Thymol in Trachyspermum ammi seed extract exhibits neuroprotection, learning, and memory enhancement in scopolamine-induced Alzheimer's disease mouse model.

Several reports have stated the neuroprotective and learning/memory effects of Tachyspermum ammi seed extract (TASE) and its principal component thymol; however, little is known about its underlying molecular mechanisms and neurogenesis potential. This study aimed to provide insights into TASE and a thymol-mediated multifactorial therapeutic approach in a scopolamine-induced Alzheimer's disease (AD) mouse model. TASE and thymol supplementation significantly reduced oxidative stress markers such as brain glutathione, hydrogen peroxide, and malondialdehyde in mouse whole brain homogenates. Tumor necrosis factor-alpha was significantly downregulated, whereas the elevation of brain-derived neurotrophic factor and phospho-glycogen synthase kinase-3 beta (serine 9) enhanced learning and memory in the TASE- and thymol-treated groups. A significant reduction in the accumulation of Aß 1-42 peptides was observed in the brains of TASE- and thymol-treated mice. Furthermore, TASE and thymol significantly promoted adult neurogenesis, with increased doublecortin positive neurons in the subgranular and polymorphic zones of the dentate gyrus in treated-mice. Collectively, TASE and thymol could  potentially act as natural therapeutic agents for the treatment of  neurodegenerative disorders, such as  AD.

N-Acetylglucosamine Kinase-Small Nuclear Ribonucleoprotein Polypeptide N Interaction Promotes Axodendritic Branching in Neurons via Dynein-Mediated Microtubule Transport.

N-acetylglucosamine kinase (NAGK) has been identified as an anchor protein that facilitates neurodevelopment with its non-canonical structural role. Similarly, small nuclear ribonucleoprotein polypeptide N (SNRPN) regulates neurodevelopment and cognitive ability. In our previous study, we revealed the interaction between NAGK and SNRPN in the neuron. However, the precise role in neurodevelopment is elusive. In this study, we investigate the role of NAGK and SNRPN in the axodendritic development of neurons. NAGK and SNRPN interaction is significantly increased in neurons at the crucial stages of neurodevelopment. Furthermore, overexpression of the NAGK and SNRPN proteins increases axodendritic branching and neuronal complexity, whereas the knockdown inhibits neurodevelopment. We also observe the interaction of NAGK and SNRPN with the dynein light-chain roadblock type 1 (DYNLRB1) protein variably during neurodevelopment, revealing the microtubule-associated delivery of the complex. Interestingly, NAGK and SNRPN proteins rescued impaired axodendritic development in an SNRPN depletion model of Prader-Willi syndrome (PWS) patient-derived induced pluripotent stem cell neurons. Taken together, these findings are crucial in developing therapeutic approaches for neurodegenerative diseases.

Neuronal Differentiation and Outgrowth Effect of Thymol in Trachyspermum ammi Seed Extract via BDNF/TrkB Signaling Pathway in Prenatal Maternal Supplementation and Primary Hippocampal Culture.

Reviving the neuronal functions in neurodegenerative disorders requires the promotion of neurite outgrowth. Thymol, which is a principal component of Trachyspermum ammi seed extract (TASE), is reported to have neuroprotective effects. However, the effects of thymol and TASE on neuronal differentiation and outgrowth are yet to be studied. This study is the first report investigating the neuronal growth and maturation effects of TASE and thymol. Pregnant mice were orally supplemented with TASE (250 and 500 mg/kg), thymol (50 and 100 mg/kg), vehicle, and positive controls. The supplementation significantly upregulated the expression of brain-derived neurotrophic factor (BDNF) and early neuritogenesis markers in the pups' brains at post-natal day 1 (P1). Similarly, the BDNF level was significantly upregulated in the P12 pups' brains. Furthermore, TASE (75 and 100 µg/mL) and thymol (10 and 20 µM) enhanced the neuronal polarity, early neurite arborization, and maturation of hippocampal neurons in a dose-dependent manner in primary hippocampal cultures. The stimulatory activities of TASE and thymol on neurite extension involved TrkB signaling, as evidenced by attenuation via ANA-12 (5 µM), which is a specific TrkB inhibitor. Moreover, TASE and thymol rescued the nocodazole-induced blunted neurite extension in primary hippocampal cultures, suggesting their role as a potent microtubule stabilizing agent. These findings demonstrate the potent capacities of TASE and thymol in promoting neuronal development and reconstruction of neuronal circuitry, which are often compromised in neurodegenerative diseases and acute brain injuries.

