Identification of important gene signatures in schizophrenia through feature fusion and genetic algorithm.

Schizophrenia is a debilitating psychiatric disorder that can significantly affect a patient's quality of life and lead to permanent brain damage. Although medical research has identified certain genetic risk factors, the specific pathogenesis of the disorder remains unclear. Despite the prevalence of research employing magnetic resonance imaging, few studies have focused on the gene level and gene expression profile involving a large number of screened genes. However, the high dimensionality of genetic data presents a great challenge to accurately modeling the data. To tackle the current challenges, this study presents a novel feature selection strategy that utilizes heuristic feature fusion and a multi-objective optimization genetic algorithm. The goal is to improve classification performance and identify the key gene subset for schizophrenia diagnostics. Traditional gene screening techniques are inadequate for accurately determining the precise number of key genes associated with schizophrenia. Our innovative approach integrates a filter-based feature selection method to reduce data dimensionality and a multi-objective optimization genetic algorithm for improved classification tasks. By combining the filtering and wrapper methods, our strategy leverages their respective strengths in a deliberate manner, leading to superior classification accuracy and a more efficient selection of relevant genes. This approach has demonstrated significant improvements in classification results across 11 out of 14 relevant datasets. The performance on the remaining three datasets is comparable to the existing methods. Furthermore, visual and enrichment analyses have confirmed the practicality of our proposed method as a promising tool for the early detection of schizophrenia.

Research Progress on Nanoplatforms and Nanotherapeutic Strategies in Treating Glioma.

Glioma is the most common and aggressive primary intracranial tumor within the central nervous system. The blood-brain barrier (BBB) has been a great hurdle for an effective glioma treatment. To effectively treat glioma, various strategies have been applied to deliver drugs to the brain by crossing the BBB. Nanocarrier-mediated drug delivery is emerging as an effective and noninvasive system to treat glioma, showing great potential in glioma therapy. In this review, we will provide a comprehensive overview on nanocarrier-mediated drug delivery and related glioma therapy. Following an initial overview of the BBB and blood-brain-tumor barrier (BBTB) structure and characteristics, nanocarrier-mediated drug delivery strategies (liposomes, micelles, inorganic systems, polymeric nanoparticles, nanogel system, biomimetic nanoparticles, and exosomes) for crossing the BBB are discussed. Finally, nanotherapeutic techniques (imaging-mediated chemotherapy, photothermal therapy, photodynamic therapy, gene therapy, immunotherapy, ferroptosis therapy, sonodynamic therapy, chemodynamic therapy, and combination therapy) in treating glioma are summarized. In addition, this review provides some perspectives on the clinical applications of nanomedicines.

Electrospun nanofibrous membrane with antibacterial and antiviral properties decorated with Myoporum bontioides extract and silver-doped carbon nitride nanoparticles for medical masks application.

Public health safety issues have been plaguing the world since the pandemic outbreak of coronavirus disease (COVID-19). However, most personal protective equipments (PPE) do not have antibacterial and anti- toxicity effects. In this work, we designed and prepared a reusable, antibacterial and anti-toxicity Polyacrylonitrile (PAN) based nanofibrous membrane cooperated with Ag/g-C3N4 (Ag-CN), Myoporum.bontioides (M. bontioides) plant extracts and Ag nanoparticles (NPs) by an electrospinning-process. The SEM and TEM characterization revealed the formation of raised, creased or wrinkled areas on the fiber surface caused by the Ag nanoparticles, the rough surface prevented the aerosol particles on the fiber surface from sliding and stagnating, thus providing excellent filtration performance. The PAN/M. bontioides/Ag-CN/Ag nanofibrous membrane could be employed as a photocatalytic bactericidal material, which not only degraded 96.37% of methylene blue within 150 min, but also exhibited the superior bactericidal effect of 98.65 ± 1.49% and 97.8 ± 1.27% against E. coli and S. aureus, respectively, under 3 hs of light exposure. After 3 cycles of sterilization experiments, the PAN/M. bontioides/Ag-CN/Ag nanofibrous membrane maintained an efficient sterilization effect. Molecular docking revealed that the compounds in M. bontioides extracts interacted with neo-coronavirus targets mainly on Mpro and RdRp proteins, and these compounds had the strongest docking energy with Mpro protein, the shortest docking radius, and more binding sites for key amino acids around the viral protein targets, which influenced the replication and transcription process of neo-coronavirus. The PAN/M.bontioides/Ag-CN/Ag nanofibrous membrane also performed significant inhibition of influenza A virus H3N2. The novel nanofiber membrane is expected to be applied to medical masks, which will improve human isolation and protection against viruses.

