Ability Of Complexes Research Articles

Impact of Experimentally Induced Pain on Logical Reasoning and Underlying Attention-Related Psychophysiological Mechanisms

Background. Pain is known to negatively impact attention, but its influence on more complex cognitive abilities, such as logical reasoning, remains inconsistent. This may be due to compensatory mechanisms (e.g., investing additional resources), which might not be detectable at the behavioral level but can be observed through psychophysiological measures. In this study, we investigated whether experimentally induced pain affects logical reasoning and underlying attentional mechanisms, using both behavioral and electroencephalographic (EEG) measures. Methods. A total of 98 female participants were divided into a pain-free control group (N = 47) and a pain group (N = 51). Both groups completed the Advanced Progressive Matrices (APM) task, with EEG recordings capturing task-related power (TRP) changes in the upper alpha frequency band (10–12 Hz). We used a mixed design where all participants completed half of the APM task in a pain-free state (control condition); the second half was completed under pain induction by the pain group but not the pain-free group (experimental condition). Results. Logical reasoning performance, as measured by APM scores and response times, declined during the experimental condition, compared to the control condition for both groups, indicating that the second part of the APM was more difficult than the first part. However, no significant differences were found between the pain and pain-free groups, suggesting that pain did not impair cognitive performance at the behavioral level. In contrast, EEG measures revealed significant differences in upper alpha band power, particularly at fronto-central sites. In the pain group, the decrease in TRP during the experimental condition was significantly smaller compared to both the control condition and the pain-free group. Conclusions. Pain did not impair task performance at the behavioral level but reduced attentional resources, as reflected by changes in upper alpha band activity. This underscores the importance of incorporating more sensitive psychophysiological measures alongside behavioral measures to better understand the impact of pain on cognitive processes.

Investigation of pivalic acid-derived organotin(IV) carboxylates: Synthesis, structural insights, interaction with biomolecules, and computational studies

Herein, six homoleptic and heteroleptic tri-organotin(IV) complexes (1–6) of pivalic acid (HL) were synthesized using 2,2′-bipyridine (bipy) and organotin(IV) chlorides, with a general formula of R3SnL/R3SnLbipy, where R = CH3, C4H9, and C6H5. The structure of the complexes was established in the solid phase via FT-IR spectroscopy and in solution through multinuclear NMR spectroscopy. The variety of coordination modes was implemented by the carboxylate group of pivalic acid, which is reflected in the FT-IR data and also supported by the single crystal XRD analysis for complex 5. The single crystal data revealed the presence of a five-coordinated distorted trigonal bipyramidal geometry for complex 5. The structural and electronic details of the complexes were also evaluated by the application of density functional theory through the Lanl2DZ basis set. The ability of complexes to inhibit the AChE and BChE was assessed in vitro as well as theoretically through molecular docking studies and the results were promising. The complexes 4 and 5 showed high inhibitory potency and could be a potential drug candidate. The DNA binding mode of the complexes was studied using UV–Vis spectroscopy and cyclic voltammetry. The findings revealed that these complexes readily intercalate into DNA via a spontaneous process. Additionally, an effective binding of the complexes with surfactant cetyl trimethyl ammonium bromide (CTAB) through a spontaneous process also proved them valuable in pharmacology.

Robot inverse kinematics solution for center selection battle royale optimization algorithm

In order to solve the problems of high time complexity and insufficient global exploration ability of the battle royale optimization algorithm, this paper proposes an improved battle royale optimization algorithm based on chaos mapping, center selection and elite adaptive strategy. Through benchmark function testing, compared to particle swarm optimization algorithm, whale optimization algorithm, and the battle royale optimization algorithm, the improved algorithm significantly reduces time complexity and notably enhances convergence precision, speed, and stability. The improved algorithm is applied to the inverse kinematics problem of robots. The accuracy and The stability of the improved algorithm is better than those of the traditional battle royale optimization algorithm, it demonstrates superior solving precision and stability, proving its practicality and potential for development in solving robot inverse kinematics problems.

