An investigation on linker modifications of cyanoguanidine-based P2X7 receptor antagonists.

Despite their acknowledged significance in the inflammatory signalling cascade across a range of disease states, P2X7R antagonists have not yet proven to be effective in clinical trials. In this study, we present findings on P2X7 receptor antagonists that are based on a core adamantyl-cyanoguanidine-quinoline lead. To investigate the specific features of the cyanoguanidine moiety that influence compound potency we carried out a structure-activity relationship (SAR) study. Compound potency was assessed using an in vitro dye-uptake assay measuring P2X7R pore formation. While none of the compounds displayed superior potency to the lead, we established key structural requirements for potent P2X7R antagonism. An additional SAR using different aryl groups was performed based on the promising activity displayed by the squaramide derivative.

Unsupervised Dual Transformer Learning for 3-D Textured Surface Segmentation.

Analysis of the 3-D texture is indispensable for various tasks, such as retrieval, segmentation, classification, and inspection of sculptures, knit fabrics, and biological tissues. A 3-D texture represents a locally repeated surface variation (SV) that is independent of the overall shape of the surface and can be determined using the local neighborhood and its characteristics. Existing methods mostly employ computer vision techniques that analyze a 3-D mesh globally, derive features, and then utilize them for classification or retrieval tasks. While several traditional and learning-based methods have been proposed in the literature, only a few have addressed 3-D texture analysis, and none have considered unsupervised schemes so far. This article proposes an original framework for the unsupervised segmentation of 3-D texture on the mesh manifold. The problem is approached as a binary surface segmentation task, where the mesh surface is partitioned into textured and nontextured regions without prior annotation. The proposed method comprises a mutual transformer-based system consisting of a label generator (LG) and a label cleaner (LC). Both models take geometric image representations of the surface mesh facets and label them as texture or nontexture using an iterative mutual learning scheme. Extensive experiments on three publicly available datasets with diverse texture patterns demonstrate that the proposed framework outperforms standard and state-of-the-art unsupervised techniques and performs reasonably well compared to supervised methods.

Water-Soluble Arylazoisoxazole Photoswitches.

Azoheteroarenes are emerging as powerful alternatives to azobenzene molecular photoswitches. In this study, water-soluble arylazoisoxazole photoswitches are introduced. UV/vis and NMR spectroscopy revealed moderate to very good photostationary states and reversible photoisomerization between the E- and Z-isomers over multiple cycles with minimal photobleaching. Several arylazoisoxazoles form host-guest complexes with ß- and γ-cyclodextrin with significant differences in binding constants for each photoisomer as shown by isothermal titration calorimetry and NMR experiments, indicating their potential for photoresponsive host-guest chemistry in water. One carboxylic acid functionalized arylazoisoxazole can act as a hydrogelator, allowing gel properties to be manipulated reversibly with light. The hydrogel was characterized by rheological experiments, atom force microscopy and transmission electron microscopy. These results demonstrate that arylazoisoxazoles can find applications as molecular photoswitches in aqueous media.

Human capital-based four-factor asset pricing model: An empirical study from Pakistan.

This study aims to extend the Fama-French three-factor model by including human capital as a fourth factor. For this purpose, we have collected data from 164 non-financial firms from July 2010 to June 2020. To evaluate the validity and applicability of our augmented human capital-based four-factor model, we apply the two-pass time series regression proposed by Fama-Macbeth (1973). We find that small firms outperform big firms, value stocks firms outperform growth stocks firms, and low-labor-income firms outperform high-labor-income firms. The augmented human capital-based four-factor model is valid and applicable in the context of the Pakistan equity market. The empirical results motivate academia and all investors to consider human capital in investment decisions.

Multimodal-Boost: Multimodal Medical Image Super-Resolution Using Multi-Attention Network With Wavelet Transform.