Delineating functional segregations of the human middle temporal gyrus with resting-state functional connectivity and coactivation patterns.

Although the middle temporal gyrus (MTG) has been parcellated into subregions with distinguished anatomical connectivity patterns, whether the structural topography of MTG can inform functional segregations of this area remains largely unknown. Accumulating evidence suggests that the brain's underlying organization and function can be directly and effectively delineated with resting-state functional connectivity (RSFC) by identifying putative functional boundaries between cortical areas. Here, RSFC profiles were used to explore functional segregations of the MTG and defined four subregions from anterior to posterior in two independent datasets, which showed a similar pattern with MTG parcellation scheme obtained using anatomical connectivity. The functional segregations of MTG were further supported by whole brain RSFC, coactivation, and specific RFSC, and coactivation mapping. Furthermore, the fingerprint with predefined 10 networks and functional characterizations of each subregion using meta-analysis also identified functional distinction between subregions. The specific connectivity analysis and functional characterization indicated that the bilateral most anterior subregions mainly participated in social cognition and semantic processing; the ventral middle subregions were involved in social cognition in left hemisphere and auditory processing in right hemisphere; the bilateral ventro-posterior subregions participated in action observation, whereas the left subregion was also involved in semantic processing; both of the dorsal subregions in superior temporal sulcus were involved in language, social cognition, and auditory processing. Taken together, our findings demonstrated MTG sharing similar structural and functional topographies and provide more detailed information about the functional organization of the MTG, which may facilitate future clinical and cognitive research on this area.

Multisolvent Similarity Measure of Chinese Herbal Medicine Ingredients for Cold-Hot Nature Identification.

Cold-hot nature theory is the core basic theory of traditional Chinese medicine (TCM). "Treating the hot syndrome with cold nature medicine and treating cold syndrome with hot nature medicine" indicates that correct classification of medical properties (cold or hot nature) of Chinese herbal medicines (CHMs) is an important basis for TCM treatment. In this study, we propose a novel multisolvent similarity measure retrieval scheme (MSSMRS) for discriminating CHMs as cold or hot. We explore a multisolvent distance metric learning algorithm to calculate similarity measure of CHM ingredients, and a retrieval scheme for nature identification. First, four solvents (chloroform, distilled water, absolute ethanol, and petroleum ether) are applied to extract ultraviolet (UV) spectrum data of CHM ingredients. Second, we study quantifying the similarity of CHM ingredients to fingerprint similarity. We explore a multisolvent distance metric learning (MSDML) algorithm to measure the similarity of CHM ingredients. MSDML can discover complementary characteristics of different solvent data sets through an optimization algorithm. Finally, a retrieval scheme is designed to analyze the relationship between the CHM ingredients and cold-hot nature. Extensive experimental results demonstrate that CHMs with similar compositions of substances have similar medicinal natures. Experimental evaluations based on the proposed retrieval scheme suggest the effectiveness of MSDML in the identification of the nature of CHMs.

Prediction of amyloid aggregation rates by machine learning and feature selection.

A novel data-based machine learning algorithm for predicting amyloid aggregation rates is reported in this paper. Based on a highly nonlinear projection from 16 intrinsic features of a protein and 4 extrinsic features of the environment to the protein aggregation rate, a feedforward fully connected neural network (FCN) with one hidden layer is trained on a dataset composed of 21 different kinds of amyloid proteins and tested on 4 rest proteins. FCN shows a much better performance than traditional algorithms, such as multivariable linear regression and support vector regression, with an average accuracy higher than 90%. Furthermore, by the correlation analysis and the principal component analysis, seven key features, folding energy, HP patterns for helix, sheet and helices cross membrane, pH, ionic strength, and protein concentration, are shown to constitute a minimum feature set for characterizing the amyloid aggregation kinetics.

Arachidonic Acid Metabolism and Kidney Inflammation.