SF6 Gas Humidity Prediction Model Based on Deep Learning

SF6 gas is widely used in Gas Insulated Switchgear(GIS) as an insulating and arc extinguishing medium in electric power industry. However, SF6 gas humidity has a significant impact on the performance and reliability of GIS equipment. The accurate prediction of humidity level is one of the keys to ensure the long-term stable operation of GIS equipment. Traditional humidity prediction methods are often limited by model complexity and data processing ability, which is difficult to meet the actual demand. In this paper, deep learning, as a powerful data-driven approach, shows great potential in gas humidity prediction. An efficient SF6 gas humidity prediction model for GIS equipment is constructed based on deep learning algorithm. The deep learning model can learn complex feature representations from a large number of historical data, and then accurately predict SF6 gas humidity.

High-Resolution Reconstruction of Temperature Fields Based on Improved ResNet18.

High-precision measurement of temperature value distributions in production scenarios is of great significance for industrial production, but traditional temperature field reconstruction algorithms rely on the design of manual feature extraction methods with high computational complexity and poor generalization ability. In this paper, we propose a high-precision temperature field reconstruction algorithm based on deep learning, using an efficient adaptive feature extraction method for temperature field reconstruction. We design an improved temperature field reconstruction algorithm based on the ResNet18 neural network; introduce the CBAM attention mechanism in the model; and design a feature pyramid, using M-FPN, a multi-scale feature aggregation network fusing PAN and FPN, to make the extracted feature information propagate multi-dimensionally among different layers to improve the feature characterization ability. Finally, the mean square error is used to guide the model to optimize the training so that the model pays more attention to the data and reduces the large error to ensure that the gap between the predicted value and the real value is small. The experimental results show that the reconstruction accuracy of the improved algorithm presented in this paper is significantly better than that of the original algorithm in the case of typical peaked temperature field distributions.

Fabrication of Uniform Melatonin Microparticles Potentially for Nasal Delivery: A Comparison of Spray Drying and Spray Freeze Drying.

Insomnia is a major health concern, and melatonin (MLT) is key for initiating sleep. Delivering MLT nasally can enhance brain bioavailability by targeting the olfactory region. This study aimed to fabricate MLT embedded microparticles for nasal delivery. MLT-cyclodextrin (CD) derivatives complex microparticles (MCCMPs) were fabricated by spray drying and spray freeze drying MLT and CD derivative solutions. Phase solubility and 1H-1H ROSEY NMR analysis assessed MLT-CD assembly. The effects of formulation compositions and process parameters on microparticle structural attributes were investigated. The in vitro nasal release and deposition performances were evaluated by a modified paddle-over-disk apparatus and 3D-printed nasal cavity cast, respectively. Sodium sulphobutylether-β-cyclodextrin (SBE-β-CD) exhibited the best complexation ability with MLT, with the indole structure of MLT included in its cavity. Spray dried MCCMPs showed dense structure with high density, while the spray freeze dried counterpart showed the brittle and porous structure with low density. Despite the porous structure may promote the release rate of spray freeze dried samples, the high hydrophilicity of the CD derivative overshadows this advantage. Samples prepared by spray drying not only exhibited rapid release rates but also could deposit more effectively in the olfactory region, as they avoid breakage due to their higher mechanical strength. The optimal sample showed ~ 86.70% of the MLT released at 20min and ~ 10.57% of the deposition fraction in the olfactory region. This work compares MCCMPs fabricated by spray drying and spray freeze drying, providing the optimal formulation and process combinations.

МНОГОУРОВНЕВАЯ СИСТЕМА ОБЕСПЕЧЕНИЯ ЭКОНОМИЧЕСКОЙ БЕЗОПАСНОСТИ

Economic security is an integral part of the overall security of the state. It is like the foundation on which the prosperity and stability of the country are built. Economic independence, sustainable development and the well-being of society directly depend on how well our economy is protected from internal and external threats. The efficiency of enterprises and organizations is also closely related to the level of economic security. The article highlights the close relationship between food and economic security of the state. The ability of the agro-industrial complex to provide the population with high-quality and affordable food directly affects the stability of the economy, social cohesion and political independence of the country. The authors note that the balance between domestic production and food imports plays a key role in ensuring food security and allows the state to effectively respond to external challenges.

