein-coupled receptor with a slightly stronger affinity than calcium channel T-type. In conclusion, the histological and biochemical findings revealed that the test compound had significant cardioprotective, hepatoprotective, and lipolytic effects in the 5-FU-induced toxicity.

Various derivatives of thiazolidine-2,4-dione (C1–C5) were designed and synthesized by chemical reaction with 4-nitrobenzaldehyde using Knoevenagel reaction conditions which results in the reduction of nitro group to amine and further modification results in target compounds. The chemical structures of all the 2,4-thiazolidinedione derivatives have been elucidated by 1H and 13C NMR spectroscopy. These compounds were further characterized by in silico ADME (absorption, distribution, metabolism, and excretion) studies. The pharmacokinetic properties were assessed by SwissADME software. The in silico ADME (absorption, distribution, metabolism, and excretion) assessment reveals that all derivatives (C1 to C5) have 5 to 7 rotatable bonds. Lipophilicity and water solubility showed that C1, C2, and C4 are water soluble except for C3 and C5 which are moderately soluble. All the compounds have high GI absorption except C3. None of the derivatives are blood-brain barrier permeant. Drug metabolism of TZDs derivatives showed that C3 was identified as an inhibitor of CYP2C9 and C5 as an inhibitor of CYP1A2 and CYP2C19. Drug likeness properties indicate that C1 has only one violation of the Ghose rule while C3 has violations in the Ghose and Egan rules. The in silico pharmacokinetic studies revealed high GI absorption and the inability to pass blood-brain barrier which can be further assessed by in vitro and in vivo antihyperglycemic activity. This study will contribute to providing TZDs derivatives with an improved pharmacokinetic profile and decreased toxicity.

Nowadays, exponential growth in online production and extensive perceptual power of visual contents (i.e., images) complicate the users' information needs. The research has shown that users are interested in satisfying their visual information needs by accessing the image objects. However, the exploration of images via existing search engines is challenging. Mainly, existing search engines employ linear lists or grid layouts, sorted in descending order of relevancy to the user's query to present the image results, which hinders image exploration via multiple information modalities associated with them. Furthermore, results at lower-ranking positions are cumbersome to reach. This research proposed a Search User Interface (SUI) approach to instantiate the non-linear reachability of the image results by enabling interactive exploration and visualization options. We represent the results in a cluster-graph data model, where the nodes represent images and the edges are multimodal similarity relationships. The results in clusters are reachable via multimodal similarity relationships. We instantiated the proposed approach over a real dataset of images and evaluated it via multiple types of usability tests and behavioral analysis techniques. The usability testing reveals good satisfaction (76.83%) and usability (83.73%) scores.

Abstract Background Edible oils have proven health benefits in the prevention and treatment of various disorders since the establishment of human era. This study was aimed to appraise neuropharmacological studies on the commonly used edible oils including Cinnamomum verum (CV), Zingiber officinale (ZO) and Cuminum cyminum (CC). Methods The oils were analyzed via GC-MS for identifications of bioactive compounds. Anti-radicals capacity of the oils were evaluated via 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radicals scavenging assays. The samples were also tested against two important acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) which are among the important drug targets in Alzheimer’s disease. Lineweaver-Burk plots were constructed for enzyme inhibition studies which correspond to velocity of enzymes (Vmax) against the reciprocal of substrate concentration (K m ) in the presence of test samples and control drugs following Michaelis-Menten kinetics. Docking studies on AChE target were also carried out using Molecular Operating Environment (MOE 2016.0802) software. Results (Gas chromatography-mass spectrometry GC-MS) analysis revealed the presence of thirty-four compounds in Cinnamon oil (Cv.Eo), fourteen in ginger oil (Zo.Eo) and fifty-six in cumin oil (Cc.Eo). In the antioxidant assays, Cv.Eo, Zo.Eo and Cc.Eo exhibited IC50 values of 85, 121, 280 μg/ml sequentially against DPPH radicals. Whereas, in ABTS assay, Cv.Eo, Zo.Eo and Cc.Eo showed considerable anti-radicals potentials with IC50 values of 93, 77 and 271 μg/ml respectively. Furthermore, Cv.Eo was highly active against AChE enzyme with IC50 of 21 μg/ml. Zo.Eo and Cc.Eo exhibited considerable inhibitory activities against AChE with IC50 values of 88 and 198 μg/ml respectively. In BChE assay, Cv.Eo, Zo.Eo and Cc.Eo exhibited IC50 values of 106, 101 and 37 μg/ml respectively. Our results revealed that these oils possess considerable antioxidant and cholinesterase inhibitory potentials. As functional foods these oils can be effective remedy for the prevention and management of neurological disorders including AD. Synergistic effect of all the identified compounds was determined via binding energy values computed through docking simulations. Binding orientations showed that all the compounds interact with amino acid residues present in the peripheral anionic site (PAS) and catalytic anionic site (CAS) amino acid residues, oxyanion hole and acyl pocket via π-π stacking interactions and hydrogen bond interactions.