As a major component of cell membrane lipids, Arachidonic acid (AA), being a major component of the cell membrane lipid content, is mainly metabolized by three kinds of enzymes: cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 (CYP450) enzymes. Based on these three metabolic pathways, AA could be converted into various metabolites that trigger different inflammatory responses. In the kidney, prostaglandins (PG), thromboxane (Tx), leukotrienes (LTs) and hydroxyeicosatetraenoic acids (HETEs) are the major metabolites generated from AA. An increased level of prostaglandins (PGs), TxA2 and leukotriene B4 (LTB4) results in inflammatory damage to the kidney. Moreover, the LTB4-leukotriene B4 receptor 1 (BLT1) axis participates in the acute kidney injury via mediating the recruitment of renal neutrophils. In addition, AA can regulate renal ion transport through 19-hydroxystilbenetetraenoic acid (19-HETE) and 20-HETE, both of which are produced by cytochrome P450 monooxygenase. Epoxyeicosatrienoic acids (EETs) generated by the CYP450 enzyme also plays a paramount role in the kidney damage during the inflammation process. For example, 14 and 15-EET mitigated ischemia/reperfusion-caused renal tubular epithelial cell damage. Many drug candidates that target the AA metabolism pathways are being developed to treat kidney inflammation. These observations support an extraordinary interest in a wide range of studies on drug interventions aiming to control AA metabolism and kidney inflammation.

Effects of Farnesiferol B on Ischemia-Reperfusion-Induced Renal Damage, Inflammation, and NF-κB Signaling.

BACKGROUND: G-protein-coupled bile acid receptor (TGR5), a membrane bile acid receptor, regulates macrophage reactivity, and attenuates inflammation in different disease models. However, the regulatory effects of TGR5 in ischemia/reperfusion (I/R)-induced kidney injury and inflammation have not yet been extensively studied. Therefore, we hypothesize that Farnesiferol B, a natural TGR5 agonist, could alleviate renal I/R injury by reducing inflammation and macrophage migration through activating TGR5. METHODS: Mice were treated with Farnesiferol B before I/R or sham procedures. Renal function, pathological analysis, and inflammatory mediators were examined. In vitro, the regulatory effects of Farnesiferol B on the Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway in macrophages were investigated. RESULTS: After I/R, Farnesiferol B-treated mice displayed better renal function and less tubular damage. Farnesiferol B reduced renal oxidative stress and inflammation significantly. In vitro, Farnesiferol B treatment alleviated lipopolysaccharide (LPS)-induced macrophage migration and activation, as well as LPS-induced NF-κB activation through TGR5. CONCLUSIONS: Farnesiferol B could protect kidney function from I/R-induced damage by attenuating inflammation though activating TGR5 in macrophages. Farnesiferol B might be a potent TGR5 ligand for the treatment of I/R-induced renal inflammation.

Toward Understanding the Cold, Hot, and Neutral Nature of Chinese Medicines Using in Silico Mode-of-Action Analysis.

One important, however, poorly understood, concept of Traditional Chinese Medicine (TCM) is that of hot, cold, and neutral nature of its bioactive principles. To advance the field, in this study, we analyzed compound-nature pairs from TCM on a large scale (>23 000 structures) via chemical space visualizations to understand its physicochemical domain and in silico target prediction to understand differences related to their modes-of-action (MoA) against proteins. We found that overall TCM natures spread into different subclusters with specific molecular patterns, as opposed to forming coherent global groups. Compounds associated with cold nature had a lower clogP and contain more aliphatic rings than the other groups and were found to control detoxification, heat-clearing, heart development processes, and have sedative function, associated with "Mental and behavioural disorders" diseases. While compounds associated with hot nature were on average of lower molecular weight, have more aromatic ring systems than other groups, frequently seemed to control body temperature, have cardio-protection function, improve fertility and sexual function, and represent excitatory or activating effects, associated with "endocrine, nutritional and metabolic diseases" and "diseases of the circulatory system". Compounds associated with neutral nature had a higher polar surface area and contain more cyclohexene moieties than other groups and seem to be related to memory function, suggesting that their nature may be a useful guide for their utility in neural degenerative diseases. We were hence able to elucidate the difference between different nature classes in TCM on the molecular level, and on a large data set, for the first time, thereby helping a better understanding of TCM nature theory and bridging the gap between traditional medicine and our current understanding of the human body.

