Perception and behavior toward neuropsychiatric disorders in Saudi Arabia: A systematic review and quality assessment.

LAY ABSTRACT: In 2010, Saudi Arabia became the first country from the Gulf Cooperation Council states to join the World Mental Health Survey Initiative, which collaborates with Harvard University and has undertaken over 33 countries. The Saudi National Mental Health Survey revealed that 80% of Saudis with severe mental health disorders do not seek treatment. Considering the strong evidence set out in Saudi national study and the recommendations for future research, this systematic literature review was initiated to examine the most studied neurodevelopmental disorders reported in the Kingdom of Saudi Arabia to explore public knowledge, attitudes, and behaviors. Findings have shown that attention deficit hyperactivity disorder and autism spectrum disorder have been the most studied neurodevelopmental disorders in Saudi Arabia since 2010. However, various groups in Saudi society, including healthcare professionals, medical students, and the general public, lacked knowledge about these health conditions, often leading to stigmatized attitudes and behaviors toward people with attention deficit hyperactivity disorder and autism spectrum disorder. However, demographic data showed that most of the studies were carried out in the Central and Western provinces. More research is needed in all regions of the Kingdom of Saudi Arabia to contribute to the knowledge about mental health conditions of attention deficit hyperactivity disorder and autism spectrum disorder children and their parents to increase knowledge about neurodevelopmental disorders and mental health disorders in the Kingdom of Saudi Arabia, thereby enabling people to rethink their attitudes and behavior.

To evaluate the complication and patency rate of superficial femoral vein transposition in tertiary care center.

INTRODUCTION: When all access options in the upper extremity have been exhausted, an autologous access can be created in lower extremity. The purpose of this study is to report our experience with superficial femoral vein transposition (SFVT) results in terms of postoperative complication and patency rate. MATERIALS AND METHODS: In the time period from January 1, 2019 to April 30, 2021, thirty-five cases of SFVT performed at our large tertiary care center Sindh Institute of Urology and Transplantation (SIUT). All patients had exhausted upper arm veins or had central vein obstructions. Medical records of all patients were traced, patients were interviewed using a standard proforma and evaluated the current AVF function in the OPD clinic or by telephone calls. Data including demographics and postoperative complications were collected. RESULTS: Thirty-nine cases of SFVT performed at our institute. Three were immediately lost to follow up so they were excluded from the study. Mean patient age was 30 ± 13.4 years. Most of our patients were females (57%) and 15 males (43%) with an average age of 29.05 years. The most common underlying renal diseasewas unknown in 16 (45%).Thirty-five patients included in the analysis; out of which primary failure observed in 4 patients, three patients were expired before fistula maturation and 3 were expired before 6 months. The remaining 25 fistulas patency rates were estimated. No any patient died due to fistulas related complication; patients died due to their primary disease. CONCLUSION: Our study shows that with appropriate patient selection, SFVT have low infection rates and patency that is comparable with other access types.

Review on blueberry drought tolerance from the perspective of cultivar improvement.

Blueberry (Vaccinium spp.) is an increasingly popular fruit around the world for their attractive taste, appearance, and most importantly their many health benefits. Global blueberry production was valued at $2.31 billion with the United States alone producing $1.02 billion of cultivated blueberries in 2021. The sustainability of blueberry production is increasingly threatened by more frequent and extreme drought events caused by climate change. Blueberry is especially prone to adverse effects from drought events due to their superficial root system and lack of root hairs, which limit blueberry's ability to intake water and nutrients from the soil especially under drought stress conditions. The goal of this paper is to review previous studies on blueberry drought tolerance focusing on physiological, biochemical, and molecular drought tolerance mechanisms, as well as genetic variability present in cultivated blueberries. We also discuss limitations of previous studies and potential directions for future efforts to develop drought-tolerant blueberry cultivars. Our review showed that the following areas are lacking in blueberry drought tolerance research: studies of root and fruit traits related to drought tolerance, large-scale cultivar screening, efforts to understand the genetic architecture of drought tolerance, tools for molecular-assisted drought tolerance improvement, and high-throughput phenotyping capability for efficient cultivar screening. Future research should be devoted to following areas: (1) drought tolerance evaluation to include a broader range of traits, such as root architecture and fruit-related performance under drought stress, to establish stronger association between physiological and molecular signals with drought tolerance mechanisms; (2) large-scale drought tolerance screening across diverse blueberry germplasm to uncover various drought tolerance mechanisms and valuable genetic resources; (3) high-throughput phenotyping tools for drought-related traits to enhance the efficiency and affordability of drought phenotyping; (4) identification of genetic architecture of drought tolerance using various mapping technologies and transcriptome analysis; (5) tools for molecular-assisted breeding for drought tolerance, such as marker-assisted selection and genomic selection, and (6) investigation of the interactions between drought and other stresses such as heat to develop stress resilient genotypes.