К ВОПРОСУ О ФОРМИРОВАНИИ ИНОЯЗЫЧНОЙ ТЕКСТОВОЙ КОМПЕТЕНЦИИ

The article is devoted to the characterization of textual competence as a complex linguistic ability integrating language experience in various types of speech activity. As a result of the analysis, the content and structure of the concept of «textual competence» are characterized, the stages of its formation are revealed. Textual competence is considered in the work as an independent competence that is not part of a more general communicative competence. The study emphasizes the mastery of textual competence as a basic elementary cultural skill. The key role of textual competence in the processes of personal socialization and intercultural communication is due to the consideration of the communication process as the implementation of a language system in texts. The foundations of textuality as a set of inherent text parameters are analyzed. In the structure of textual competence, knowledge of the language system, language units and the rules of their combination are highlighted, as well as mechanisms for generating speech utterance, taking into account communicative tasks, due to the nature of the communicative situation. The complex nature of textual competence is revealed, due to the multidimensional nature of the text as a linguistic phenomenon. The research material confirms that the formation of foreign language textual competence in the process of learning a foreign language is aimed not only at developing students’ skills to work with foreign language texts, but also intercultural competence.

Selective dealumination of large pore Zeolite Beta for effective Brønsted acid site utilization

Tuning of Al sites through spatial and geometric distribution is a novel pursuit for deterministic catalytic performance. To design an efficient Zeolite Beta for phenol alkylation with optimal physicochemical attributes, we conducted a systematic study with a series of dicarboxylic acids to selectively extract the framework and/or non-framework Aluminium. Herein, the post-synthetic treatment resulted in dealuminated catalysts of silicon-to-aluminum ratio ∼15–53. Extensive Al and Si NMR studies glean the selective extraction of aluminum from the zeolitic framework along with recomposition in T sites. The potency study alludes to the convoluted role of pH, chelating ability, and/or site accessibility for complexation. The differentiated Al extraction results in the emergence of unique super-strong acid sites. The novelty of our approach was established using phenol alkylation with cyclohexanol wherein we observed the highest conversion and desired CC alkylated product formation for the malonic acid-treated Zeolite Beta.

CNN-Informer: A Hybrid Deep Learning Model for Seizure Detection on Long-term EEG

Timely detecting epileptic seizures can significantly reduce accidental injuries of epilepsy patients and offer a novel intervention approach to improve their quality of life. Investigation on seizure detection based on deep learning models has achieved great success. However, there still remain challenging issues, such as the high computational complexity of the models and overfitting caused by the scarce availability of ictal electroencephalogram (EEG) signals for training. Therefore, we propose a novel end-to-end automatic seizure detection model named CNN-Informer, which leverages the capability of Convolutional Neural Network (CNN) to extract EEG local features of multi-channel EEGs, and the low computational complexity and memory usage ability of the Informer to capture the long-range dependencies. In view of the existence of various artifacts in long-term EEGs, we filter those raw EEGs using Discrete Wavelet Transform (DWT) before feeding them into the proposed CNN-Informer model for feature extraction and classification. Post-processing operations are further employed to achieve the final detection results. Our method is extensively evaluated on the CHB-MIT dataset and SH-SDU dataset with both segment-based and event-based criteria. The experimental outcomes demonstrate the superiority of the proposed CNN-Informer model and its strong generalization ability across two EEG datasets. In addition, the lightweight architecture of CNN-Informer makes it suitable for real-time implementation.

Insights into Advances and Applications of Biomaterials for Nerve Tissue Injuries and Neurodegenerative Disorders.

The incidence of nerve tissue injuries, such as peripheral nerve injury, spinal cord injury, traumatic brain injury, and various neurodegenerative diseases (NDs), is continuously increasing because of stress, physical and chemical trauma, and the aging population worldwide. Restoration of the damaged nervous system is challenging because of its structural and functional complexity and limited regenerative ability. Additionally, there is no cure available for NDs except for medications that provide symptomatic relief. Stem cells offer an alternative approach for promoting damage repair, but their efficacy is limited by a compromised survival rate and neurogenesis process. To address these challenges, neural tissue engineering has emerged as a promising strategy in which stem cells are seeded or encapsulated within a suitable biomaterial construct, increasing cell survival and neurogenesis. Numerous biomaterials are utilized to create different types of constructs for this purpose. Researchers are trying to develop ideal scaffolds that combine biomaterials, cells, and molecules that exactly mimic the biological and mechanical properties of the tissue to achieve functional recovery associated with neurological dysfunction. This review focuses on exploring the development and applications of different biomaterials for their potential use in the diagnosis, therapy, nerve tissue regeneration, and treatment of neurological disorders.