Differential Effects of the Processed and Unprocessed Garlic (Allium sativum L.) Ethanol Extracts on Neuritogenesis and Synaptogenesis in Rat Primary Hippocampal Neurons.

Garlic (Allium sativum L.) is an aromatic herb known for its culinary and medicinal uses for centuries. Both unprocessed (white) and processed (black) garlic are known to protect against the pathobiology of neurological disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD), which has been attributed to their anti-inflammatory and antioxidant properties. The information on the effects of processed and unprocessed garlic on neuronal process outgrowth, maturation, and synaptic development is limited. This study aimed at investigating and comparing the effects of the ethanol extracts of unprocessed (white garlic extract, WGE) and processed (black garlic extract, BGE) garlic on the maturation of primary hippocampal neurons. Neurite outgrowth was stimulated in a dose-dependent manner by both WGE and BGE and the most effective doses were 15 µg/mL and 60 µg/mL, respectively, without showing cytotoxicity. At this optimal concentration, both extracts promoted axonal and dendritic growth and maturation. Furthermore, both extracts substantially increased the formation of functional synapses. However, the effect of WGE was more robust at every developmental stage of neurons. In addition, the gas chromatography and mass spectrometry (GC-MS) analysis revealed a chemical profile of various bioactives in both BGE and WGE. Linalool, a compound that was found in both extracts, has shown neurite outgrowth-promoting activity in neuronal cultures, suggesting that the neurotrophic activity of garlic extracts is attributed, at least in part, to this compound. By using network pharmacology, linalool's role in neuronal development can also be observed through its modulatory effect on the signaling molecules of neurotrophic signaling pathways such as glycogen synthase kinase 3 (GSK3ß), extracellular signal-regulated protein kinase (Erk1/2), which was further verified by immunocytochemistry. Overall, these findings provide information on the molecular mechanism of processed and unprocessed garlic for neuronal growth, survival, and memory function which may have the potential for the prevention of several neurological disorders.

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1.

Disruptive neuronal migration during early brain development causes severe brain malformation. Characterized by mislocalization of cortical neurons, this condition is a result of the loss of function of migration regulating genes. One known neuronal migration disorder is lissencephaly (LIS), which is caused by deletions or mutations of the LIS1 (PAFAH1B1) gene that has been implicated in regulating the microtubule motor protein cytoplasmic dynein. Although this class of diseases has recently received considerable attention, the roles of non-synonymous polymorphisms (nsSNPs) in LIS1 on lissencephaly progression remain elusive. Therefore, the present study employed combined bioinformatics and molecular modeling approach to identify potential damaging nsSNPs in the LIS1 gene and provide atomic insight into their roles in LIS1 loss of function. Using this approach, we identified three high-risk nsSNPs, including rs121434486 (F31S), rs587784254 (W55R), and rs757993270 (W55L) in the LIS1 gene, which are located on the N-terminal domain of LIS1. Molecular dynamics simulation highlighted that all variants decreased helical conformation, increased the intermonomeric distance, and thus disrupted intermonomeric contacts in the LIS1 dimer. Furthermore, the presence of variants also caused a loss of positive electrostatic potential and reduced dimer binding potential. Since self-dimerization is an essential aspect of LIS1 to recruit interacting partners, thus these variants are associated with the loss of LIS1 functions. As a corollary, these findings may further provide critical insights on the roles of LIS1 variants in brain malformation.

Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning.

Diffuse gliomas are the most common primary brain tumors and they vary considerably in their morphology, location, genetic alterations, and response to therapy. In 2016, the World Health Organization (WHO) provided new guidelines for making an integrated diagnosis that incorporates both morphologic and molecular features to diffuse gliomas. In this study, we demonstrate how deep learning approaches can be used for an automatic classification of glioma subtypes and grading using whole-slide images that were obtained from routine clinical practice. A deep transfer learning method using the ResNet50V2 model was trained to classify subtypes and grades of diffuse gliomas according to the WHO's new 2016 classification. The balanced accuracy of the diffuse glioma subtype classification model with majority voting was 0.8727. These results highlight an emerging role of deep learning in the future practice of pathologic diagnosis.

Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function.

An enzyme of the mammalian amino-sugar metabolism pathway, N-acetylglucosamine kinase (NAGK), that synthesizes N-acetylglucosamine (GlcNAc)-6-phosphate, is reported to promote dynein functions during mitosis, axonal and dendritic growth, cell migration, and selective autophagy, which all are unrelated to its enzyme activity. As non-enzymatic structural functions can be altered by genetic variation, we made an effort in this study aimed at deciphering the pathological effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in NAGK gene. An integrated computational approach, including molecular dynamics (MD) simulation and protein-protein docking simulation, was used to identify the damaging nsSNPs and their detailed structural and functional consequences. The analysis revealed the four most damaging variants (G11R, G32R, G120E, and A156D), which are highly conserved and functional, positioned in both small (G11R and G32R) and large (G120E and A156D) domains of NAGK. G11R is located in the ATP binding region, while variants present in the large domain (G120E and A156D) were found to induce substantial alterations in the structural organizations of both domains, including the ATP and substrate binding sites. Furthermore, all variants were found to reduce binding energy between NAGK and dynein subunit DYNLRB1, as revealed by protein-protein docking and MM-GBSA binding energy calculation supporting their deleteriousness on non-canonical function. We hope these findings will direct future studies to gain more insight into the role of these variants in the loss of NAGK function and their role in neurodevelopmental disorders.

N-Acetyl-D-Glucosamine Kinase Interacts with NudC and Lis1 in Dynein Motor Complex and Promotes Cell Migration.

Recently, we showed that N-acetylglucosamine kinase (NAGK), an enzyme of amino sugar metabolism, interacts with dynein light chain roadblock type 1 (DYNLRB1) and promotes the functions of dynein motor. Here, we report that NAGK interacts with nuclear distribution protein C (NudC) and lissencephaly 1 (Lis1) in the dynein complex. Yeast two-hybrid assays, pull-down assays, immunocytochemistry, and proximity ligation assays revealed NAGK-NudC-Lis1-dynein complexes around nuclei, at the leading poles of migrating HEK293T cells, and at the tips of migratory processes of cultured rat neuroblast cells. The exogenous expression of red fluorescent protein (RFP)-tagged NAGK accelerated HEK293T cell migration during in vitro wound-healing assays and of neurons during in vitro neurosphere migration and in utero electroporation assays, whereas NAGK knockdown by short hairpin RNA (shRNA) delayed migration. Finally, a small NAGK peptide derived from the NudC interacting domain in in silico molecular docking analysis retarded the migrations of HEK293T and SH-SY5Y cells. These data indicate a functional interaction between NAGK and dynein-NudC-Lis1 complex at the nuclear envelope is required for the regulation of cell migration.

Dependence of the viewing angle control property of a guest-host liquid crystal cell on the extinction coefficient of the mixture.

The theoretical prediction of a display viewing angle control using a guest-host (GH) liquid crystal (LC) cell has been reported by Chen et al. [Jpn. J. Appl. Phys.48, 062401 (2009)JJAPA50021-492210.1143/JJAP.48.062401]. We experimentally confirmed the viewing angle control property of the GH cell and also investigated its dependence on the extinction coefficient of the GH mixture. The GH cell with a negative dielectric anisotropy and a vertical orientation was attached on front of the display panel, resulting in narrow viewing (NV) property at the field-off state. The GH molecules were switched to a planar orientation, which is also orthogonal to the polarization direction of light at the field-on state, showing wide viewing (WV) property. We varied the concentration of a guest dichroic dye in a host LC and measured the extinction coefficients of the mixtures. We simulated the viewing control property using the measured extinction coefficients and found that the horizontal viewing angle can be controlled using the GH cell, but the vertical viewing angle cannot be controlled. Then, we experimentally confirmed the horizontal viewing angle control using the GH cell. The extinction between the NV and the WV states was increased with a greater extinction coefficient of the GH molecules, but the transmittance was decreased.

Modeling long-term human activeness using recurrent neural networks for biometric data.

