Electronic Beam Steering Metamaterial Antenna with Dual-Tuned Mode of Liquid Crystal Material.

In this study, a dual-tuned mode of liquid crystal (LC) material was proposed and adopted on reconfigurable metamaterial antennas to expand the fixed-frequency beam-steering range. The novel dual-tuned mode of the LC is composed of double LC layers combined with composite right/left-handed (CRLH) transmission line theory. Through a multi-separated metal layer, the double LC layers can be loaded with controllable bias voltage independently. Therefore, the LC material exhibits four extreme states, among which the permittivity of LC can be varied linearly. On the strength of the dual-tuned mode of LC, a CRLH unit cell is elaborately designed on three-layer substrates with balanced dispersion values under arbitrary LC state. Then five CRLH unit cells are cascaded to form an electronically controlled beam-steering CRLH metamaterial antenna on a downlink Ku satellite communication band with dual-tuned characteristics. The simulated results demonstrate that the metamaterial antenna features' continuous electronic beam-steering capacity from broadside to -35° at 14.4 GHz. Furthermore, the beam-steering properties are implemented in a broad frequency band from 13.8 GHz to 17 GHz, with good impedance matching. The proposed dual-tuned mode can make the regulation of LC material more flexible and enlarge the beam-steering range simultaneously.

Can Light Alter the Yield of Plasmon-Driven Reactions on Gold and Gold-Palladium Nanoplates?

Noble-metal nanostructures, as well as their bimetallic analogues, catalyze a broad spectrum of plasmon-driven reactions. Catalytic properties of such nanostructures arise from light-generated surface plasmon resonances that decay forming transient hot electrons and holes. Hot carriers with "slower" dissipation rates accumulate on nanostructures generating an electrostatic potential. In this study, we examine whether light intensity can alter the electrostatic potential of mono- and bimetallic nanostructures changing yields of plasmon-driven reactions. Using tip-enhanced Raman spectroscopy (TERS), we quantified the yield of plasmon-driven transformations of 4-nitrobenzenethiol (4-NBT) and 3-mercaptobenzoic acid (3-MBA) on gold and gold-palladium nanoplates (AuNPs and Au@PdNPs, respectively). We found that on AuNPs 3-MBA decarboxylated forming thiophenol (TP), whereas 4-NBT was reduced to DMAB. The yield of both TP and DMAB gradually increased with increasing light intensity. On Au@PdNPs, 3-MBA could be reduced to 3-mercaptophenylmethanol (3-MPM), the yield of which was also directly dependent on the light intensity.

Plasmon-Driven Chemistry on Mono- and Bimetallic Nanostructures.

ConspectusHot carriers are highly energetic species that can perform a large spectrum of chemical reactions. They are generated on the surfaces of nanostructures via direct interband, phonon-assisted intraband, and geometry-assisted decay of localized surface plasmon resonances (LSPRs), which are coherent oscillations of conductive electrons. LSPRs can be induced on the surface of noble metal (Ag or Au) nanostructures by illuminating the surfaces with electromagnetic irradiation. These noble metals can be coupled with catalytic metals, such as Pt, Pd, and Ru, to develop bimetallic nanostructures with unique catalytic activities. The plasmon-driven catalysis on bimetallic nanostructures is light-driven, which essentially enables green chemistry in organic synthesis. During the past decade, surface-enhanced Raman spectroscopy (SERS) has been actively utilized to study the mechanisms of plasmon-driven reactions on mono- and bimetallic nanostructures. SERS has provided a wealth of knowledge about the mechanisms of numerous plasmon-driven redox, coupling, and scissoring reactions. However, the nanoscale catalytic properties of both mono- and bimetallic nanostructures as well as the underlying physical cause of their catalytic reactivity and selectivity remained unclear for decades.In this Account, we focus on the most recent findings reported by our and other research groups that shed light on the nanoscale properties of mono- and bimetallic nanostructures. This information was revealed by tip-enhanced Raman spectroscopy (TERS), a modern analytical technique that has single-molecule sensitivity and subnanometer spatial resolution. TERS findings have shown that plasmonic reactivity and the selectivity of bimetallic nanostructures are governed by the nature of the catalytic metal and the strength of the rectified electric field on their surfaces. TERS has also revealed that the catalytic properties of bimetallic nanostructures directly depend on the interplay between the catalytic and plasmonic metals. We anticipate that these findings will be used to tailor synthetic approaches that are used to fabricate novel nanostructures with desired catalytic properties. The experimental and theoretical results discussed in this Account will facilitate a better understanding of TERS and explain artifacts that could be encountered upon TERS imaging of a large variety of samples. Consequently, plasmon-driven chemistry should be considered as an essential part of near-field microscopy.