Multimodal medical images are widely used by clinicians and physicians to analyze and retrieve complementary information from high-resolution images in a non-invasive manner. Loss of corresponding image resolution adversely affects the overall performance of medical image interpretation. Deep learning-based single image super resolution (SISR) algorithms have revolutionized the overall diagnosis framework by continually improving the architectural components and training strategies associated with convolutional neural networks (CNN) on low-resolution images. However, existing work lacks in two ways: i) the SR output produced exhibits poor texture details, and often produce blurred edges, ii) most of the models have been developed for a single modality, hence, require modification to adapt to a new one. This work addresses (i) by proposing generative adversarial network (GAN) with deep multi-attention modules to learn high-frequency information from low-frequency data. Existing approaches based on the GAN have yielded good SR results; however, the texture details of their SR output have been experimentally confirmed to be deficient for medical images particularly. The integration of wavelet transform (WT) and GANs in our proposed SR model addresses the aforementioned limitation concerning textons. While the WT divides the LR image into multiple frequency bands, the transferred GAN uses multi-attention and upsample blocks to predict high-frequency components. Additionally, we present a learning method for training domain-specific classifiers as perceptual loss functions. Using a combination of multi-attention GAN loss and a perceptual loss function results in an efficient and reliable performance. Applying the same model for medical images from diverse modalities is challenging, our work addresses (ii) by training and performing on several modalities via transfer learning. Using two medical datasets, we validate our proposed SR network against existing state-of-the-art approaches and achieve promising results in terms of structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR).

What matters when examining the performance of salespersons? Analyzing the boundary conditions of personal dispositional factor.

Purpose: This study intended to examine the effect of developmental and evaluative purposes of performance appraisal (PA) on job meaningfulness (JM). Furthermore, the study also aimed to assess the moderating effect of personal dispositional factors, that is, internal and external loci of control between developmental and evaluative PA and JM. Design/Methodology/Approach: A total of 295 questionnaires were received from salespersons working in national and multinational pharmaceutical companies in Khyber Pakhtunkhwa, Pakistan. Data were gathered using a time lag study design using a convenience sampling technique. Data collected via questionnaires were analyzed using PLS-SEM to assess measurement and structural models for testing hypotheses. Findings: Results revealed that developmental PA significantly influenced JM, while evaluative PA failed to influence JM. Furthermore, there was a moderating effect of the external locus of control (ELOC) on the relationship between developmental PA and JM, while the rest of moderating hypotheses failed to influence the relationship of developmental and evaluative PA with JM. Practical implications: The results can be used as a building block in order to bring positive work outcomes in the form of meaningful work. Organizations should use their PA as a development tool, instead of instrumental or evaluative PA, for making the work more meaningful to the employees. Originality/Value: The extant literature is limited in terms of assessing the dimensions of PA (developmental and evaluative) in predicting workplace outcomes. Also, examinations of multidimensions of the locus of control are limited in the existing literature between HR practices and work outcomes. The current study has filled these gaps in the contemporary literature.

Foodborne Disease Risk Prediction Using Multigraph Structural Long Short-term Memory Networks: Algorithm Design and Validation Study.

BACKGROUND: Foodborne disease is a common threat to human health worldwide, leading to millions of deaths every year. Thus, the accurate prediction foodborne disease risk is very urgent and of great importance for public health management. OBJECTIVE: We aimed to design a spatial-temporal risk prediction model suitable for predicting foodborne disease risks in various regions, to provide guidance for the prevention and control of foodborne diseases. METHODS: We designed a novel end-to-end framework to predict foodborne disease risk by using a multigraph structural long short-term memory neural network, which can utilize an encoder-decoder to achieve multistep prediction. In particular, to capture multiple spatial correlations, we divided regions by administrative area and constructed adjacent graphs with metrics that included region proximity, historical data similarity, regional function similarity, and exposure food similarity. We also integrated an attention mechanism in both spatial and temporal dimensions, as well as external factors, to refine prediction accuracy. We validated our model with a long-term real-world foodborne disease data set, comprising data from 2015 to 2019 from multiple provinces in China. RESULTS: Our model can achieve F1 scores of 0.822, 0.679, 0.709, and 0.720 for single-month forecasts for the provinces of Beijing, Zhejiang, Shanxi and Hebei, respectively, and the highest F1 score was 20% higher than the best results of the other models. The experimental results clearly demonstrated that our approach can outperform other state-of-the-art models, with a margin. CONCLUSIONS: The spatial-temporal risk prediction model can take into account the spatial-temporal characteristics of foodborne disease data and accurately determine future disease spatial-temporal risks, thereby providing support for the prevention and risk assessment of foodborne disease.