Heteroleptic complexes of hydrazone Scaffold of picolinoyl N- oxide and 2,4 dihydroxy phenyl moieties; evaluation of antioxidant activity, DNA and protein binding properties and in vitro antiproliferation studies

The present study deals with design and synthesis of new mononuclear Cu(II), Co(II), Ni(II) and Zn(II) metal complexes of hydrazone of 2-(2-(2,4-dihydroxybenzylidene)hydrazinecarbonyl)pyridine-1-oxide (H2L), in a view to study their potential relevance for the biological applications. Structural aspects of the title compound (H2L) and metal complexes synthesized were evaluated by spectral and analytical methods viz. 1H NMR, 13C NMR, LC-MS, FT-IR, UV–Visible, SEM, EDX, Powder XRD, ESR, TGA and DTA. Ligational properties of H2L were explored by employing pH metric equilibrium studies for recognizing metal ion binding potential donor sites, and further HyperChem 7.5 software for computing properties of frontier molecular orbitals to ascertain orientation of highest occupied molecular orbitals from which presumably electrons are donated to metal ion in complex formation. The affinity of all title compounds to bind with CT-DNA and the type of interaction, therein have been studied by conducting UV–VIS absorption and fluorescence emission titrations. The protein-binding ability of all metal complexes with two serum proteins (BSA and HSA) were explored by absorption titrations, and further fluorescence titrations for BSA binding were also performed. Antioxidant activity of the title compounds was carried out by the method of free radical scavenging using spectrophotometric technique. Additionally, cytotoxicity of all metal complexes and ligand was measured by CTG cell proliferation assay after treating them with MDA-MB-231 and SKOV-3 cell lines. The cell cycle arrest and apoptosis assay in above cell lines after treatment with title compounds were also investigated by flow cytometry. In addition, molecular docking studies at target CDK2 protein inferred binding affinity of the title compounds through non covalent bonding interactions.

Specific and shared cognitive predictors of drawing and block building in typically developing children.

Spatial construction is a complex ability involving attention, global/local visual processing, mental representation, visuo-motor coordination and, to varying extent, working memory and executive functions, and verbal abilities. In developmental neuropsychology, little attention has been paid to comprehend whether and to what extent the above cognitive processes are involved in two main spatial construction tasks, that is drawing and block building. We used path analysis to test shared and specific effects of verbal and spatial working memory, spatial attention, inhibition, verbal abilities (vocabulary and naming), figure disembedding, mental rotation, and visual-motor coordination, as well as of demographics (sex, age and socio-economic status), on two classical drawing (Rey-Osterrieth Complex Figure; ROCF) and block building (Block design; BD) tasks in a sample of 195 typically developing children (age range: 7-11 years). Figure disembedding and visuo-motor coordination were the only shared predictors of both spatial construction tasks. Moreover, ROCF score was directly related with spatial attention and inhibition, while BD score was directly related with sex, vocabulary, mental rotation and backward spatial working memory. These findings distinguish between abilities involved in spatial construction regardless of the type of task and those specifically related to ROCF or Block Design, thus providing clues relevant to neuropsychological assessment and intervention in children with spatial construction disorders.

The complex affective and cognitive capacities of rats

For several decades, although studies of rat physiology and behavior have abounded, research on rat emotions has been limited in scope to fear, anxiety, and pain. Converging evidence for the capacity of many species to share others’ affective states has emerged, sparking interest in the empathic capacities of rats. Recent research has demonstrated that rats are a highly cooperative species and are motivated by others’ distress to prosocial actions, such as opening a door or pulling a chain to release trapped conspecifics. Studies of rat affect, cognition, and neural function provide compelling evidence that rats have some capacity to represent others’ needs, to instrumentally act to improve their well-being, and are thus capable of forms of targeted helping. Rats’ complex abilities raise the importance of integrating new measures of rat well-being into scientific research.

Object permanence in rooks (Corvus frugilegus): Individual differences and behavioral considerations.

