Q2 Values Research Articles

Drug affinity to human serum albumin prediction by retention of cetyltrimethylammonium bromide pseudostationary phase in micellar electrokinetic chromatography and chemically advanced template search descriptors

The development of high-throughput methods for the estimation of physicochemical and biological properties of drug candidates is highly desired in the pharmaceutical landscape. Affinity to plasma protein is one of the most important biological properties, which should be taken under concern during the design and assessment of future potential medicines. The main goal of this study was to develop a quantitative retention-activity relationship model, with rationalized in vivo and in silico approach to predict the affinity to human serum albumin (HSA), which is one of the most important plasma proteins. To achieve this goal, a set of 27 chemically diverse drugs with known affinity to HSA were analyzed by micellar electrokinetic chromatography (MEKC). The proposed model for HSA affinity assessment was based on retention in hexadecyltrimethylmonium bromide (CTAB) pseudostationary phase and chemically advanced template search (CATS) pharmacophore descriptors. The comparison of various regression methods, namely multiple linear regression (MLR), partial least squares regression (PLS), orthogonal partial least squares (OPLS), and support vector machine (SVM) were performed to develop a model with highest predictability. The obtained models are suitable for the prediction of drug affinity to human serum albumin using retention factor determined by MEKC and CATS descriptors, and only slightly differ in terms of coefficients of determination, Q2 value calculated using leave-one-out cross-validation technique and root-mean-squared error of cross-validation (RMSECV) as well as root-mean-square error in prediction (RMSEP) obtained by external validation.

Development of Colorimetric Sensor Array for Instant Determination of Sodium Metabisulfite in Dried Longan

Sodium metabisulfite has been used as a pretreatment chemical to prevent the gradual discoloration and to slow down the spoilage process of dried longan. The excessive use of this sulfiting agent can result in allergic reactions, particularly for sulfite-sensitive people. In this research study, a colorimetric strip was fabricated to determine the concentration of sodium metabisulfite in dried longan. The detection was based on reactions of a series of colorimetric reagents including four different Fuchsine compounds and an Ellman’s regent. The maximum change of color was observed 3 min after the reactions. To perform a quantitative analysis, the image of the strip was captured using a commercial scanner, and it was converted into an RGB color model to be digitally analyzed by chemometrics. Using partial least square (PLS) regression, the calibration range (5.00–250.00 mg/kg) provided R2 and Q2 values of 0.994 and 0.908, respectively. The limits of detection and quantitation were 5.48 and 16.6 mg/kg, which were sensible for the detection of the sulfiting agent in dried longan samples. The developed colorimetric strip was applied to determine the concentration of metabisulfite in dried longan fruit purchased from local markets in Chiang Mai, Thailand. The results agreed well with the findings obtained from the standard reference method. The developed strip could be an alternative solution for rapid, simple, and low-cost detection of the sulfiting agent in dried agricultural products, where test results could be instantly obtained without the requirement of sophisticated analytical instruments.

Structural insights on vitamin D receptor and screening of new potent agonist molecules: structure and ligand-based approach

Vitamin D deficiency is one of the common clinical symptoms of severe chronic kidney disease (CKD) patients. Vitamin D receptor (VDR) is a part of the nuclear receptor family exerts vitamin D activation to maintain calcium/phosphorous homeostasis and bone metabolism. The reduction of VDR activity leads to vitamin D deficiency. In this study, we found three potent agonists for VDR protein on the structure and ligand-based screening methods. In the structure-based method, 792 compounds were screened. A 5-point pharmacophore (one hydrogen bond acceptor, two hydrophobic and aromatic rings (AHHRR)) was developed and used to obtain a predictive 3 D-Quantitative structure-activity relationship (QSAR), model. The acquire R2 and Q2 values are 0.8676 and 0.8523 respectively. Further, E-pharmacophore based screening, molecular docking (binding affinity), Molecular Mechanics-Generalized Born Surface Area (binding free energy), chemical reactivity (Density Functional Theory (DFT) study) and molecular dynamics (protein-ligand stability) analysis were done. Hence, the computational investigations demonstrate that the identified ligands such as TCM_1875, TCM_1874, and TCM_2868 showed promising agonist effect on VDR protein. Further validation and experiments need to be done to confirm the potency of the identified compounds shortly. Communicated by Ramaswamy H. Sarma