New aryl Schiff bases of thiadiazole derivative of ibuprofen as DNA binders and potential anticancer drug candidates.

The work presented in this paper describes the synthesis of two new aryl Schiff bases [(E)-N-(4-(benzyloxy)-3-methoxybenzylidene)-5-(1-(4-isobutylphenyl)ethyl)-1,3,4-thiadiazol-2-amine] (ASB-1) and [(E)-N-(4-(benzyloxy)benzylidene)-5-(1-(4-isobutylphenyl)ethyl)-1,3,4-thiadiazol-2-amine] (ASB-2). These compounds were characterized by different analytical techniques and then studied for DNA binding. Binding studies were carried out at neutral pH (7.0) and at 37 °C by theoretical and experimental methods including DFT, molecular docking, spectroscopy (UV-visible, fluorescence), cyclic voltammetry (CV) and viscometry. Further investigations of these compounds were done on hepatocellular carcinoma; Huh-7 cancer cell line. Binding constant, free energy change and binding site size, i.e. Kb, ΔG and n were evaluated which indicated that both ASB-1 and ASB-2 bind significantly and spontaneously with the DNA. However, data revealed relatively greater binding of ASB-1 with DNA. Spectral and voltammetric results were found supportive of each other. Binding site sizes and viscosity measurements verified the mixed binding mode of interactions as observed in molecular docking analysis, i.e. intercalation with groove binding. DNA binding studies were very well correlated with the in-vitro studies performed on Huh-7 cell line as well as normal HEK-293 cell lines. The compound ASB-1 not only showed greater binding affinity toward DNA but also showed greater anticancer potency with least IC50 value as compared to ASB-2.

Comparison of Machine Learning Techniques Based Brain Source Localization Using EEG Signals.

BACKGROUND: The brain is the most complex organ of the human body with millions of connections and activations. The electromagnetic signals are generated inside the brain due to a mental or physical task performed. These signals excite a bunch of neurons within a particular lobe depending upon the nature of the task performed. To localize this activity, certain machine learning (ML) techniques in conjunction with a neuroimaging technique (M/EEG, fMRI, PET) are developed. Different ML techniques are provided in the literature for brain source localization. Among them, the most common are: minimum norm estimation (MNE), low resolution brain electromagnetic tomography (LORETA) and Bayesian framework based multiple sparse priors (MSP). AIMS: In this research work, EEG is used as a neuroimaging technique. METHODS: EEG data is synthetically generated at SNR=5dB. Afterwards, ML techniques are applied to estimate the active sources. Each dataset is run for multiple trials (>40). The performance is analyzed using free energy and localization error as performance indicators. Furthermore, MSP is applied with a variant number of patches to observe the impact of patches on source localization. RESULTS: It is observed that with an increased number of patches, the sources are localized with more precision and accuracy as expressed in terms of free energy and localization error, respectively. CONCLUSION: The patches optimization within the Bayesian Framework produces improved results in terms of free energy and localization error.

Ultra-Low Molecular Weight Photoswitchable Hydrogelators.