Predicting gene phenotype by multi-label multi-class model based on essential functional features.

Phenotype is one of the most significant concepts in genetics, which is used to describe all the characteristics of a research object that can be observed. Considering that phenotype reflects the integrated features of genotype and environment factors, it is hard to define phenotype characteristics, even difficult to predict unknown phenotypes. Restricted by current biological techniques, it is still quite expensive and time-consuming to obtain sufficient structural information of large-scale phenotype-associated genes/proteins. Various bioinformatics methods have been presented to solve such problem, and researchers have confirmed the efficacy and prediction accuracy of functional network-based prediction. But general functional descriptions have highly complicated inner structures for phenotype prediction. To further address this issue and improve the efficacy of phenotype prediction on more than ten kinds of phenotypes, we first extract functional enrichment features from GO and KEGG, and then use node2vec to learn functional embedding features of genes from a gene-gene network. All these features are analyzed by some feature selection methods (Boruta, minimum redundancy maximum relevance) to generate a feature list. Such list is fed into the incremental feature selection, incorporating some multi-label classifiers built by RAkEL and some classic base classifiers, to build an optimum multi-label multi-class classification model for phenotype prediction. According to recent researches, our method has indeed identified many literature-supported genes/proteins and their associated phenotypes, and even some candidate genes with re-assigned new phenotypes, which provide a new computational tool for the accurate and effective phenotypic prediction.

Synthesis and Spectral Characteristics Investigation of the 2D-2D vdWs Heterostructure Materials.

Due to the attractive optical and electrical properties, van der Waals (vdWs) heterostructures constructed from the different two-dimensional materials have received widespread attention. Here, MoS2/h-BN, MoS2/graphene, WS2/h-BN, and WS2/graphene vdWs heterostructures are successfully prepared by the CVD and wet transfer methods. The distribution, Raman and photoluminescence (PL) spectra of the above prepared heterostructure samples can be respectively observed and tested by optical microscopy and Raman spectrometry, which can be used to study their growth mechanisms and optical properties. Meanwhile, the uniformity and composition distribution of heterostructure films can also be analyzed by the Raman and PL spectra. The internal mechanism of Raman and PL spectral changes can be explained by comparing and analyzing the PL and Raman spectra of the junction and non-junction regions between 2D-2D vdWs heterostructure materials, and the effect of laser power on the optical properties of heterostructure materials can also be analyzed. These heterostructure materials exhibit novel and unique optical characteristics at the stacking or junction, which can provide a reliable experimental basis for the preparation of suitable TMDs heterostructure materials with excellent performance.

Nanoscale Structural Characterization of Individual Viral Particles Using Atomic Force Microscopy Infrared Spectroscopy (AFM-IR) and Tip-Enhanced Raman Spectroscopy (TERS).