Quantum mechanics and 3D-QSAR studies on thienopyridine analogues: inhibitors of IKKβ

Inhibitor of kappa B kinase subunit β (IKKβ) is a main regulator of nuclear factor kappa B (NF-κB) and has received considerable attention as an attractive therapeutic target for the treatment of lung cancer or other inflammatory disease. A group of diversified thienopyridine derivatives exhibited a wide range of biological activity was used to investigate its structural requirements by using DFT and 3D-Quantitative structure activity relationship. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established using the experimental activity of thienopyridine derivatives. The cross-validation coefficient (q2) values for CoMFA and CoMSIA are 0.671 and 0.647 respectively, were achieved, demonstrating high predictive capability of the model. The contour analysis indicate that presence of hydrophobic and electrostatic field is highly desirable for biological activity. The results indicate that substitution of hydrophobic group with electron withdrawing effect at R4 and R6 position have more possibility to increase the biological activity of thienopyridine derivatives. Subsequently molecular docking and DFT calculation were performed to assess the potency of the compounds.

The black hole weak gravity conjecture with multiple charges

We study the effect of higher-derivative corrections on asymptotically flat, four-dimensional, dyonic black holes in low-energy models of gravity coupled to N U(1) gauge fields. For large extremal black holes, the leading mathcal{O} (1/Q2) correction to the extremality bound is calculated from the most general low-energy effective action containing operators with up to four derivatives. Motivated by the multi-charge generalization of the Weak Gravity Conjecture, we analyze the necessary kinematic conditions for an asymptotically large extremal black hole to decay into a multi-particle state of extremal black holes. In the large black hole regime, we show that the convex hull condition degenerates to the requirement that a certain quartic form constructed from the Wilson coefficients of the four- derivative effective operators, is everywhere positive. Using on-shell unitarity methods, we show that higher-derivative operators are renormalized at one-loop only if they generate local, on-shell matrix elements that are invariant tensors of the electromagnetic duality group U(N). The one-loop logarithmic running of the four-derivative Wilson coefficients is calculated and shown to imply the positivity of the extremality form at some finite value of Q2. This result generalizes an argument recently given by Charles [1], and shows that under the given assumptions the multi-charge Weak Gravity Conjecture is not a Swampland criterion.

Docking-Guided 3D-QSAR Studies of 4-Aminoquinoline-1,3,5-triazines as Inhibitors for <i>Plasmodium falciparum</i> Dihydrofolate Reductase

Mutations in Plasmodium falciparum dihydrofolate reductase (PfDHFR), together with other mutations, hinder malaria elimination in Southeast Asia due to multiple drug resistance. In this article, molecular docking-guided three-dimensional (3D) quantitative structure-activity relationship (QSAR) analysis of 4-aminoquinoline-1,3,5-triazines as inhibitors for the wild-type (WT) PfDHFR to identify the molecular determinants of the inhibitors binding are presented. Compounds 4-aminoquinoline-1,3,5-triazines were reported promising to be developed as the non-resistant drugs. The 3D-QSAR analysis resulted in the best model with the R2 and Q2 values of 0.881 and 0.773, respectively. By correlating the molecular interaction fields (MIFs) of the best model to the docking pose employed to guide the 3D-QSAR analysis, S108 residue of the WT-PfDHFR was unfortunately recognized as one of the molecular determinants. Since the S108 residue is one of the mutation points of the PfDHFR mutants, the subsequent design strategy should modify the morpholine moiety to avoid the interaction with the S108 residue of the WT-PfDHFR.

FTIR and HPLC-Based Metabolomics of Yacon Leaves Extracts (<i>Smallanthus sonchifolius</i> [Poepp & Endl.] H. Robinson) from Two Locations in Indonesia