Two photoswitchable arylazopyrozoles form hydrogels at a concentration of 1.2 % (w/v). With a molecular weight of 258.28 g mol-1 , these are the lowest known molecular weight hydrogelators that respond reversibly to light. Photoswitching of the E- to the Z-form by exposure to 365 nm light results in a macroscopic gel→sol transition; nearly an order of magnitude reduction in the measured elastic and loss moduli. In the case of the meta-arylazopyrozole, cryogenic transmission electron microscopy suggests that the 29±7 nm wide sheets in the E-gel state narrow to 13±2 nm upon photoswitching to the predominantly Z-solution state. Photoswitching for meta-arylazopyrozole is reversible through cycles of 365 nm and 520 nm excitation with little fatigue. The release of a rhodamine B dye encapsulated in gels formed by the arylazopyrozoles is accelerated more than 20-fold upon photoswitching with 365 nm light, demonstrating these materials are suitable for light-controlled cargo release.

Highly productive and scalable approach to synthesize ticlopidine: A potent thienopyridine anti-platelet aggregation drug.

Ticlopidine (trade name Ticlid), an acidic thienopyridine derivative, is an effective, well-known and long-acting inhibitor of platelet aggregation. Because of its potent inhibitory activity for treating a variety of diseases, the development of efficient approaches for accessing ticlopidine represents an important endeavour. Therefore, in this research work, we developed a promising novel five-step synthetic approach for synthesizing ticlopidine. This method provides ticlopidine in 60% overall yield from readily available starting material viz. thiophene. In this methodology, all steps afforded excellent yields and are operationally simple and environmentally acceptable. This approach also offers various attractive advantages, for example, it's applicable for large-scale synthesis, has simple work-up procedures and short reaction times, and uses inexpensive and readily available reagents. Furthermore, 4,5,6,7-tetrahydrothieno[3,2-c]pyridine is a key precursor for the synthesis of numerous bioactive compounds such as prasugrel and clopidogrel. This protocol provides 4,5,6,7-tetrahydrothieno[3,2-c]pyridine in 62% overall yield via a 4-step synthetic approach.

Anion Binding Affinity: Acidity versus Conformational Effects.

High-level quantum chemical calculations were used to elucidate the gas- and solution-phase conformational equilibria for a series of symmetrically substituted (thio)ureas, (thio)squaramides, and croconamides. Gas-phase calculations predict that the thermodynamic conformer of many of these anion receptors is not the dual-hydrogen-bond-facilitating anti-anti conformer as is commonly assumed. For N,N'-diaryl thiosquaramides and croconamides, the syn-syn conformer is typically the predominant conformer. Solution-phase calculations show that the anti-anti conformer is increasingly stabilized as the polarity of the solvent increases. However, the syn-syn conformer remains the lowest energy conformation for croconamides. These predictions are used to explain the acidity versus chloride binding affinity correlations recently reported for some of these compounds. The chloride binding constants for thioureas and croconamides are significantly lower than expected on the basis of their pKa values, and this may be due in part to the need for these receptors to reorganize into the anti-anti conformer. Experimental NMR nuclear Overhauser effect (NOE) measurements of an asymmetrically substituted squaramide and its thio analogue are consistent with the syn-syn conformation being predominant at 298 K. The conformational equilibria should therefore be an important consideration for the design and development of future anion receptors and organocatalysts.

Recent developments and comparison of transformation strategies for organic halides to aldehydes and ketones.

Aldehydes and ketones are parts of millions of compounds and are important classes of chemicals which serve as important precursors for the synthesis of library of compounds. For the synthesis of aldehydes and ketones, one impressive approach to date, because of its excellent selectivity, high yield and stability toward over-reduction and over-oxidation, is the oxidation of organic halides (viz. aliphatic and benzyl halides). The current review covers the conventional and eco-friendly transformational approaches, from 2000 to date, toward synthesis of aldehydes and ketones from organic halides, including mechanistic studies, comparison of different transformational strategies and discussion on scope and cons and pros of each transformational approach. The review would be beneficial to get knowledge about recent synthesis techniques, select finest synthetic approach, develop further new transformational methodologies and improve current transformational approaches.