Knowledge, attitude, and awareness of cardiopulmonary resuscitation among university enrolled medical and non-medical students of Pakistan: An online study.

Objective: To evaluate the awareness, attitude and knowledge of cardiopulmonary resuscitation (CPR) among university-enrolled medical and non-medical undergraduate students of Pakistan. Methods: Cross-sectional online survey-based study was conducted across institutes in Pakistan from December, 2022 to January, 2023. The study involved university-enrolled undergraduate students across the country. The structured questionnaire was disseminated via Google forms. For statistical analysis, SPSS version 20 was used to analyze the data by applying independent sample t-tests and ANOVA. Results: A total of 249 responses were received. After the exclusion of two responses, the overall awareness score of participants was found to be 2.49 ± 1.33, attitude score of 4.09 ± 1.74, and knowledge score of 3.51 ± 2.13. Female respondents, medical students, unmarried (single), private institutes, and respondents with educated parents achieved relatively higher scores. The overall difference in awareness scores among different regions of Pakistan was also significant (p <0.05). Gender, region, and parental literacy rate also showed effects on participants' basic life support (BLS) and CPR knowledge (p <0.05). Conclusions: Overall knowledge and awareness were unsatisfactory and inadequate in university-enrolled undergraduate students, with no one getting a complete score on very basic knowledge questions. Significant differences in awareness, attitude, and knowledge among different regions, genders, and parental literacy rates were found.

Unveiling the MIL-53(Al) MOF: Tuning Photoluminescence and Structural Properties via Volatile Organic Compounds Interactions.

MIL-53(Al) is a metal-organic framework (MOF) with unique properties, including structural flexibility, thermal stability, and luminescence. Its ability to adsorb volatile organic compounds (VOCs) and water vapor makes it a promising platform for sensing applications. This study investigated the adsorption mechanism of MIL-53(Al) with different VOCs, including ketones, alcohols, aromatics, and water molecules, focusing on structural transformations due to pore size variation and photoluminescence properties. The reported results assess MIL-53(Al) selectivity towards different VOCs and provide insights into their fundamental properties and potential applications in sensing.

Hyperspectral Analysis for Discriminating Herbicide Site of Action: A Novel Approach for Accelerating Herbicide Research.

In agricultural weed management, herbicides are indispensable, yet innovation in their modes of action (MOA)-the general mechanisms affecting plant processes-has slowed. A finer classification within MOA is the site of action (SOA), the specific biochemical pathway in plants targeted by herbicides. The primary objectives of this study were to evaluate the efficacy of hyperspectral imaging in the early detection of herbicide stress and to assess its potential in accelerating the herbicide development process by identifying unique herbicide sites of action (SOA). Employing a novel SOA classification method, eight herbicides with unique SOAs were examined via an automated, high-throughput imaging system equipped with a conveyor-based plant transportation at Purdue University. This is one of the earliest trials to test hyperspectral imaging on a large number of herbicides, and the study aimed to explore the earliest herbicide stress detection/classification date and accelerate the speed of herbicide development. The final models, trained on a dataset with nine treatments with 320 samples in two rounds, achieved an overall accuracy of 81.5% 1 day after treatment. With the high-precision models and rapid screening of numerous compounds in only 7 days, the study results suggest that hyperspectral technology combined with machine learning can contribute to the discovery of new herbicide MOA and help address the challenges associated with herbicide resistance. Although no public research to date has used hyperspectral technology to classify herbicide SOA, the successful evaluation of herbicide damage to crops provides hope to accelerate the progress of herbicide development.

Echocardiography in a critical care unit: a contemporary review.