BACKGROUND: With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three types of biometric data, the user's "activeness", and investigates the feasibility in modeling and predicting the long-term activeness of the user. METHODS: The dataset used in this study consisted of several months of biometric time-series data gathered by seven users independently. Four recurrent neural network (RNN) architectures-as well as a deep neural network and a simple regression model-were proposed to investigate the performance on predicting the activeness of the user under various length-related hyper-parameter settings. In addition, the learned model was tested to predict the time period when the user's activeness falls below a certain threshold. RESULTS: A preliminary experimental result shows that each type of activeness data exhibited a short-term autocorrelation; and among the three types of data, the consumed calories and the number of footsteps were positively correlated, while the heart rate data showed almost no correlation with neither of them. It is probably due to this characteristic of the dataset that although the RNN models produced the best results on modeling the user's activeness, the difference was marginal; and other baseline models, especially the linear regression model, performed quite admirably as well. Further experimental results show that it is feasible to predict a user's future activeness with precision, for example, a trained RNN model could predict-with the precision of 84%-when the user would be less active within the next hour given the latest 15 min of his activeness data. CONCLUSIONS: This paper defines and investigates the notion of a user's "activeness", and shows that forecasting the long-term activeness of the user is indeed possible. Such information can be utilized by a health-related application to proactively recommend suitable events or services to the user.

Investigating the Impact of Possession-Way of a Smartphone on Action Recognition.

For the past few decades, action recognition has been attracting many researchers due to its wide use in a variety of applications. Especially with the increasing number of smartphone users, many studies have been conducted using sensors within a smartphone. However, a lot of these studies assume that the users carry the device in specific ways such as by hand, in a pocket, in a bag, etc. This paper investigates the impact of providing an action recognition system with the information of the possession-way of a smartphone, and vice versa. The experimental dataset consists of five possession-ways (hand, backpack, upper-pocket, lower-pocket, and shoulder-bag) and two actions (walking and running) gathered by seven users separately. Various machine learning models including recurrent neural network architectures are employed to explore the relationship between the action recognition and the possession-way recognition. The experimental results show that the assumption of possession-ways of smartphones do affect the performance of action recognition, and vice versa. The results also reveal that a good performance is achieved when both actions and possession-ways are recognized simultaneously.

Codon-based encoding for DNA sequence analysis.

With the exponential growth of biological sequence data (DNA or Protein Sequence), DNA sequence analysis has become an essential task for biologist to understand the features, functions, structures, and evolution of species. Encoding DNA sequences is an effective method to extract the features from DNA sequences. It is commonly used for visualizing DNA sequences and analyzing similarities/dissimilarities between different species or cells. Although there have been many encoding approaches proposed for DNA sequence analysis, we require more elegant approaches for higher accuracy. In this paper, we propose a noble encoding approach for measuring the degree of similarity/dissimilarity between different species. Our approach can preserve the physiochemical properties, positional information, and the codon usage bias of nucleotides. An extensive performance study shows that our approach provides higher accuracy than existing approaches in terms of the degree of similarity.

Link-based similarity measures using reachability vectors.

We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the "Random Walk with Restart" strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures.

Essential oil of Pterocarpus santalinus L. alleviates behavioral impairments in social defeat stress-exposed mice by regulating neurotransmission and neuroinflammation.

BACKGROUND: Pterocarpus santalinus L. essential oil (PSEO) is traditionally employed for treating fever and mental aberrations. We aim to explore the antidepressant potential of intranasal PSEO in social defeat stress (SDS)-expose mice and identify its mechanisms and components. METHODS: PSEO components were analyzed using gas chromatography-mass spectrometry (GC-MS). C57BL/6 mice underwent a 10-day SDS with intranasal PSEO (10, 20 mg/kg) for 21 days. Efficacy was evaluated through changes in behaviors and serum corticosterone (CORT), hippocampal neurotransmitter, and inflammatory cytokine levels. In vitro effects were examined using primary hippocampal neurons, PC12 and BV2 cells. RESULTS: GC-MS identified 22 volatile compounds in PSEO, and (+)-ledene (16.7%), cedrol (13.5%), and isoaromadendrene epoxide (7.0%) as major components. PSEO (20 mg/kg) significantly reversed SDS-induced social withdrawal, increased open-area explorations in the open field test (OFT) and elevated plus maze (EPM) test, and reduced immobility time in the tail suspension test (TST) and forced swimming test (FST). PSEO downregulated serum CORT and hippocampal interleukin (IL)-1ß, IL-6, and tumor necrosis factor (TNF)-α levels, while increasing hippocampal gamma-aminobutyric acid (GABA), norepinephrine (NE), and serotonin (5-HT) levels. PSEO (0.1, 1, 10 µg/mL) reduced neurotoxicity and neuroinflammation in PC12 and BV2 cells, respectively. PSEO (10 µg/mL) enhanced glutamic acid decarboxylase 6 (GAD6)- and GABA B receptor 1 (GABABR1)-positive puncta in the hippocampal neurons and FM1-43 fluorescence intensity. CONCLUSION: Intranasal PSEO exhibited antidepressant-like effects on SDS-exposed mice, potentially through modulating stress hormone, neurotransmission, and neuroinflammation. Further investigation into the pharmacokinetics, bioavailability, and mechanisms of (+)-ledene, cedrol, and isoaromadendrene epoxide is needed.