Smallanthus sonchifolius [Poepp. & Endl.] H. Robinson (Asteraceae) also known as Yacon or insulin plant, is traditionally used for treating diabetes. Varying geographical origins and postharvest handling, however, seem to affect quantitative and qualitative metabolites in the leaves of Smallanthus sonchifolius [Poepp. & Endl.] H. Robinson (Yacon). The study was conducted to compare and differentiate metabolites profile/fingerprint of Yacon leaves which were grown and obtained from different locations in Pulau Jawa i.e. Lembang (Jawa Barat) and Wonosobo (Jawa Tengah). Three different solvents (95% ethanol, 50% ethanol and water) were used to synthesize Yacon leaves extracts, in order to determine the suitable solvent to produce discernable differentiation through FTIR and HPLC-based metabolomics. Principal Component Analysis (PCA) of FTIR data (4000–400 cm1 wavenumber) indicated that Yacon leaves extracted with ethanol at 95%, had a distinctive FTIR fingerprint profile when compared to others. However, the FTIR-based PCA could not differentiate the extracts based on their geographical origins, although PCA analysis of HPLC-data successfully differentiated the extracts based on their geographical origins. Furthermore, the prominent peak for the leaves extract from Lembang and Wonosobo as regards retention time, was observed at 21.59–25.10 min and 20.69–21.695 min respectively. Notably, R2Y and Q2 value obtained by cross-validation and permutation tests showed all multivariate models were statistically reliable. Overall, there is the need to conduct further research using a more sophisticated tool such as LC-MS, to identify which metabolites represented by the aforementioned FTIR and HPLC data.

Assessment of the effect of external risk factors on the success of an oil and gas construction project

PurposeConstruction projects in the oil and gas sector are greatly affected by external risk factors, especially those related to the economy, politics, security and stability factors. Hence, this research aimed to investigate the fundamental relationship between the external risk factors and their effects on the construction project success using Structural Equation Modeling method and PLS-SEM approach.Design/methodology/approachData collected through a structured survey distributed to projects teams in the oil and gas sectors in Yemeni companies involved in mega construction projects. A hierarchical model for assessing causative external risk factors and their effects on project success was developed and analyzed using Smart PLS 3 software of SEM.FindingsThe findings showed that economic, political, force majeure and security-related risk factors had a strong effect on project success. Besides, the Coefficient of Determination (R-squared value) equals 0.743, represented the proportion of variation in the dependent variable(s), which can be explained by one or more predictor variable. Moreover, the predictive relevance value Q2 is 0.375 above zero, which indicates that the conceptual model can predict the endogenous latent constructs. The calculated Goodness of Fit (GoF) Index of the model was 0.699, which shows that the developed model had substantial explanatory power to represent the relationship between the cause of external risk factors to and the effect on construction project success.Research limitations/implicationsThis research was limited to the oil and gas construction projects in Yemen as case study.Practical implicationsPractically, this study highlights the external risk factors that cause a negative effect on the success of oil and gas construction projects in Yemen. The research model of these factors is the first step in the risk management process to develop strategic responses for risks and explain the relationship between cause and effect on project success.Social implicationsThe model of external risks factors that cause the failure of construction projects helps develop response strategies for these risks, thereby increasing the chances of project success reflected in the oil and gas sector, which is a main tributary of the national economy in developing countries.Originality/valueThere is a need to improve the planning of economic and security performance as well as to mitigate political risk factors effects on project success and other risk factors discussed in this study, which effect on construction project success according to their priorities.

3D-QSAR and Docking Studies on Pyrimidine Derivatives as CSF-1R Inhibitors

Background: Colony Stimulating Factor-1 Receptor (CSF-1R) is associated with malignancy, invasiveness and poor prognosis of tumors, and pyrimidine derivatives are considered as a novel class of CSF-1R inhibitor. Methods: To explore the relationship between the structures of substituted pyrimidine derivatives and their inhibitory activities against CSF-1R, CoMFA and CoMSIA analyses, and molecular docking studies were performed on a dataset of forty-four compounds. Results: We found in CoMFA model including steric and electrostatic fields for the training set, the cross-validated q2 value was 0.617 and the non-cross-validated r2 value was 0.983. While, the crossvalidated q2 value was 0.637 and the non-cross-validated r2 value was 0.984 in CoMSIA Model which include steric, electrostatic and hydrophobic fields. 3D equipotential maps generated from CoMFA and CoMSIA along with the docking binding structures provided enough information about the structural requirements for better activity. Conclusion: The data generated from the present study helped us to predict the activity of new inhibitors and further design some novel and potent CSF-1R inhibitors.