Abstract Background Diabetes mellitus is a common disease effecting the lifestyles of majority world population. In this research work, we have embarked the potential role of crude extracts and isolated compounds of Notholirion thomsonianum for the management diabetes mellitus. Methods The crude extracts of N. thomsonianum were initially evaluated for α-glucosidase, α-amylase and antioxidant activities. The compounds were isolated from the activity based potent solvent fraction. The structures of isolated compounds were confirmed with NMR and MS analyses. The isolated compounds were tested for α-glucosidase, α-amylase, protein tyrosine phosphatase 1B (PTP1B) and DPPH activities. The molecular docking studies were carried out to find the binding interactions of isolated compounds for α-glucosidase, α-amylase and PTP1B. Results Initially, we screened out crude extracts and subfractions of N. thomsonianum against different in-vitro targets. Among all, Nt.EtAc was observed a potent fraction among all giving IC50 values of 67, 70,

Abstract Modulation of the endocannabinoid system (ECS) is a novel putative target for therapeutic intervention in depressive disorders. Altering concentrations of one of the principal endocannabinoids, N‐arachidonoylethanolamine, also known as anandamide (AEA) can affect depressive‐like behaviors through several mechanisms including anti‐inflammatory, hormonal, and neural circuit alterations. Recently, isoflavonoids, a class of plant‐derived compounds, have been of therapeutic interest given their ability to modulate the metabolism of the endogenous ligands of the ECS. To determine the therapeutic potential of isoflavonoids, we screened several candidate compounds (Genistein, Biochanin‐A, and 7‐hydroxyflavone) in silico to determine their binding properties with fatty acid amide hydrolase (FAAH), the primary degrative enzyme for AEA. We further validated the ability of these compounds to inhibit FAAH and determined their effects on depressive‐like and locomotor behaviors in the forced swim test (FST) and open field test in male and female mice. We found that while genistein was the most potent FAAH inhibitor, 7‐hydroxyflavone was most effective at reducing immobility time in the forced swim test. Finally, we measured blood corticosterone and prefrontal cortex AEA concentrations following the forced swim test and found that all tested compounds decreased corticosterone and increased AEA, demonstrating that isoflavonoids are promising therapeutic targets as FAAH inhibitors.

A dermatologist-like automatic classification system is developed in this paper to recognize nine different classes of pigmented skin lesions (PSLs), using a separable vision transformer (SVT) technique to assist clinical experts in early skin cancer detection. In the past, researchers have developed a few systems to recognize nine classes of PSLs. However, they often require enormous computations to achieve high performance, which is burdensome to deploy on resource-constrained devices. In this paper, a new approach to designing SVT architecture is developed based on SqueezeNet and depthwise separable CNN models. The primary goal is to find a deep learning architecture with few parameters that has comparable accuracy to state-of-the-art (SOTA) architectures. This paper modifies the SqueezeNet design for improved runtime performance by utilizing depthwise separable convolutions rather than simple conventional units. To develop this Assist-Dermo system, a data augmentation technique is applied to control the PSL imbalance problem. Next, a pre-processing step is integrated to select the most dominant region and then enhance the lesion patterns in a perceptual-oriented color space. Afterwards, the Assist-Dermo system is designed to improve efficacy and performance with several layers and multiple filter sizes but fewer filters and parameters. For the training and evaluation of Assist-Dermo models, a set of PSL images is collected from different online data sources such as Ph2, ISBI-2017, HAM10000, and ISIC to recognize nine classes of PSLs. On the chosen dataset, it achieves an accuracy (ACC) of 95.6%, a sensitivity (SE) of 96.7%, a specificity (SP) of 95%, and an area under the curve (AUC) of 0.95. The experimental results show that the suggested Assist-Dermo technique outperformed SOTA algorithms when recognizing nine classes of PSLs. The Assist-Dermo system performed better than other competitive systems and can support dermatologists in the diagnosis of a wide variety of PSLs through dermoscopy. The Assist-Dermo model code is freely available on GitHub for the scientific community.