Synthesis, antibacterial activity and molecular docking study of vanillin derived 1,4-disubstituted 1,2,3-triazoles as inhibitors of bacterial DNA synthesis.

Antimicrobial resistance (AMR) compelled scientists in general while pharmacists, chemists and biologists in specific to believe that we could always remain ahead of the pathogens. The pipeline of new drugs is running gasping and the inducements to develop new antimicrobials to address the global problems of drug resistance are weak. In this pursuit, effective endeavours to prepare new anti-bacterial entities is highly wished. The present study demonstrates successful synthesis of a library of 1,4-disbustituted 1,2,3-triazoles (3a-3k) using Click-chemistry concept and anti-their bacterial potential. In this 1,3-dipolar cycloaddition, the 3-methoxy-4-(prop-2-yn-1-yloxy)benzaldehyde (1) was used as alkyne partner which was synthesized from vanillin and propargyl bromide and further reacted with differently substituted arylpropoxy azides (2a-k) to furnish series of mono and bis1,4-disubstituted-1,2,3-triazoles. All the synthesized compounds were characterized spectroscopically and were evaluated for their initial antimicrobial activity. Preliminary results of antibacterial screening revealed that the synthesized compounds have the highest inhibitory effects compare to the control ciprofloxacin. The compounds 3b and 3g were found to be the most active (MIC: 5 µg/mL, MIC: 10 µg/mL respectively) against various strains of gram-positive and gram-negative bacteria. The molecular docking study against 4GQQ protein with synthesized ligands was performed to see the necessary interactions responsible for anti-bacterial activity. The docking analysis of the most potent compound 3g supported the antibacterial activity exhibiting high inhibition constant and binding energy.

Design, synthesis and biological evaluation of trinary benzocoumarin-thiazoles-azomethines derivatives as effective and selective inhibitors of alkaline phosphatase.

Design, synthesis and characterization of new trinary Benzocoumarin-Thiazoles-Azomethine derivatives having three bioactive scaffolds in a single structural unit were carried out. The newly synthesized molecules were investigated for the inhibitory activity on human tissue nonspecific alkaline phosphatase (h-TNAP) and human intestinal alkaline phosphatase (h-IAP) isozymes. All the tested compounds exhibited the potent inhibition profile on both isozymes of alkaline phosphatase i.e., h-TNAP and h-IAP. Molecular docking studies were performed to explore the putative binding mode of interactions of selective inhibitors. Moreover, the synthesized derivatives were evaluated against cervical cancer cell line, HeLa and a few compounds exhibited significant inhibition in the range of 21.0-69.7%. The derivatives can be potential and selective alkaline phosphatase inhibitors for future studies.

Synthesis, molecular docking and kinetic studies of novel quinolinyl based acyl thioureas as mushroom tyrosinase inhibitors and free radical scavengers.

The enzyme tyrosinase plays a vital role in melanin biosynthesis and enzymatic browning of vegetables and fruits. A series of novel quinolinyl thiourea analogues (11a-j) were synthesized by reaction of 3-aminoquinoline and corresponding isothiocyanates, in moderate to excellent yields with different substitutions and their inhibitory effect on mushroom tyrosinase and free radical scavenging activity were evaluated. The compound N-(quinolin-3-ylcarbamothioyl)hexanamide (11c) exhibited the maximum tyrosinase inhibitory effect (IC50 = 0.0070 ±â€¯0.0098 µM) compared to other derivatives and the reference Kojic acid (IC50 = 16.8320 ±â€¯0.0621 µM). The docking studies were carried out and the compound (11c) showed most negative estimated free energy of -7.2 kcal/mol in mushroom tyrosinase active site. The kinetic analysis revealed that the compound (11c) inhibits the enzyme tyrosinase non-competitively to form the complex of enzyme and inhibitor. The results revealed that 11c could be identified as putative lead compound for the design of efficient tyrosinase inhibitors.