In silico screening of FDA approved drugs on AXL kinase and validation for breast cancer cell line

AXL kinase has been over expressed in many tumors and its involvement in cell proliferation, migration, survival, and resistance makes the kinase as attractive therapeutic target for many cancers. In this study, we performed a virtual screening of the food and drug administration (FDA) approved drug molecule database against AXL kinase for repurposing studies of breast cancer. We have identified three non-cancer drugs with good binding energies were subjected to in vitro breast cancer MCF-7 cell lines. Three drug molecules showing the activity with good IC50 values toward the cancer cell line. We also carried out a 2 dimensional (2 D) quantitative structure activity relation (QSAR) studies on N-[4-(Quinolin-4-yloxy)phenyl]benzenesulfonamides derivatives to design potent inhibitors for AXL kinase. The final QSAR equation was robust with good predictivity and the statistical validation having R2 and Q2 values are 0.91 and 0.86, respectively. QSAR equation descriptors informs about the chemical properties of AXL inhibitors and helpful for designing novel inhibitors. Communicated by Ramaswamy H. Sarma

Docking Based 3D-QSAR Modelling of the Thiophene Analogues as a PTP1B Inhibitors

PTP1B inhibitors have been largely studied because of their promising therapeutic effects, PTP1B dephosphorylate (removal of Phosphate group) the insulin receptor (IR), Insulin Receptor Substrate (IRS), Janus Kinase-2(JAK2) & STAT3 which is present in the downstream of insulin and leptin receptor respectively. PTP1B inhibitors are used for the treatment of diabetes and obesity as a singly drug therapy due to simultaneously acting in both insulin and leptin signalling pathway. The clinical use of PTP1B inhibitors was restricted Selectivity is one of the major issues in the development of PTP1B inhibitors as drugs. Because all PTPs share a high degree of structural conservation in the active site, the pTyr (phosphotyrosine)-binding pocket, The various research results indicate that there are sub pockets adjacent to the PTP active site that can also be targeted for inhibitor development. These studies also provide a molecular basis for addressing and manipulating PTP inhibitor potency and specificity, and suggest a novel paradigm for the design of potent and specific PTP inhibitors Therefore, this work deals with the development of 3D-QSAR models, supported by molecular docking studies, to identify the key requirements underlying selective PTP1B inhibition. Our structure-based effort resulted in significant improvements in potency and selectivity. Docking based alignments and 3D-QSAR study have been performed on 46 molecules based on Thiophene ring scaffold derived from published literature. The QSAR model was selected having highest value of Q2 (0.6005) and Pearson-r (0.8539). The selected model also displayed the highest values of R2 (0.9750) and F-value (179.1) and the lowest SD (0.2230). The contour plots developed on the basis of the best model helped to reveal the essential structural features of Thiophene derivatives responsible for inhibition of PTP1B. The generated model and information revealed from it was utilized to design and predict new congeneric molecules that can be used as potential therapeutic agents.

A Double-Activity (Green Algae Toxicity and Bacterial Genotoxicity) 3D-QSAR Model Based on the Comprehensive Index Method and Its Application in Fluoroquinolones' Modification.

The comparative molecular similarity index analysis (CoMSIA) model of double-activity quinolones targeting green algae toxicity and bacterial genotoxicity (8:2) was constructed in this paper on the basis of the comprehensive index method. The contour maps of the model were analyzed for molecular modifications with high toxicities. In the CoMSIA model, the optimum number of components n was 7, the cross-validated q2 value was 0.58 (>0.5), the standard deviation standard error of estimate (SEE) was 0.02 (<0.95), F was 1265.33, and the non-cross-validated R2 value was 1 (>0.9), indicating that the model had a good fit and predicting ability. The scrambling stability test parameters Q2, cross-validated standard error of prediction (cSDEP), and dq2/dr2yy were 0.54, 0.25, and 0.8 (<1.2), respectively, indicating that the model had good stability. The external verification coefficient r2pred was 0.73 (>0.6), and standard error of prediction (SEP) was 0.17, indicating that the model had a good external prediction ability. The contribution rates of the steric fields, electrostatic fields, hydrophobic fields, hydrogen bond donor, and acceptor fields were 10.9%, 19.8%, 32.7%, 13.8%, and 22.8%, respectively. Large volume groups were selected for modification of ciprofloxacin (CIP), and the derivatives with increased double-activity characterization values were screened; the increase ratio ranged from 12.31–19.09%. The frequency of derivatives were positive and total energy, bioaccumulation, and environmental persistence was reduced, indicating that the CIP derivatives had good environmental stability and friendliness. Predicted values and CoMSIA model constructed of single activities showed that the CoMSIA model of double activities had accuracy and reliability. In addition, the total scores of the derivatives docking with the D1 protein, ferredoxin-NADP (H) reductases (FNRs), and DNA gyrase increased, indicating that derivatives can be toxic to green algae by affecting the photosynthesis of green algae. The mechanism behind the bactericidal effect was also explained from a molecular perspective.