Piagetian object permanence (OP) refers to the ability to know that an object continues to exist when out of sight: In humans, it develops in six stages. Species of great apes, other mammals, and birds (parrots, corvids, and pigeons) have been shown to possess partial or full OP, which is a prerequisite for more complex physical cognition abilities they may possess. In birds, the greatest variation is in Stage 6 (invisible displacements) and in "A-not-B" errors-incorrectly persevering in searching an empty location rewarded previously. Caching abilities have been invoked as holding explanatory power over results in corvids, for which this error is sometimes completely absent. The rook (Corvus frugilegus), a cognitively advanced, social, caching corvid, has not yet been studied for OP. This study applies tasks of one OP scale commonly adapted for nonhuman animals, Uzgiris and Hunt's Scale 1, as well as later-conceived tasks 16 and S, to a sample of adult, captive rooks. One rook demonstrated full OP (Stage 6b, multiple invisible displacements), whereas other individuals varied, attaining between Stages 5a (single visible displacements) and 6a (single invisible displacements). Like some corvids, a few made transient "A-not-B" errors. Behavioral considerations potentially underlying observed individual variation in results in rooks, including dominance, neophobia, past experiences, and individual idiosyncrasies, are examined. Rooks, like other corvids, possess well-developed OP abilities, and these results support the idea that exertion of executive control is required to avoid "A-not-B" errors, rather than caching abilities or developmental age, as previously suggested.

A highly stable, rapid and sensitive fluorescent probe for Al3+ and pefloxacin based on enhanced fluorescence of a Co(II) coordination polymer

Fabricating functional coordination polymer (CP) architectures and exploiting it as fluorescence sensors for detecting diverse metal ions and antibiotics, have attracted extensive attention. Based on a rarely-used benzimidazole-derived ligand 2,2′-bis-(2-pyridin-3-yl-vinyl)-3H,3′H-[5,5]bibenzoimidazole (L), a new CP {[Co(L)0.5(tbip)]·H2O}n (H2tbip =5‑tert-butylisophthalic acid) (1) was synthesized under solvothermal condition and characterized. Complex 1 reveals a two-dimensional network with the type of topology of 3,4,5L7. Complex 1 possesses excellent thermal and chemical stability. The fluorescence detection ability of complex 1 was explored and demonstrated that complex 1 can be used as the first fluorescent turn-on sensor to sense Al3+ and pefloxacin (PEF) with a low detection limit and fast response. The fluorescence enhancement mechanism was investigated in detail.

Decomposition of Hydrogen Peroxide in Presence of DimethylglyoximatoNickel Complexes as Catalysts: Catalase-Like Activity

The development in coordination chemistry in recent years raise hopes that synthetically produced metal complexes could mimic many biochemical systems widely found in nature. There is a certain analogy between nature and organometallic systems. A large number of biological metal complexes are known, including oxygen carriers like hemoglobin in the blood, which contains a ferrous ion; respiratory enzymes; those involved in protein hydrolysis; and vitamin B12, which is only active in the presence of cobalt in the trivalent state. The Nickel (III), in addition to Fe-S clusters, was an essential component in hydrogenases. Since then, nickel (III) complexes have been used as models for studying the catalytic function of certain enzymes (hydrogenases). In this context, a study on the catalytic ability of dimethylglyoximato-nickel complexes as peroxiredoxases in the dismutation or oxidation of hydrogen peroxide was conducted. The results were discussed, commented upon, and a reaction mechanism was proposed. The results seem encouraging, regarding the effect of the complexation on catalase- like activity.

Exploring the DNA-binding and anticancer potential of polypyridyl ruthenium(II) complexes

Organometallic medicines based on ruthenium (Ru) have attracted interest as chemotherapeutic and bioimaging agents due to their low toxicity and superior physical optical characteristics. However, there are still no ideal candidates in clinical trials due to the lack of understanding of the structure-activity relationships (SARs) of polypyrodyl Ru(II) complexes. Though increasing the electron-donating ability of the ligands has been proven to benefit bioactivity due to the fast hydroxylation rate between chlorine and DNA, the total electronic effects are much more important, especially for the binding modes between Ru(II)-polypyridyl complexes and DNA. By evaluating the electron-donating ability of the ligand complexes 1 - 4 through density functional theory (DFT) calculations, bioactivities tests, and docking studies, we investigated the relationship between the structures of Ru(II) complexes and cytotoxicity. Our findings showed that it was insufficient to merely consider the impact of electron-donating effects on biological activities in place of interaction modes. Furthermore, the cellular imaging study investigated the complex with phenyl substituents (1) and confirmed that the main target was DNA. Besides, the “off-on” emission phenomena of complex 1 indicated that there is also covalent interaction with DNA. These findings offer valuable insight into the development of SARs of polypyrodyl Ru(II) complexes.