INTRODUCTION: Echocardiography is a rapid, noninvasive, and complete cardiac assessment tool for patients with hemodynamic instability. Relevant articles were extracted after searching on databases by two reviewers and incorporated in this review in anarrative style. AREAS COVERED: his review provides an overview of the evidence for current practices in critical care units (CCUs), incorporating the use of echocardiography in different etiologies of shock. EXPERT OPINION: In an acute scenario, a basic echocardiographic study yields prompt diagnosis, allowing for the initiation of treatment. The most common pathologies in shocked patients are identified promptly using two-dimensional (2D) and M-mode echocardiography. A more comprehensive assessment can follow after patients have been stabilized. There are four types of shock: (i) cardiogenic shock, (ii) hypovolemic shock, (iii) obstructive shock, and (iv) septic shock. All of them can be readily identified by echocardiography. As echocardiography is increasingly being used in an intensive care setting, its applications and evidence base should be expanded by randomized controlled trials to demonstrate patient outcomes in critical care.

Improving selective targeting to cancer-associated fibroblasts by modifying liposomes with arginine based materials.

A library of arginine-like surface modifiers was tested to improve the targetability of DOPE:DOPC liposomes towards myofibroblasts in a tumour microenvironment. Liposomes were characterised using zeta potential and dynamic light scattering. Cell viability remained unchanged for all liposomes. Liposomes were encapsulated using doxorubicin (DOX) with an encapsulation efficiency >94%. The toxicity of DOX-loaded liposomes was calculated via half-maximal inhibitory concentration (IC50) for fibroblasts and myofibroblasts. These liposomes resulted in significantly lower IC50-values for myofibroblasts compared to fibroblasts, making them more toxic towards the myofibroblasts. Furthermore, a significant increase in cell internalisation was observed for myofibroblasts compared to fibroblasts, using fluorescein-loaded liposomes. Most importantly, a novel regression model was constructed to predict the IC50-values for different modifications using their physicochemical properties. Fourteen modifications (A-N) were used to train and validate this model; subsequently, this regression model predicted IC50-values for three new modifications (O, P and Q) for both fibroblasts and myofibroblasts. Predicted and measured IC50-values showed no significant difference for fibroblasts. For myofibroblasts, modification O showed no significant difference. This study demonstrates that the tested surface modifications can improve targeting to myofibroblasts in the presence of fibroblasts and hence are suitable drug delivery vehicles for myofibroblasts in a tumour microenvironment.

Elimination of Leaf Angle Impacts on Plant Reflectance Spectra Using Fusion of Hyperspectral Images and 3D Point Clouds.

During recent years, hyperspectral imaging technologies have been widely applied in agriculture to evaluate complex plant physiological traits such as leaf moisture content, nutrient level, and disease stress. A critical component of this technique is white referencing used to remove the effect of non-uniform lighting intensity in different wavelengths on raw hyperspectral images. However, a flat white tile cannot accurately reflect the lighting intensity variance on plant leaves, since the leaf geometry (e.g., tilt angles) and its interaction with the illumination severely impact plant reflectance spectra and vegetation indices such as the normalized difference vegetation index (NDVI). In this research, the impacts of leaf angles on plant reflectance spectra were summarized, and an improved image calibration model using the fusion of leaf hyperspectral images and 3D point clouds was built. Corn and soybean leaf samples were imaged at different tilt angles and orientations using an indoor desktop hyperspectral imaging system and analyzed for differences in the NDVI values. The results showed that the leaf's NDVI largely changed with angles. The changing trends with angles differed between the two species. Using measurements of leaf tilt angle and orientation obtained from the 3D point cloud data taken simultaneously with the hyperspectral images, a support vector regression (SVR) model was successfully developed to calibrate the NDVI values of pixels at different angles on a leaf to a same standard as if the leaf was laid flat on a horizontal surface. The R-squared values between the measured and predicted leaf angle impacts were 0.76 and 0.94 for corn and soybean, respectively. This method has a potential to be used in any general plant imaging systems to improve the phenotyping quality.

Soft materials as biological and artificial membranes.

The past few decades have seen emerging growth in the field of soft materials for synthetic biology. This review focuses on soft materials involved in biological and artificial membranes. The biological membranes discussed here are mainly those involved in the structure and function of cells and organelles. As building blocks in medicine, non-native membranes including nanocarriers (NCs), especially liposomes and DQAsomes, and polymeric membranes for scaffolds are constructed from amphiphilic combinations of lipids, proteins, and carbohydrates. Artificial membranes can be prepared using synthetic, soft materials and molecules and then incorporated into structures through self-organization to form micelles or niosomes. The modification of artificial membranes can be realized using traditional chemical methods such as click reactions to target the delivery of NCs and control the release of therapeutics. The biomembrane, a lamellar structure inlaid with ion channels, receptors, lipid rafts, enzymes, and other functional units, separates cells and organelles from the environment. An active domain inserted into the membrane and organelles for energy conversion and cellular communication can target disease by changing the membrane's composition, structure, and fluidity and affecting the on/off status of the membrane gates. The biological membrane targets analyzing pathological mechanisms and curing complex diseases, which inspires us to create NCs with artificial membranes.