In silico identification of hydantoin derivatives: a novel natural prolyl hydroxylase inhibitor

Alzheimer’s disease (AD) is the most common dementia in late life memory related issues. It is estimated that worldwide 46.8 million people suffer from dementia. The hypoxia inducible factor (HIF) upregulation could be a potential neuroprotective strategy by modulating the multiple survival pathways in AD. Hence, the development of small molecules that induce HIF-α activation via inhibition of prolyl hydroxylase enzyme (PHD) has been suggested as a potentially useful therapeutic strategy for the treatment of AD. Thus, to unveil a novel human PHD inhibitor, 2D-QSAR (Quantitative Structure Activity Relationship) modeling was performed with the 213 PHD inhibitors reported in the USA patent database. Best model with the r2 score of 0.8273 and q2 value of 0.8284 with dendritic fingerprint was developed and visualized by kernel partial least squares (KPLS) methods, which were used for visualization and screening of natural/derivative compounds database for novel and effective drug or scaffold. The docking was performed as a secondary strategy for screening the top 5000 compounds retrieved by 2D-QSAR based screening. Further, the docked complexes were screened by molecular dynamics (MD) simulation and molecular mechanics/generalized Born surface area (MM-GBSA) based binding free energy calculations to determine the binding energy of the inhibitors and to identify crucial interacting energy contributors. Three leads have demonstrated good binding free energy and the better binding affinity for PHD compared to other selected ligands. Thus, the results obtained from QSAR, docking and MD simulations depicted that hydantoin scaffold could be effectively used as a potent inhibitor toward human PHD in AD therapeutics.Communicated by Ramaswamy H. Sarma

Investigation of high energy behaviour of HERA data

We analyse the high precision HERA F2 data in the low-x, x<0,01, and very-low-x, x<0.001, regions using λ-fits. λ is a measure of the rate of rise of F2 defined by F2∝(1/x)λ. We show that λ determined in these two regions, at various Q2 values, is systematically smaller in the very-low-x region as compared to the low-x region. We discuss some possible physical interpretations of this effect.

Quantitative structure–activity relationships analysis, homology modeling, docking and molecular dynamics studies of triterpenoid saponins as Kirsten rat sarcoma inhibitors

Oncogenic Kirsten RAt Sarcoma (KRAS) mutations are attractive targets in non-small-cell lung cancer (NSCLC). Thus, the objective of this work is to discover promising inhibitors that target this protein using in silico methods that have become increasingly cost-effective in research and development of drugs. In this study, 24 triterpenoid saponins were selected for designing the potent inhibitors using different methods: quantitative structure activity relationships (QSAR) analysis, homology modeling, as well as molecular docking, molecular dynamics (MD) simulation and in silico Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) screening. The selected model was presented high-squared cross-validation coefficient Q2 = 0.85, and external validation R2pred = 0.75. In addition, the best comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models presented high values of Q2 = 0.77 and 0.784 and values of R2pred = 0.87 and 0.83, respectively. After that, homology modeling was carried out for modeling the selected target and then validated by both Ramachandran plot and Qualitative Model Energy ANalysis (QMEAN) score of 0.83, indicating the best accuracy of the modeled protein with the experimental results. Furthermore, molecular docking study was conducted to better understanding the binding mechanism of homologous protein with triterpenoid saponins. In addition, MD simulations confirmed the stability of the selected complex systems during 10,000 femtosecondes (fs). According to these studies, three molecules were picked out as potential inhibitors. Indeed, the oral bioavailability and the toxicity of the predicted triterpenoid saponins have been found respecting the ADMET properties. Communicated by Ramaswamy H Sarma

Integrated molecular docking, 3D QSAR and molecular dynamics simulation studies on indole derivatives for designing new Pim-1 inhibitors