Viruses are infections species that infect a large spectrum of living systems. Although displaying a wide variety of shapes and sizes, they are all composed of nucleic acid encapsulated into a protein capsid. After virions enter the host cell, they replicate to produce multiple copies of themselves. They then lyse the host, releasing virions to infect new cells. The high proliferation rate of viruses is the underlying cause of their fast transmission among living species. Although many viruses are harmless, some of them are responsible for severe diseases such as AIDS, viral hepatitis, and flu. Traditionally, electron microscopy is used to identify and characterize viruses. This approach is time- and labor-consuming, which is problematic upon pandemic proliferation of previously unknown viruses, such as H1N1 and COVID-19. Herein, we demonstrate a novel diagnosis approach for label-free identification and structural characterization of individual viruses that is based on a combination of nanoscale Raman and infrared spectroscopy. Using atomic force microscopy-infrared (AFM-IR) spectroscopy, we were able to probe structural organization of the virions of Herpes Simplex Type 1 viruses and bacteriophage MS2. We also showed that tip-enhanced Raman spectroscopy (TERS) could be used to reveal protein secondary structure and amino acid composition of the virus surface. Our results show that AFM-IR and TERS provide different but complementary information about the structure of complex biological specimens. This structural information can be used for fast and reliable identification of viruses. This nanoscale bimodal imaging approach can be also used to investigate the origin of viral polymorphism and study mechanisms of virion assembly.

Formononetin alleviates Streptococcus suis infection by targeting suilysin.

Streptococcus suis serotype 2 (SS2) has become a leading pathogen responsible for swine industry and human infections, causing enormous economic loss and triggering food safety risk. New and alternative strategies for combating this microorganism are urgently needed. Suilysin (SLY), a pore-forming toxins produced by SS2 has been revealed play critical role during its infection and could be an ideal target for combating this pathogen. Here, we found that formononetin (Form) inhibited the haemolytic activity of SLY without exerting growth pressure on SS2 or affecting the expression of SLY. At the cellular infection level, Form treatment diminished the cytotoxicity induced by SLY or SS2 and inflammatory response induced by SS2. In addition, the treatment with Form reduced bacterial burden in livers and spleens in SS2 infected mice. These data revealed that Form could attenuate the pathogenesis of SS2 both in vitro and in vivo by targeting SLY, suggesting that this compound could be used in combating S. suis infections.

Serum Level of Antibodies Against Hepatitis B Core Protein Is Associated With Clinical Relapse After Discontinuation of Nucleos(t)ide Analogue Therapy.

BACKGROUND & AIMS: Levels of antibodies against the hepatitis B virus (HBV) core protein (anti-HBc) have been associated with response to nucleos(t)ide analogue and (peg)interferon therapy in patients with chronic HBV infection. We performed a prospective study to determine whether the total serum level of anti-HBc level (immunoglobulins M and G) is associated with clinical relapse after discontinuation of nucleos(t)ide analogue-based therapy. METHODS: We collected data from patients with chronic HBV infection who discontinued nucleos(t)ide analogue therapy according to pre-specified stopping criteria, recruited from November 2012 through July 2016 at an academic hospital in Guangzhou, China. Patients were followed through February 2017. We performed comprehensive biochemical and virologic tests at every visit, and anti-HBc was quantified for 2 years after treatment cessation (at baseline and weeks 4, 8, 12, 24, 48, and 96). The primary endpoint was clinical relapse, defined as level of HBV DNA >2000 IU/mL and level of alanine aminotransferase more than 2-fold the upper limit of normal-these were also the criteria for retreatment. RESULTS: We followed 100 patients (71% positive for HB e antigen [HBeAg] at the start of nucleos(t)ide analogue therapy, 43% treated with entecavir or tenofovir) for a median of 2.5 years after stopping therapy. Clinical relapse occurred in 39 patients (in 46% of patients at year 4 after discontinuation). High level of anti-HBc at the end of treatment (hazard ratio [HR], 0.31 per log IU/mL; P = .002) and low level of HB surface antigen (HBsAg) at the end of treatment (HR, 1.71 per log IU/mL; P = .032) were associated with a reduced risk of clinical relapse after adjusting for age, start of nucleos(t)ide analogue therapy, HBeAg-status, and consolidation therapy duration. At year 4, 21% of patients with anti-HBc levels at the end of treatment ≥1000 IU/mL developed a clinical relapse compared to 85% of patients with levels <100 IU/mL (P < .001). An HBsAg level at the end of treatment ≤100 IU/mL was associated with a reduced risk of relapse (HR 0.30; P = .045). However, 82% of patients had levels of HBsAg above 100 IU/mL; for these patients, level of anti-HBc at the end of treatment could be used to determine the risk of relapse (HR 0.39 per log IU/mL; P = .005). CONCLUSION: In a median 2.5-year follow-up study of patients with chronic HBV infection who stopped nucleos(t)ide analogue therapy, total serum level of anti-HBc at the end of treatment was associated with risk of clinical relapse. Serum level of anti-HBc might be used to select patients suitable for discontinuing nucleos(t)ide analogue therapy.