Stress Distribution Analysis on Hyperspectral Corn Leaf Images for Improved Phenotyping Quality.

High-throughput imaging technologies have been developing rapidly for agricultural plant phenotyping purposes. With most of the current crop plant image processing algorithms, the plant canopy pixels are segmented from the images, and the averaged spectrum across the whole canopy is calculated in order to predict the plant's physiological features. However, the nutrients and stress levels vary significantly across the canopy. For example, it is common to have several times of difference among Soil Plant Analysis Development (SPAD) chlorophyll meter readings of chlorophyll content at different positions on the same leaf. The current plant image processing algorithms cannot provide satisfactory plant measurement quality, as the averaged color cannot characterize the different leaf parts. Meanwhile, the nutrients and stress distribution patterns contain unique features which might provide valuable signals for phenotyping. There is great potential to develop a finer level of image processing algorithm which analyzes the nutrients and stress distributions across the leaf for improved quality of phenotyping measurements. In this paper, a new leaf image processing algorithm based on Random Forest and leaf region rescaling was developed in order to analyze the distribution patterns on the corn leaf. The normalized difference vegetation index (NDVI) was used as an example to demonstrate the improvements of the new algorithm in differentiating between different nitrogen stress levels. With the Random Forest method integrated into the algorithm, the distribution patterns along the corn leaf's mid-rib direction were successfully modeled and utilized for improved phenotyping quality. The algorithm was tested in a field corn plant phenotyping assay with different genotypes and nitrogen treatments. Compared with the traditional image processing algorithms which average the NDVI (for example) throughout the whole leaf, the new algorithm more clearly differentiates the leaves from different nitrogen treatments and genotypes. We expect that, besides NDVI, the new distribution analysis algorithm could improve the quality of other plant feature measurements in similar ways.

Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants.

The normalized difference vegetation index (NDVI) is widely used in remote sensing to monitor plant growth and chlorophyll levels. Usually, a multispectral camera (MSC) or hyperspectral camera (HSC) is required to obtain the near-infrared (NIR) and red bands for calculating NDVI. However, these cameras are expensive, heavy, difficult to geo-reference, and require professional training in imaging and data processing. On the other hand, the RGBN camera (NIR sensitive RGB camera, simply modified from standard RGB cameras by removing the NIR rejection filter) have also been explored to measure NDVI, but the results did not exactly match the NDVI from the MSC or HSC solutions. This study demonstrates an improved NDVI estimation method with an RGBN camera-based imaging system (Ncam) and machine learning algorithms. The Ncam consisted of an RGBN camera, a filter, and a microcontroller with a total cost of only $70 ~ 85. This new NDVI estimation solution was compared with a high-end hyperspectral camera in an experiment with corn plants under different nitrogen and water treatments. The results showed that the Ncam with two-band-pass filter achieved high performance (R2 = 0.96, RMSE = 0.0079) at estimating NDVI with the machine learning model. Additional tests showed that besides NDVI, this low-cost Ncam was also capable of predicting corn plant nitrogen contents precisely. Thus, Ncam is a potential option for MSC and HSC in plant phenotyping projects.

Development of Acoustically Active Nanocones Using the Host-Guest Interaction as a New Histotripsy Agent.

Histotripsy is a noninvasive and nonthermal ultrasound ablation technique, which mechanically ablates the tissues using very short, focused, high-pressured ultrasound pulses to generate dense cavitating bubble cloud. Histotripsy requires large negative pressures (≥28 MPa) to generate cavitation in the target tissue, guided by real-time ultrasound imaging guidance. The high cavitation threshold and reliance on real-time image guidance are potential limitations of histotripsy, particularly for the treatment of multifocal or metastatic cancers. To address these potential limitations, we have recently developed nanoparticle-mediated histotripsy (NMH) where perfluorocarbon (PFC)-filled nanodroplets (NDs) with the size of ∼200 nm were used as cavitation nuclei for histotripsy, as they are able to significantly lower the cavitation threshold. However, although NDs were shown to be an effective histotripsy agent, they pose several issues. Their generation requires multistep synthesis, they lack long-term stability, and determination of PFC concentration in the treatment dose is not possible. In this study, PFC-filled nanocones (NCs) were developed as a new generation of histotripsy agents to address the mentioned limitations of NDs. The developed NCs represent an inclusion complex of methylated ß-cyclodextrin as a water-soluble analog of ß-cyclodextrin and perfluorohexane (PFH) as more effective PFC derivatives for histotripsy. Results showed that NCs are easy to produce, biocompatible, have a size <50 nm, and have a quantitative complexation that allows us to directly calculate the PFH amount in the used NC dose. Results further demonstrated that NCs embedded into tissue-mimicking phantoms generated histotripsy cavitation "bubble clouds" at a significantly lower transducer amplitude compared to control phantoms, demonstrating the ability of NCs to function as effective histotripsy agents for NMH.