Pim-1 is one of the isoforms of pim proteins comprising pim-1, pim-2 and pim-3. It was basically recognized as proviral integration moloney murine leukemia virus which is associated with T-cell lymphomogenesis. Pim-1 is known to play a crucial role in cell cycle progression and acts as downstream target for the JAK/STAT signaling pathway. Recently it has emerged as a hopeful therapeutic target for cancer treatment as deregulation or over expression of pim causes hematologic cancers. In present article molecular docking based three dimensional quantitative structure and activity relationship and molecular dynamics simulation studies have been carried out on indole derivatives reported as pim-1 inhibitors. Initially docking was carried out to obtain the receptor specific orientation of the molecules and later to understand the structural requirements of pim-1 inhibitors robust 3 D QSAR models were built using CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methods. The reliability of the models was established from conventional (r2) and cross validated (q2) values of 0.982, 0.524 for CoMFA and 0.974, 0.586 for CoMSIA respectively. Further the predictive ability of the model was evaluated using a test set of 17 molecules. The docking studies revealed that interaction with Glu 121 is vital for binding of inhibitors to pim-1. Based on the outcome of the results new molecules with improved activity were designed. Furthermore, MD simulations were also performed to examine the stability of interactions and investigate the pivotal role of Glu 121.

Prediction of inhibition of influenza virus neuraminidase of various strains by using a generalized model constructed using the data on the position of known ligands

Several variants of models for predicting the IC50 values of inhibitors of influenza virus neuraminidase are presented for both individual strains and for combinations of data for neuraminidases of several strains. They are based on the use of calculated energy contributions to the amount of change in the free energy of enzyme-inhibitor complexes. In contrast to previous works, aimed at the complex modeling, we added a procedure of comparison of the docking variants with one of the neuraminidase inhibitors, for which the structure of the complexes was determined experimentally. The choice of the comparison structure was made according to the similarity of structures evaluated using the Tanimoto metrics and the limit of the RMSD value for a similar part of the structure was no more than 2 Å. Using this limitation and filtering datasets for a particular strain by the Q2 value obtained in the leave-one-out control procedure it is possible to construct equations for predicting the IC50 value with a Q2 value close to the minimum confidence threshold (0.57 in this work). Taking into consideration that in this version of the prediction, a minimum set of energy contributions is used, which does not provide for expensive calculations of entropy contributions, the result obtained supports the correctness of using a generalized model based on the data on the position of known ligands to predict the inhibition of neuraminidase of the influenza virus of various strains.

First principles study of electronic and nonlinear optical properties of A-D-π-A and D-A-D-π-A configured compounds containing novel quinoline-carbazole derivatives.

Materials with nonlinear optical (NLO) properties have significant applications in different fields, including nuclear science, biophysics, medicine, chemical dynamics, solid physics, materials science and surface interface applications. Quinoline and carbazole, owing to their electron-deficient and electron-rich character respectively, play a role in charge transfer applications in optoelectronics. Therefore, an attempt has been made herein to explore quinoline–carbazole based novel materials with highly nonlinear optical properties. Structural tailoring has been made at the donor and acceptor units of two recently synthesized quinoline–carbazole molecules (Q1, Q2) and acceptor–donor–π–acceptor (A–D–π–A) and donor–acceptor–donor–π–acceptor (D–A–D–π–A) type novel molecules Q1D1–Q1D3 and Q2D2–Q2D3 have been quantum chemically designed, respectively. Density functional theory (DFT) and time-dependent density functional theory (TDDFT) computations are performed to process the impact of acceptor and donor units on photophysical, electronic and NLO properties of selected molecules. The λmax values (321 and 319 nm) for Q1 and Q2 in DSMO were in good agreement with the experimental values (326 and 323 nm). The largest shift in absorption maximum is displayed by Q1D2 (436 nm). The designed compounds (Q1D3–Q2D3) express absorption spectra with an increased border and with a reduced band gap compared to the parent compounds (Q1 and Q2). Natural bond orbital (NBO) investigations showed that the extended hyper conjugation and strong intramolecular interaction play significant roles in stabilising these systems. All molecules expressed significant NLO responses. A large value of βtot was elevated in Q1D2 (23 885.90 a.u.). This theoretical framework reveals the NLO response properties of novel quinoline–carbazole derivatives that can be significant for their use in advanced applications.