Chinese Marine Materia Medica Resources: Status and Potential.

Chinese marine materia medica (CMMM) is a vital part of traditional Chinese medicine (TCM). Compared with terrestrial TCM, CMMM, derived from specific marine habitats, possesses peculiar chemical components with unique structures reflecting as potent pharmacological activities, distinct drug properties and functions. Nowadays, CMMM appears to be especially effective in treating such difficult diseases as cancers, diabetes, cardio-cerebrovascular diseases, immunodeficiency diseases and senile dementia, and therefore has become an important medicinal resource for the research and development of new drugs. In recent years, such development has attracted wide attention in the field of medicine. In this study, the CMMM resources in China were systematically investigated and evaluated. It was found that the historic experiences of Chinese people using CMMM have continuously accumulated over a period of more than 3600 years, and that the achievements of the research on modern CMMM are especially outstanding. By June 2015, 725 kinds of CMMMs from Chinese coastal sea areas have been identified and recorded, covering 1552 organisms and minerals. More than 3100 traditional prescriptions containing CMMMs have been imparted and inherited. However, the number of CMMMs is less than the 8188 terrestrial TCMs, from more than 12,100 medicinal terrestrial plants, animals and minerals. In the future, the research and development of CMMM should focus on the channel entries (TCM drug properties), compatibility, effective ingredients, acting mechanisms, drug metabolism and quality standard. This study reveals the high potential of CMMM development.

[Effect of 5 warm-hot nature Chinese drugs for promoting blood circulation and removing blood stasis on 5-HT, NE, and endocrine hormones of rats of cold coagulation and blood stasis syndrome].

OBJECTIVE: To study the mechanism of warm-hot nature Chinese drugs (WHNCD) for promoting blood circulation and removing blood stasis (PBCRBS) for intervening model rats of cold coagulation and blood stasis syndrome (CCBSS). METHODS: CCBSS rat model was set up in outbred SD rats using ice water immersion method. Totally 300 successfully modeled CCBSS rats were randomly divided into 5 groups according to the principle of balance weight, 60 in each group. Contents of triothyrone (T3), tetraiodothyroine (T4), progesterone (P), 5-hydroxytryptamine (5-HT), and noradrenalin (NE) were paralleledly detected in all groups. Then rats in each group were subdivided into 6 subgroups as the model group, the curcuma group, the Ligsticum Chuanxiong group, the safflower group, the Rhizoma Corydalis group, and the Olibanumg group. Besides, 5 normal control groups were set up for 5 indices, 50 rats in total. We need 70 rats (7 groups) to finish observing 1 index, 350 rats in total for 5 indices. Except those in the model group and the normal control group, rats were administered with corresponding decoction at 20 g crude drugs/kg body weight by gastrogavage, 3 mL each time, once daily for 7 successive days. Equal volume of normal saline was given to rats in the normal control group and the model group. Contents of T3, T4, P, 5-HT, and NE were detected before treatment and 1 week after treatment. RESULTS: Compared with before treatment in the same group, T3 increased in the Ligsticum Chuanxiong group and the Olibanumg group, 5-HT increased in the Ligsticum Chuanxiong group, T4, NE, and P increased in all medicated groups (P < 0.05). Compared with the normal control group, contents of T3, T4, 5-HT, NE, and P in the model group decreased (P < 0.05). Compared with the model group, contents of T3, T4, 5-HT, and NE increased in each medicated group (P < 0.05). There was statistical difference in contents of P between the Ligsticum Chuanxiong group and the Olibanumg group (P < 0.05). CONCLUSIONS: WHNCD for PBCRBS had regulatory roles in serum contents of T3, T4, P, and NE in modeled rats of CCBSS. They could promote the thyroid gland-gonadal axis function, enhance the function of the endocrine system, which might be one of the pharmacodynamic mechanism of WHNCD for PBCRBS in intervening CCBSS.

[Research progress of traditional mineral Chinese medicine].

Traditional mineral Chinese medicine is a characteristic part of Chinese medicine, in the development of traditional Chinese medicine has its unique role. With the development of science and technology and the increase of the medical level, traditional mineral medicine research is gradually thorough and wide-ranging. In recent years, traditional mineral Chinese medicine research mainly includes the physical properties of mineral medicine, structure, chemical composition, pharmacology and treatment mechanism research. The above several aspects of research in the mineral medicine has important practical and theoretical significance. The above several aspects of research status and the problems existing in the research were briefly summarized and reviewed in this paper, and its development were discussed, to provide reference for further studies in the future.