Nanoparticle-mediated histotripsy (NMH) using perfluorohexane 'nanocones'.

Nanoparticle-mediated histotripsy (NMH) is an ultrasound treatment strategy that combines acoustically sensitive nanoparticles with histotripsy. Previous NMH studies using perfluorocarbon (PFC) nanodroplets (ND's), ~200 nm in diameter, demonstrated that NMH can selectively generate cavitation by reducing the cavitation threshold from ~25-30 MPa to ~10-15 MPa. Recent studies have also shown that cavitation nucleation in NMH is directly caused by the incident negative pressure (p-) exposed to the PFC, as predicted by classical nucleation theory (CNT), suggesting that the NMH cavitation threshold is dependent on the total volume of PFC present in the focal region. In this study, we investigate the use of a newly developed NMH nanoparticle synthesized using an inclusion complex of methylated ß-cyclodextrin and perfluorohexane (PFH). These 'nanocones' (NCs) have advantages compared to previously used ND's due to their smaller size (~50 nm), simple synthesis method, higher stability and information of definite PFH amount carried by the NC. To test the hypothesis that NCs can reduce the NMH cavitation threshold similar to ND's, and that the NMH cavitation threshold is dependent upon the total PFH concentration, tissue phantoms containing concentrations of NCs ranging from 10-5 to 10-10 (ml PFH/ml water) were exposed to single cycle ultrasound pulses using a 500 kHz focused transducer where high speed imaging captured cavitation data. Results showed that NCs significantly reduced the histotripsy cavitation threshold to 11.0 MPa for a concentration of 10-5 (ml PFH/ml water), with the threshold increasing at lower concentrations. Finally, the ability of NCs to be used for effective NMH ablation was demonstrated in tissue phantoms containing red blood cells (RBCs). Overall, the results of the study support our hypotheses that NCs can be used for effective NMH therapy and that NC concentration has a predictable threshold-reducing effect.

Investigation of nepetolide as a novel lead compound: Antioxidant, antimicrobial, cytotoxic, anticancer, anti-inflammatory, analgesic activities and molecular docking evaluation.

In the present study, we describe various pharmacological effects and computational analysis of nepetolide, a tricyclic clerodane-type diterpene, isolated from Nepeta suavis. Nepetolide concentration-dependently (1.0-1000 µg/mL) exhibited 1,1-diphenyl,2-picrylhydrazyl free radical scavenging activity with maximum effect of 87.01 ±â€¯1.85%, indicating its antioxidant potential, as shown by standard drug, ascorbic acid. It was moderately active against bacterial strain of Staphylococcus aureus. In brine shrimp's lethality model, nepetolide potently showed cytotoxic effect, with LC50 value of 8.7 µg/mL. When evaluated for antitumor activity in potato disc tumor assay, nepetolide exerted tumor inhibitory effect of 56.5 ±â€¯1.5% at maximum tested concentration of 1000 µg/mL. Nepetolide at 20 mg/kg reduced carrageenan-induced inflammation (P < .001 vs. saline group) in rat paw. Nepetolide dose-dependently (100-500 mg/kg) decreased acetic acid evoked writhes, as exhibited by diclofenac sodium. In-silico investigation of nepetolide was carried out against cyclooxygenase-2, epidermal growth factor receptor and lipoxygenase-2 targets. Virtual screening through Patchdock online docking server identified primarily hydrophobic interactions between ligand nepetolide and receptors proteins. Enhanced hydrogen bonding was predicted with Autodock showing 6-8 hydrogen bonds per target. These results indicate that nepetolide exhibits antioxidant, antibacterial, cytotoxic, anticancer, anti-inflammatory and analgesic activities and should be considered as a lead compound for developing drugs for the remedy of oxidative stress-induced disorders, microbial infections, cancers, inflammations and pain.