Analysis of Sociodemographic and Information Factors on Family Behaviour in Early Detection of High-Risk Pregnancy

Introduction: Pregnancy and childbirth are physiological processes experienced by women, but they sometimes have risky conditions. There are still many pregnant women and their families who are unable to detect a high-risk of pregnancy early. This study aims to determine family behaviour in conducting early detection of a high-risk of pregnancy in terms of sociodemographic and information factors.Methods: This study uses an explanatory survey design with a cross sectional design. The sample size of this study was 146, with simple random sampling. The independent variables were sociodemographic factors (age, gender, ethnicity, education, income and religion) and information factors (experience, and media exposure) while the dependent variable is family behaviour. The instrument with the questionnaire used the Likert scale. The data was analysed using partial least square.Results: The results showed that Structural Equation Modelling-Partial least square (SEM-PLS) statistical analysis, through Confirmatory Factor Analysis (CFA), obtained sociodemographic factors on family behaviour of 1,999, and information factors on family behaviour of 13,78. The value of the influence of sociodemographic factors (0.102) and the value of the influence of information factors (0.754). R2 (0.63) and Q2 value of 0.65.Conclusion: Sociodemographic factors and information factors significantly influenced family behaviour factors in early detection of high-risk of pregnancy. Information factors have a greater effect on family behaviour than sociodemographic factors. Midwives as health service providers at the health care centre need to optimize family empowerment through health information efforts in health promotion efforts. Further research requires the involvement of other factors to improve family behaviour, especially in the ability of families to detect early high-risk pregnancies.

GENDER DIFFERENCES INDIVIDUAL-TYPOLOGICAL CHARACTERISTICS IN ADOLESCENT WITH ESSENTIAL ARTERIAL HYPERTENSION

Relevance. Certain personality traits can contribute to the development of diseases, including cardiovascular disease. It has been shown that in patients with essential hypertension (EH) neuroticism is more pronounced, and the level of blood pressure (BP) has a close relationship with the level of depression, anxiety, and stress.&#x0D; Objective of the study was to establish the individual-typological characteristics of adolescents with EH.&#x0D; Materials and methods. In the Kyiv city center for the diagnosis and correction of autonomic dysfunctions in children of Children's Clinical Hospital No. 6, a comprehensive clinical and psychological study was conducted in 34 adolescents (6 girls, 28 boys) aged 13-17 years (average 14.70 ± 1.46 years),who were hospitalized for EH. A multifactorial study of the personality of R.B. Kettell was used.&#x0D; Results. According to the data of ambulatory monitoring of BP in 25 adolescents stable, 6 labile form of hypertension were revealed, in 3 - unstable BP.&#x0D; On average, in the personality profile of adolescents with EH, relatively high values of factors E (dominance), Q3 (arrogance), O (hypotymia, guilt, anxiety) were revealed (6.39 ± 2.01 points, 6.22 ± 1,99 and 6.16 ± 2.61 points respectively) and low values on the factors M (practicality, traditionalism) and I (rigidity, realisticness) (respectively 4.00 ± 1.98 points and 4.03 ± 1.92 points).&#x0D; In boys with EH, compared to girls, the mean of factors I and Q5 were significantly decreased (3.68 ± 1.61 versus 6.00 ± 1.90; P &lt;0.05 and 4.89 ± 1.73 vs. 6.50 ± 1.22; P &lt;0.05), and the factor C (5) was higher on average (14 ± 2.17 vs. 3.33 ± 2.07; P &lt;0.05), which corresponds to more masculine personality traits (low sensitivity, courage, etc.).&#x0D; The daily average values of diastolic blood pressure and hemodynamic blood pressure, as well as the average daily heart rate, were significantly inverse correlated (P &lt;0.05) with the value of factor Q2 (r = -0.50, r = -0.35, r = -0.50, respectively).&#x0D; On average, the personality profile of adolescents with EH is characterized by a tendency to dominance, arrogance, hypotension, guilt, anxiety, practicability, tradition, rigidity, and realism, which may be explained by the significant dominance of boys. Conformity, and therefore dependence on one's opinion, in adolescents with EH correlated with an increase in diastolic blood pressure and an average daily heart rate.&#x0D; Conclusion. These gender personality traits of adolescents with EH (conformity and anxiety) should be considered when developing a program of medical and psychological care.