Multi-task learning approach for utilizing temporal relations in natural language understanding tasks.

Various studies have been conducted on multi-task learning techniques in natural language understanding (NLU), which build a model capable of processing multiple tasks and providing generalized performance. Most documents written in natural languages contain time-related information. It is essential to recognize such information accurately and utilize it to understand the context and overall content of a document while performing NLU tasks. In this study, we propose a multi-task learning technique that includes a temporal relation extraction task in the training process of NLU tasks such that the trained model can utilize temporal context information from the input sentences. To utilize the characteristics of multi-task learning, an additional task that extracts temporal relations from given sentences was designed, and the multi-task model was configured to learn in combination with the existing NLU tasks on Korean and English datasets. Performance differences were analyzed by combining NLU tasks to extract temporal relations. The accuracy of the single task for temporal relation extraction is 57.8 and 45.1 for Korean and English, respectively, and improves up to 64.2 and 48.7 when combined with other NLU tasks. The experimental results confirm that extracting temporal relations can improve its performance when combined with other NLU tasks in multi-task learning, compared to dealing with it individually. Also, because of the differences in linguistic characteristics between Korean and English, there are different task combinations that positively affect extracting the temporal relations.

Fabrication of p-type silicon nanowire arrays with a high aspect ratio using electrochemical and alkaline etching.

We report on the fabrication of silicon nanostructures with a high aspect ratio that were created using a combination of electrochemical etching and alkaline etching. With this technique, we were able to fabricate nano- and/or micro-wire structures that are perfectly periodic over large areas of 3.14 cm2. After porous silicon was created by electrochemical etching, the effect of post-alkaline etching was investigated to determine how changes in the etching time, solution concentration and temperature of the etchant influenced the silicon morphology. As a result, periodic silicon wire arrays with good vertical alignment were obtained, and these arrays had a width of less than 500 nm and/or a high aspect ratio of more than 20.

Dynamic insights into the effects of nonsynonymous polymorphisms (nsSNPs) on loss of TREM2 function.

Single nucleotide variations in Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) are associated with many neurodegenerative diseases, including Nasu-Hakola disease (NHD), frontotemporal dementia (FTD), and late-onset Alzheimer's disease because they disrupt ligand binding to the extracellular domain of TREM2. However, the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) in TREM2 on disease progression remain unknown. In this study, we identified several high-risk nsSNPs in the TREM2 gene using various deleterious SNP predicting algorithms and analyzed their destabilizing effects on the ligand recognizing region of the TREM2 immunoglobulin (Ig) domain by molecular dynamics (MD) simulation. Cumulative prediction by all tools employed suggested the three most deleterious nsSNPs involved in loss of TREM2 function are rs549402254 (W50S), rs749358844 (R52C), and rs1409131974 (D104G). MD simulation showed that these three variants cause substantial structural alterations and conformational remodeling of the apical loops of the TREM2 Ig domain, which is responsible for ligand recognition. Detailed analysis revealed that these variants substantially increased distances between apical loops and induced conformation remodeling by changing inter-loop nonbonded contacts. Moreover, all nsSNPs changed the electrostatic potentials near the putative ligand-interacting region (PLIR), which suggested they might reduce specificity or loss of binding affinity for TREM2 ligands. Overall, this study identifies three potential high-risk nsSNPs in the TREM2 gene. We propose further studies on the molecular mechanisms responsible for loss of TREM2 function and the associations between TREM2 nsSNPs and neurodegenerative diseases.