Applicability of Quantum Dots in Breast Cancer Diagnostic and Therapeutic Modalities-A State-of-the-Art Review.

The increasing incidence of breast cancers (BCs) in the world population and their complexity and high metastatic ability are serious concerns for healthcare systems. Despite the significant progress in medicine made in recent decades, the efficient treatment of invasive cancers still remains challenging. Chemotherapy, a fundamental systemic treatment method, is burdened with severe adverse effects, with efficacy limited by resistance development and risk of disease recurrence. Also, current diagnostic methods have certain drawbacks, attracting attention to the idea of developing novel, more sensitive detection and therapeutic modalities. It seems the solution for these issues can be provided by nanotechnology. Particularly, quantum dots (QDs) have been extensively evaluated as potential targeted drug delivery vehicles and, simultaneously, sensing and bioimaging probes. These fluorescent nanoparticles offer unlimited possibilities of surface modifications, allowing for the attachment of biomolecules, such as antibodies or proteins, and drug molecules, among others. In this work, we discuss the potential applicability of QDs in breast cancer diagnostics and treatment in light of the current knowledge. We begin with introducing the molecular and histopathological features of BCs, standard therapeutic regimens, and current diagnostic methods. Further, the features of QDs, along with their uptake, biodistribution patterns, and cytotoxicity, are described. Based on the reports published in recent years, we present the progress in research on possible QD use in improving BC diagnostics and treatment efficacy as chemotherapeutic delivery vehicles and photosensitizing agents, along with the stages of their development. We also address limitations and open questions regarding this topic.

Synthesis, Structural Characterization, and Computational Studies of Novel Co(II) and Zn(II) Fluoroquinoline Complexes for Antibacterial and Antioxidant Activities.

Research into heterocyclic ligands has increased in popularity due to their versatile applications in the biomedical field. Quinoline derivatives with their transition metal complexes are popular scaffolding molecules in the ongoing pursuit of newer and more effective bioactive molecules. Subsequently, this work reports on the synthesis and possible biological application of new Zn(II) and Co(II) complexes with a bidentate quinoline derivative ligand (H2 L), [(H2 L):(E)-2-(((6-fluoro-2-((2-hydroxyethyl)amino)quinolin-3-yl)methylene)amino)ethanol]. The ligand and its metal complexes were structurally characterized by spectroscopic methods (1H NMR, 13C NMR, Fourier transform infrared (FTIR), UV-vis, fluorescence, and mass spectroscopy), as well as by thermogravimetric and elemental analysis methods. The spectroscopic findings were further supported by density functional theory (DFT) and time-dependent (TD)-DFT calculations. The biological application was examined by investigating the inhibitory action of the complexes against bacterial strains using diffusion and agar dilution methods, and their profiles against two Gram-positive and Gram-negative bacterial strains were supported by molecular docking analysis. To rationalize the in vitro activity and establish the possible mechanism of action, the interactions and binding affinity of the ligand and complexes were investigated against three different bacterial enzymes (Escherichia coli DNA gyrase (PDB ID 6f86), E. coli dihydrofolate reductase B (PDB ID: 7r6g), and Staphylococcus aureus tyrosyl-tRNA synthetase (PDB ID: 1JIJ)) using AutoDock with the standard protocol. The MIC value of 0.20 μg/mL for zinc complex against E. coli and associated binding affinities -7.2 and -9.9 kcal/mol with DNA gyrase (PDB ID 6f86) and dihydrofolate reductase B (PDB ID: 7r6g), as well as the MIC value of 2.4 μg/mL for cobalt(II) complex against Staphylococcus aureus and the associated binding affinity of -10.5 kcal/mol with tyrosyl-tRNA synthetase (PDB ID: 1JIJ), revealed that the complexes' inhibitory actions were strong and comparable with those of the standard drug in the experiments. In addition, the ability of the new quinoline-based complexes to scavenge 1,1-diphenyl-picrylhydrazyl radicals was investigated; the findings suggested that the complexes exhibit potent antioxidant activities, which may be of therapeutic significance.