Malinzi, a traditional medicinal plants: Comprehensive review of botany, medical application, chemical composition, and pharmacology.

Malinzi is the dry ripe seed of Iris Lactea Pall. var. chinensis (Fisch.) Koidz and is a tradtional medicinal plant with significant development and utilization value. A total of 31 compounds from Malinzi have been reported, including flavonoids, quinones, oligostilbenes, and other constituents. Modern pharmacological studies have shown that Malinzi has good activities in anti-tumor, radio-sensitization, boost immunity, anti-oxidation, anti-fertility, and glucolipid metabolism. In this paper, by reviewing the domestic and foreign research literatures of Malinzi and summarizing its traditional uses, chemical constituents, and pharmacological activities, it is expected to provide theoretical reference for the subsequent in-depth research and application of Malinzi.

Bitter-Pungent Flavor Identification Based on Ingredient Information Similarity of Chinese Herbal Medicines.

BACKGROUND: The flavor theory of Chinese herbal medicines (CHMs) is one of the core theories of traditional Chinese medicine (TCM). Accurate flavor identification of CHMs is essential to guide the clinical application of CHMs. OBJECTIVE: To develop a new method for flavor identification of CHMs according to the ingredient information for CHMs. METHODS: It was found that the chemical basis of medicinal flavors was CHM ingredients. We developed a bitter-pungent flavor identification scheme to build a relationship between medicinal flavors and CHM ingredients. We firstly proposed a scientific hypothesis that "CHMs with similar flavors should have a similar chemical basis". To test this scientific hypothesis, we then explored an intelligent algorithm for bitter-pungent flavor identification of CHMs based on the information similarity of CHM ingredients. GC was used to separate the chemical ingredients of CHMs and analyze the ingredient information of CHMs. A distance metric learning algorithm was built to measure the similarity of GC chemical fingerprints. A bitter-pungent flavor identification scheme (BPFI) was proposed to predict the bitter-pungent flavor of CHMs. Finally, a number of experiments were performed to evaluate the identification performance of our scheme. RESULTS: Compared to classical algorithms, our proposed BPFI scheme has better flavor prediction performance. The total identification accuracy of our BPFI scheme reached 0.843. The area under ROC (receiver operating characteristic curve) curve (AUC) was 0.899. CONCLUSION: The experimental results confirmed our inference that the chemical basis of CHM flavors was CHM ingredients, and implied that CHMs with similar flavors had similar composition. The BPFI model proved to be effective and feasible. HIGHLIGHTS: Verification hypothesis: CHMs with similar flavors should have similar chemical basis.

Phytochemical and pharmacological properties of the genus Tamarix: a comprehensive review.

The genus Tamarix in the Tamaricaceae family consists of more than 100 species of halophyte plants worldwide that are mainly used to improve saline-alkali land and for coastal windbreaks, sand fixation, and afforestation in arid areas. A considerable number of species in this genus are also used as traditional medicines to treat various human diseases, especially in Asian and African countries. This review presents a comprehensive summary of 655 naturally occurring compounds derived from the genus Tamarix, categorized into flavonoids (18.0%), phenols (13.9%), tannins (9.3%), terpenoids (10.5%), essential oils (31.0%), and others (17.3%). The investigation revealed that the crude extracts and phytochemicals of this genus exhibited significant therapeutic potential, including anti-inflammatory, anti-Alzheimer, anticancer, antidiabetic, antibacterial, and antifungal activities. Six species of Tamarix have anticancer effects by causing cancer cell death, inducing autophagy, and stopping cell division. Seven species from the same genus have the potential for treating diabetes by inhibiting α-glycosidase activity, suppressing human islet amyloid polypeptide, regulating blood glucose levels, and modulating autophagy or inflammation. The focus on antibacterial and antidiabetic effects is due to the presence of volatile oil and flavonoid components. Extensive research has been conducted on the biological activity of 30 constituents, including 15 flavonoids, 5 phenols, 3 terpenoids, 1 tannin, and 6 others. Therefore, future research should thoroughly study the mechanisms of action of these and similar compounds. This is the most comprehensive review of the phytochemistry and pharmacological properties of Tamarix species, with a critical assessment of the current state of knowledge.