The main objective of the present research project was to investigate the possibility of using low cost, eco-friendly, and easily available adsorbents, such as mint biomass and marble stone waste, for the removal of dyes, DRIM blue HS-RL and DRIM black ep-B, from wastewater using an efficient procedure, which is adsorption. Nine different combinations of these adsorbents were prepared with and without modification using sodium metasilicate and potassium ferricyanide. Spectroscopic analysis was carried out to investigate the λmax of the dyes. Adsorbent nanocomposites were characterized using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) and zeta (ζ) potential. Adsorption equilibrium studies were investigated by determining the adsorption at the following conditions: initial dye concentrations (5–50 ppm), adsorbent doses (0.005–0.5 g), contact times (15–240 min), temperatures (30–70 °C) and pH (5–10). Of all the nine adsorbents, MTPF showed the maximum adsorption capacity at 50 ppm initial dye concentration, 0.005 g dosage of adsorbent and 240 min contact time for both dyes. DRIM Blue HS-RL was adsorbed efficiently at 6 pH and temperature 60 °C and DRIM black ep-B was adsorbed at pH 5 and temperature 50 °C by MTPF (mint–tawera composite treated with potassium ferricyanide). Among the various adsorption isotherms (Langmuir, Dubinin–Radushkevich, Freundlich, Herkin–Jura, and Temkin isotherms), some adsorbent followed the Freundlich isotherm while the others followed the Langmuir isotherm. The best-fit model was decided based on their high R2 value and agreement between qe calculated from isotherms and those obtained experimentally. At equilibrium concentration, application of kinetic models (pseudo-first-order, and pseudo-second-order) revealed that the best-fit model was pseudo-second-order kinetic model for both dyes, as their R2 > 0.9, and qe calculated was close to qe obtained experimentally.

Transformation of lignocellulosic biomass into high-value chemicals is a viable strategy for sustainable development of a bio-based economy. 5-Hydroxymethylfurfural (HMF) is one of potential platform bio-chemicals for the manufacture of various renewable products. In this work, a commercial H-ZSM-5 zeolite was used as a starting material for preparing a series of acid catalysts with bifunctionality for direct dehydration of glucose to HMF in a biphasic water/tetrahydrofuran system. The pristine H-ZSM-5 was mildly dealuminated by refluxing with dilute nitric acid solutions to adjust its acid properties. Although the acid treatment slightly altered the elemental composition, textural properties, and morphology of zeolite, the total acidity and distribution of acid sites were significantly modified. Some non-framework aluminum (Al) oxide clusters were removed from the parent H-ZSM-5 simultaneously with a partial hydrolysis of zeolitic framework. An increased fraction of coordinatively unsaturated framework Al species enhanced the number of Lewis acid sites. Using 0.1 M solution in the treatment provided the suitable catalyst (0.1DeAl.H-ZSM-5), giving a glucose conversion and HMF yield of >99% and 64.7%, respectively, and a good reusability under the optimized reaction conditions. These results show the industrial potential of the proposed method for simple but efficient preparation of H-ZSM-5 catalysts for producing HMF via the catalytic dehydration of glucose.

Production of biodiesel from edible vegetable oils using homogenous catalysts negatively impacts food availability and cost while generating significant amounts of caustic wastewater during purification. Thus, there is an urgent need to utilize low-cost, non-food feedstocks for the production of biodiesel using sustainable heterogeneous catalysis. The objective of this study was to synthesize a novel supported nano-magnetic catalyst (CaO/Fe2O3/feldspar) for the production of biodiesel (fatty acid methyl esters) from waste and low-cost plant seed oils, including Sinapis arvensis (wild mustard), Carthamus oxyacantha (wild safflower) and Pongamia pinnata (karanja). The structure, morphology, surface area, porosity, crystallinity, and magnetization of the nano-magnetic catalyst was confirmed using XRD, FESEM/EDX, BET, and VSM. The maximum biodiesel yield (93.6–99.9%) was achieved at 1.0 or 1.5 wt.% catalyst with methanol-to-oil molar ratios of 5:1 or 10:1 at 40 °C for 2 h. The CaO/Fe2O3/feldspar catalyst retained high activity for four consecutive cycles for conversion of karanja, wild mustard, and wild safflower oils. The effective separation of the catalyst from biodiesel was achieved using an external magnet. Various different physico-chemical parameters, such as pour point, density, cloud point, iodine value, acid value, and cetane number, were also determined for the optimized fuels and found to be within the ranges specified in ASTM D6751 and EN 14214, where applicable.