Novel pyridine-2,4,6-tricarbohydrazide thiourea compounds as small key organic molecules for the potential treatment of type-2 diabetes mellitus: In vitro studies against yeast α- and ß-glucosidase and in silico molecular modeling.

A range of novel pyridine-2,4,6-tricarbohydrazide thiourea compounds (4a-i) were synthesized in good to excellent yields (63-92%). The enzyme inhibitory potentials of these compounds were investigated against α- and ß-glucosidases because these enzymes play a crucial role in treating type-2 diabetes mellitus (T2DM). As compared to the reference compound acarbose (IC50 38.22 ± 0.12 µM), compounds 4i (IC50 25.49 ± 0.67 µM), 4f (IC50 28.91 ± 0.43 µM), 4h (IC50 30.66 ± 0.52 µM), and 4e (IC50 35.01 ± 0.45 µM) delivered better inhibition against α-glucosidase and were quite inactive/completely inactive against ß-glucosidase. The structure-activity relationship of these compounds was developed and elaborated with the help of molecular docking studies.

An Efficient Synthesis of bi-Aryl Pyrimidine Heterocycles: Potential New Drug Candidates to Treat Alzheimer's Disease.

A series of 13 novel pyrimidine-based sulfonamides 6a-m were synthesized in short periods of time under microwave conditions in good to excellent yield (54-86%). The chemical structures of these heterocycles consist of a central pyrimidine ring having a phenyl group and pyrimidine groups with sulfonamide motifs. The enzyme inhibitory potential of these compounds was investigated against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) because these enzymes play a crucial role in the treatment of Alzheimer's disease. As compared to the reference compound eserine (IC50 = 0.04 ± 0.0001 µM for AChE and IC50 = 0.85 ± 0.0001 µM for BChE), the IC50 values of the synthesized compounds ranged from 3.73 ± 0.61 µM to 57.36 ± 0.22 µM for AChE and 4.81 ± 0.16 µM to 111.61 ± 0.53 µM for BChE. Among these tested compounds, 6j having a -CH3 group was found to be the most potent one against both enzymes (AChE, IC50 = 3.73 ± 0.61 µM; BChE, IC50 = 4.81 ± 0.16 µM). Quantitative structure-activity relationship (QSAR) and molecular docking studies of the synthesized compounds were also performed.

Pyridine sulfonamide as a small key organic molecule for the potential treatment of type-II diabetes mellitus and Alzheimer's disease: In vitro studies against yeast α-glucosidase, acetylcholinesterase and butyrylcholinesterase.

This paper presents the efficient high yield synthesis of novel pyridine 2,4,6-tricarbohydrazide derivatives (4a-4i) along with their α-glucosidase, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibition activities. The enzymes inhibition results showed the potential of synthesized compounds in controlling both type-II diabetes mellitus and Alzheimer's disease. In vitro biological investigations revealed that most of compounds were more active against yeast α-glucosidase than the reference compound acarbose (IC50 38.25±0.12µM). Among the tested series the compound 4c bearing 4-flouro benzyl group was noted to be the most active (IC50 25.6±0.2µM) against α-glucosidase, and it displayed weak inhibition activities against AChE and BChE. Compound 4a exhibited the most desired results against all three enzymes, as it was significantly active against all the three enzymes; α-glucosidase (IC50 32.2±0.3µM), AChE (IC50 50.2±0.8µM) and BChE (IC50 43.8±0.8µM). Due to the most favorable activity of 4a against the tested enzymes, for molecular modeling studies this compound was selected to investigate its pattern of interaction with α-glucosidase and AChE targets.

Novel pyridine-2,4,6-tricarbohydrazide derivatives: design, synthesis, characterization and in vitro biological evaluation as α- and ß-glucosidase inhibitors.

A range of novel pyridine 2,4,6-tricarbohydrazide derivatives (4a-4h) were synthesized and its biological inhibition towards α- and ß-glucosidases was studied. Most of the compounds demonstrate to be active against α-glucosidase, and quite inactive/completely inactive against ß-glucosidase. A number of compounds were found to be more active against α-glucosidase than the reference compound acarbose (IC50 38.25±0.12µM); being compound 4d with the p-hydroxy phenyl motive the most active (IC50 20.24±0.72µM). Molecular modeling studies show the interactions of compound 4d with the active site of target α-glucosidase kinase.