Synthesis, Crystal Structure, Hirshfeld Surface Analysis, DFT, and DNA-Binding Studies of (E)-2-(3-Hydroxy-4-Methoxybenzylidene)Hydrazinecarbothioamide.

(E)-2-(3-Hydroxy-4-methoxybenzylidene)hydrazinecarbothioamide 3 was synthesized by reacting thiosemicarbazide with 2-hydorxy-3-methoxybenzaldehyde in dry ethanol. The structure was elucidated by spectroscopic (FT-IR, 1H NMR, and 13C NMR) and single crystal X-ray diffraction techniques. A detailed analysis of the intermolecular interactions has been performed based on the Hirshfeld surfaces and their associated two-dimensional fingerprint plots. DFT, spectroscopic, and electrochemical DNA-binding analysis confirmed that the compound is reactive to bind with DNA. Viscometric studies suggested that compound 3 has a mixed mode of interaction and intercalated into the DNA base pairs predominantly along with the possibility of electrostatic interactions. Graphical Abstract.

Novel C-2 Symmetric Molecules as α-Glucosidase and α-Amylase Inhibitors: Design, Synthesis, Kinetic Evaluation, Molecular Docking and Pharmacokinetics.

A series of symmetrical salicylaldehyde-bishydrazine azo molecules, 5a-5h, have been synthesized, characterized by 1H-NMR and 13C-NMR, and evaluated for their in vitro α-glucosidase and α-amylase inhibitory activities. All the synthesized compounds efficiently inhibited both enzymes. Compound 5g was the most potent derivative in the series, and powerfully inhibited both α-glucosidase and α-amylase. The IC50 of 5g against α-glucosidase was 0.35917 ± 0.0189 µM (standard acarbose IC50 = 6.109 ± 0.329 µM), and the IC50 value of 5g against α-amylase was 0.4379 ± 0.0423 µM (standard acarbose IC50 = 33.178 ± 2.392 µM). The Lineweaver-Burk plot indicated that compound 5g is a competitive inhibitor of α-glucosidase. The binding interactions of the most active analogues were confirmed through molecular docking studies. Docking studies showed that 5g interacts with the residues Trp690, Asp548, Arg425, and Glu426, which form hydrogen bonds to 5g with distances of 2.05, 2.20, 2.10 and 2.18 Å, respectively. All compounds showed high mutagenic and tumorigenic behaviors, and only 5e showed irritant properties. In addition, all the derivatives showed good antioxidant activities. The pharmacokinetic evaluation also revealed promising results.

Drug-1,3,4-Thiadiazole Conjugates as Novel Mixed-Type Inhibitors of Acetylcholinesterase: Synthesis, Molecular Docking, Pharmacokinetics, and ADMET Evaluation.

A small library of new drug-1,3,4-thiazidazole hybrid compounds (3a⁻3i) was synthesized, characterized, and assessed for their acetyl cholinesterase enzyme (AChE) inhibitory and free radical scavenging activities. The newly synthesized derivatives showed promising activities against AChE, especially compound 3b (IC50 18.1 ± 0.9 nM), which was the most promising molecule in the series, and was substantially more active than the reference drug (neostigmine methyl sulfate; IC50 2186.5 ± 98.0 nM). Kinetic studies were performed to elucidate the mode of inhibition of the enzyme, and the compounds showed mixed-type mechanisms for inhibiting AChE. The Ki of 3b (0.0031 µM) indicates that it can be very effective, even at low concentrations. Compounds 3a⁻3i all complied with Lipinski's Rule of Five, and showed high drug-likeness scores. The pharmacokinetic parameters revealed notable lead-like properties with insignificant liver and skin-penetrating effects. The structure⁻activity relationship (SAR) analysis indicated π⁻π interactions with key amino acid residues related to Tyr124, Trp286, and Tyr341.