Intracerebral Hemorrhage Prognosis Classification via Joint-Attention Cross-Modal Network.

Intracerebral hemorrhage (ICH) is a critical condition characterized by a high prevalence, substantial mortality rates, and unpredictable clinical outcomes, which results in a serious threat to human health. Improving the timeliness and accuracy of prognosis assessment is crucial to minimizing mortality and long-term disability associated with ICH. Due to the complexity of ICH, the diagnosis of ICH in clinical practice heavily relies on the professional expertise and clinical experience of physicians. Traditional prognostic methods largely depend on the specialized knowledge and subjective judgment of healthcare professionals. Meanwhile, existing artificial intelligence (AI) methodologies, which predominantly utilize features derived from computed tomography (CT) scans, fall short of capturing the multifaceted nature of ICH. Although existing methods are capable of integrating clinical information and CT images for prognosis, the effectiveness of this fusion process still requires improvement. To surmount these limitations, the present study introduces a novel AI framework, termed the ICH Network (ICH-Net), which employs a joint-attention cross-modal network to synergize clinical textual data with CT imaging features. The architecture of ICH-Net consists of three integral components: the Feature Extraction Module, which processes and abstracts salient characteristics from the clinical and imaging data, the Feature Fusion Module, which amalgamates the diverse data streams, and the Classification Module, which interprets the fused features to deliver prognostic predictions. Our evaluation, conducted through a rigorous five-fold cross-validation process, demonstrates that ICH-Net achieves a commendable accuracy of up to 87.77%, outperforming other state-of-the-art methods detailed within our research. This evidence underscores the potential of ICH-Net as a formidable tool in prognosticating ICH, promising a significant advancement in clinical decision-making and patient care.

Accurate leukocyte detection based on deformable-DETR and multi-level feature fusion for aiding diagnosis of blood diseases.

In standard hospital blood tests, the traditional process requires doctors to manually isolate leukocytes from microscopic images of patients' blood using microscopes. These isolated leukocytes are then categorized via automatic leukocyte classifiers to determine the proportion and volume of different types of leukocytes present in the blood samples, aiding disease diagnosis. This methodology is not only time-consuming and labor-intensive, but it also has a high propensity for errors due to factors such as image quality and environmental conditions, which could potentially lead to incorrect subsequent classifications and misdiagnosis. Contemporary leukocyte detection methods exhibit limitations in dealing with images with fewer leukocyte features and the disparity in scale among different leukocytes, leading to unsatisfactory results in most instances. To address these issues, this paper proposes an innovative method of leukocyte detection: the Multi-level Feature Fusion and Deformable Self-attention DETR (MFDS-DETR). To tackle the issue of leukocyte scale disparity, we designed the High-level Screening-feature Fusion Pyramid (HS-FPN), enabling multi-level fusion. This model uses high-level features as weights to filter low-level feature information via a channel attention module and then merges the screened information with the high-level features, thus enhancing the model's feature expression capability. Further, we address the issue of leukocyte feature scarcity by incorporating a multi-scale deformable self-attention module in the encoder and using the self-attention and cross-deformable attention mechanisms in the decoder, which aids in the extraction of the global features of the leukocyte feature maps. The effectiveness, superiority, and generalizability of the proposed MFDS-DETR method are confirmed through comparisons with other cutting-edge leukocyte detection models using the private WBCDD, public LISC and BCCD datasets. Our source code and private WBCCD dataset are available at https://github.com/JustlfC03/MFDS-DETR.

The Morphology Dependent Interaction between Silver Nanoparticles and Bovine Serum Albumin.