Emerging potential of cannabidiol in reversing proteinopathies.

The aberrant accumulation of disease-specific protein aggregates accompanying cognitive decline is a pathological hallmark of age-associated neurological disorders, also termed as proteinopathies, including Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis and multiple sclerosis. Along with oxidative stress and neuroinflammation, disruption in protein homeostasis (proteostasis), a network that constitutes protein surveillance system, plays a pivotal role in the pathobiology of these dementia disorders. Cannabidiol (CBD), a non-psychotropic phytocannabinoid of Cannabis sativa, is known for its pleiotropic neuropharmacological effects on the central nervous system, including the ability to abate oxidative stress, neuroinflammation, and protein misfolding. Over the past years, compelling evidence has documented disease-modifying role of CBD in various preclinical and clinical models of neurological disorders, suggesting the potential therapeutic implications of CBD in these disorders. Because of its putative role in the proteostasis network in particular, CBD could be a potent modulator for reversing not only age-associated neurodegeneration but also other protein misfolding disorders. However, the current understanding is insufficient to underpin this proposition. In this review, we discuss the potentiality of CBD as a pharmacological modulator of the proteostasis network, highlighting its neuroprotective and aggregates clearing roles in the neurodegenerative disorders. We anticipate that the current effort will advance our knowledge on the implication of CBD in proteostasis network, opening up a new therapeutic window for aging proteinopathies.

Black Cumin (Nigella sativa L.): A Comprehensive Review on Phytochemistry, Health Benefits, Molecular Pharmacology, and Safety.

Mounting evidence support the potential benefits of functional foods or nutraceuticals for human health and diseases. Black cumin (Nigella sativa L.), a highly valued nutraceutical herb with a wide array of health benefits, has attracted growing interest from health-conscious individuals, the scientific community, and pharmaceutical industries. The pleiotropic pharmacological effects of black cumin, and its main bioactive component thymoquinone (TQ), have been manifested by their ability to attenuate oxidative stress and inflammation, and to promote immunity, cell survival, and energy metabolism, which underlie diverse health benefits, including protection against metabolic, cardiovascular, digestive, hepatic, renal, respiratory, reproductive, and neurological disorders, cancer, and so on. Furthermore, black cumin acts as an antidote, mitigating various toxicities and drug-induced side effects. Despite significant advances in pharmacological benefits, this miracle herb and its active components are still far from their clinical application. This review begins with highlighting the research trends in black cumin and revisiting phytochemical profiles. Subsequently, pharmacological attributes and health benefits of black cumin and TQ are critically reviewed. We overview molecular pharmacology to gain insight into the underlying mechanism of health benefits. Issues related to pharmacokinetic herb-drug interactions, drug delivery, and safety are also addressed. Identifying knowledge gaps, our current effort will direct future research to advance potential applications of black cumin and TQ in health and diseases.

A study on the behavior of water droplet confined between an atomic force microscope tip and rough surfaces.

The atomic force microscope (AFM) is used for imaging, measuring, and manipulating matter at the nanoscale. It is well-known that water condenses between an AFM tip and a solid surface, thereby generating a pull-off force acting on the tip. We investigated the behavior of a water meniscus between the tip and a solid surface using molecular dynamics simulation. We considered ideally smooth surfaces and rough surfaces that are regularly structured and randomly generated with a standard deviation of 2 A. The characteristic energy values of the solid surfaces used in the study are 0.1, 0.5, 1.0, 1.5, 2.0, and 2.5 kcal/mol, and the tip-to-surface distance considered is in the range from 1.5 to 3.7 nm. The behavior of water confined between the tip and a solid surface depends on the characteristic energy of the solid surface, the tip-to-surface distance, and the shape of the solid surface. The contact angle, neck radius of the water meniscus, and absolute value of capillary force decreases as the tip-to-surface distance increases, regardless of the pattern of the solid surface. Compared to an ideally smooth surface, the effect of regularly structured roughness on the behavior of a water meniscus on a solid surface is significant, whereas the effect of randomly generated roughness is relatively small.