In the era of acquired microbial resistance (AMR), resulting in the ineffectiveness of antibiotics is of keen interest for researchers in current scenarios. Ten novel metal complexes of gemifloxacin have been synthesized by reacting it with essential and trace elements in a 2:1 ratio predetermined conducto-metrically. As these metals are either present in the body or co-administered as metallic supplements can alter the level of antibiotics. Therefore, Metal complexes of Gemifloxacin, an important member of the fluoroquinolone family, were synthesized. The possible coordination of gemifloxacin with these metals has been proposed by the electronic and elemental data obtained through molar conductance, elemental analysis, and spectroscopic techniques like ultraviolet-visible (UV-Vis), infrared (IR), and proton-nuclear magnetic resonance (1H NMR) studies.In the light of these studies, the monoanionic bidentate ligand behavior of gemifloxacin in complexation with metals has been revealed. For in-vitro microbial studies, these newly synthesized complexes were tested against eleven different bacteria including Gram + ve and Gram -ve organisms, and one fungal strain. The results were compared with the parent drug by applying ANOVA through SPSS software version 22. Therefore, it has been found that among all synthesized metal complexes, the G-M01 complex exhibits increased activity against B. subtilis, P. mirabilis, E. coli, K. pneumonia, and C. freundii. Complex G-M02, G-M03, G-M04, and G-M10 show more pronounced activity than Gemifloxacin against S. aureus and M. luteus. Moreover, the binding orientations of the synthesized metal complexes into the binding site of the urease enzyme revealed that all the docked metal complexes oriented away from the Ni bi-center, and the inactivation of urease is due to their interaction with entrance flap residues.

Diabetes mellitus (DM) is a real challenge to the recent era and is one of the major diseases for initiating life-threatening disorders. In current research, a compound was designed by combining vanillin, thiazolidinedione and morpholine. The goal of our designed work is to demonstrate the ability of our design compound (9) to modulate more than one target responsible for hyperglycemia at the same time. The synthesized compound was able to show good to moderate inhibition potential against α-glucosidase, α-amylase and protein tyrosine phosphatase 1B. However, it exhibited excellent in-vitro inhibition of Dipeptidyl peptidase-4 (DPP-4) with IC50 value of 0.09 µM. Antioxidant activity by using DPPH assay also showed its good antioxidant potential. In in-vivo experiments, the compound 9 was proved to be safe in experimental mice. The activity profile of the compound was observed for 21 days which showed that the compound was also effective in experimental mice. Binding orientations and Interactions with key amino acid residues of the selected targets were also studied by using docking studies. Overall, we were successful in synthesizing multitarget preclinical therapeutic by combining three pharmacophoric moieties into a single chemical entity that can modulate more than one target at the same time.

Drought is a serious threat worldwide to soybean and maize production. This study was conducted to discern the impact of salvianolic acid treatment on osmotic-stressed soybean (Glycine max L.) and maize (Zea mays L.) seedlings from the perspective of physiochemical and molecular reactions. Examination of varied salvianolic acid concentrations (0, 0.1, 1, 5, 10, and 25 μM) on soybean and maize seedling growth confirmed that the 0.1 and 1 μM concentrations, respectively, showed an improvement in agronomic traits. Likewise, the investigation ascertained how salvianolic acid application could retrieve osmotic-stressed plants. Soybean and maize seedlings were irrigated with water or 25% PEG for 8 days. The results indicated that salvianolic acid application promoted the survival of the 39-day-old osmotic-stressed soybean and maize plants. The salvianolic acid-treated plants retained high photosynthetic pigments, protein, amino acid, fatty acid, sugar, and antioxidant contents, and demonstrated low hydrogen peroxide and lipid contents under osmotic stress conditions. Gene transcription pattern certified that salvianolic acid application led to an increased expression of GmGOGAT, GmUBC2, ZmpsbA, ZmNAGK, ZmVPP1, and ZmSCE1d genes, and a diminished expression of GmMIPS2, GmSOG1, GmACS, GmCKX, ZmPIS, and ZmNAC48 genes. Together, our results indicate the utility of salvianolic acid to enhance the osmotic endurance of soybean and maize plants.