Biological applications of silver nanoparticles (AgNPs) depend on the covalently attached or adsorbed proteins. A series of biological effects of AgNPs within cells are determined by the size, shape, aspect ratio, surface charge, and modifiers. Herein, the morphology dependent interaction between AgNPs and protein was investigated. AgNPs with three different morphologies, such as silver nanospheres, silver nanorods, and silver nanotriangles, were employed to investigate the morphological effect on the interaction with a model protein: bovine serum albumin (BSA). The adsorptive interactions between BSA and the AgNPs were probed by UV-Vis spectroscopy, fluorescence spectroscopy, dynamic light scattering (DLS), Fourier transform infrared spectrometry (FTIR), transmission electron microscopy (TEM), and circular dichroism (CD) techniques. The results revealed that the particle size, shape, and dispersion of the three types of AgNPs markedly influence the interaction with BSA. Silver nanospheres and nanorods were capsulated by protein coronas, which led to slightly enlarged outer size. The silver nanotriangles evolved gradually into nanodisks in the presence of BSA. Fluorescence spectroscopy confirmed the static quenching the fluorescence emission of BSA by the three AgNPs. The FTIR and CD results suggested that the AgNPs with different morphologies had different effects on the secondary structure of BSA. The silver nanospheres and silver nanorods induced more pronounced structural changes than silver nanotriangles. These results suggest that the formation of a protein corona and the aggregation behaviors of AgNPs are markedly determined by their inherent morphologies.

Discovery of natural polyphenols from the wild vegetable Suaeda salsa L. with potential cardioprotective functions.

Suaeda salsa L. (Chenopodiaceae) is a wild vegetable distributed along the northern coast of China. Searching for potential agents with health benefits from S. salsa L. led to the identification of 14 flavonoids (1-14), eight phenolic acids (15-22), one coumarin (23), one benzoquinone (24), two sesquiterpenes (25, 26), and three lignins (27-29) from an aqueous ethanol (EtOH) extract of the above-ground whole plant using various column chromatographic methods. High-resolution electrospray ionization mass spectrometry (HRESIMS) analyses and nuclear magnetic resonance (1H and 13C NMR) spectroscopy were adopted to examine the structural properties of the compounds. To date, our study is the first to identify 20 compounds from this genus. Some compounds exhibited significant health benefits in zebrafish models. Compounds 2, 4, 23, and 28 significantly improved oxidative damage, while compounds 1-5, 7, 11, 13, 18, 19, and 23 significantly improved zebrafish lateral line neuromast inflammation. Additionally, compounds 1, 4, 8, 13, and 16 significantly promoted zebrafish angiogenesis, while compounds 3-5 and 18 significantly improved zebrafish arrhythmia. Furthermore, a flavonoid-targeted metabolomics study revealed that flavanone was the precursor of all of the flavonoids and had its highest accumulation in August, while the others showed their highest accumulation in September. Thus, the best time to harvest most of the bioactive polyphenols is during September. The present study revealed that the wild vegetable S. salsa L. might be developed as a potential cardioprotective functional food.

Clinical development and informatics analysis of natural and semi-synthetic flavonoid drugs: A critical review.

BACKGROUND: Flavonoids are one of the most important metabolites with vast structural diversity and a plethora of potential pharmacological applications, which have drawn considerable attention in the laboratory. Nevertheless, it remains uncertain how many candidates were progressed to clinical application. AIM OF REVIEW: We carried out a critical review of natural and semi-synthetic flavonoid drugs and candidates undergoing different clinical phases worldwide by applying an adequate search method and conducted a brief cheminformatic and bioinformatic analysis. It was expected that the obtained results might narrow the screening scope and reduce the cost of drug research and development. KEY SCIENTIFIC CONCEPTS OF REVIEW: To our knowledge, this is the most systematic summarization of flavonoid-based drugs and clinical candidates to date. It was found that a total of 19 flavonoid-based drugs have been approved for the market, and of these, natural flavonoids accounted for 52.6%. Besides, a total of 36 flavonoid-based clinical candidates are undergoing or suspended in different phases, and of these, natural flavonoids account for 44.4%. Thus, natural flavonoids remain the best option for finding novel agents/active templates, and when investigated in conjunction with synthetic chemicals and biologicals, they offer the potential to discover novel structures that can lead to effective agents against a variety of human diseases. Additionally, flavonoid-based marketed drugs have been successful in cardiovascular treatment, and the related drugs account for more than 30% of marketed drugs. However, the use of flavonoids as antineoplastic and immunomodulating agents is not likely for approximately 50% of the candidates suspended in the clinical stage. Interestingly, the marketed drugs covered a broader range of chemical spaces based on size, polarity, and three-dimensional structure compared to the clinical candidates. In addition, flavonoid glycosides with poor oral bioavailability account for 36.8% of the marketed drugs, and thus, they could be thoroughly investigated.