An investigation of the levels of vitamins A, D, and E in the serum of Chinese pregnant women.

BACKGROUND: Vitamins A, D (Vitamin D2 and vitamin D3) and E, play an important role during pregnancy. METHODS: Sera were collected from 1056 normal pregnant women, who were between 18 and 40 years old, at seven different hospitals in northeastern China. The levels of Vitamin A and E in the sera samples were detected using HPLC (High Performance Liquid Chromatography), and the level of vitamin D was measured by LC-MS (Liquid Chromatography-Mass Spectrometry). Data were analyzed using IBM SPSS Statistics 21. RESULTS: The mean levels of vitamin A, D and E in the 1056 sera samples were 0.39 mg/L (0.38-0.39), 20.44 µg/L (19.86-21.08) and 12.96 mg/L (12.70-13.25), respectively. The levels of vitamin A, D, and E deficiency were 17.05%, 0.19%, and 56.44%, respectively. The levels of vitamin A, D, and E of those between age 21 and 31 among the 1056 pregnant women were similar. The correlation of vitamin E and D was significant at the .01 level (two-tailed), and the correlation of vitamin A and age was significant at the .05 level (2-tailed). CONCLUSION: According to our finding, the levels of vitamin A, D, and E in the sera of pregnant women in northeastern China were affected by where they live and their age. Vitamin D deficiency was very serious, vitamin A deficiency was common, while vitamin E seems to be sufficient.

Off-Treatment Hepatitis B Virus (HBV) DNA Levels and the Prediction of Relapse After Discontinuation of Nucleos(t)ide Analogue Therapy in Patients With Chronic Hepatitis B: A Prospective Stop Study.

Background: The optimal management remains unknown after nucleos(t)ide analogue (NA) discontinuation in patients with chronic hepatitis B (CHB). This prospective study investigated the role of off-treatment viral kinetics in predicting relapse after discontinuation of NA therapy. Methods: A total of 82 noncirrhotic Asian patients with CHB who discontinued NA therapy according to international guidelines were prospectively followed. Patients with a hepatitis B virus (HBV) DNA level of >2000 IU/mL and an alanine aminotransferase (ALT) level of >2 times the upper limit of normal (clinical relapse) were retreated. Results: Sixty patients were HBV envelope antigen (HBeAg) positive at the start of treatment, and 22 were HBeAg negative. Clinical relapse developed in 28 patients (2-year rates, 31% among HBeAg-positive patients and 53% among HBeAg-negative patients). Age of ≤35 years (hazard ratio [HR], 0.37; P = .026) and end-of-treatment HBsAg level of ≤200 IU/mL (HR, 0.39; P = .078) were independently associated with lower relapse rates. A high risk of biochemical relapse (defined as an ALT level of >2 times the upper limit of normal) was observed if the HBV DNA level was >200000 IU/mL when the level was initially elevated, compared with HBV DNA levels of >2000 to ≤200000 IU/mL (HR, 8.42; P < .001). The risk of biochemical relapse was also high in patients with persistent elevation in the HBV DNA level (confirmed to be >2000 IU/mL within 3 months), compared with the group with transient elevation (HR, 6.87; P < .001). Conclusions: After NA discontinuation, a lower relapse rate was observed in younger patients and in those with low end-of-treatment HBsAg levels. The level and persistence of off-treatment elevated HBV DNA levels were useful in the prediction of a subsequent biochemical relapse and may thus be used to guide off-treatment management.

Single Molecule Study on Polymer-Nanoparticle Interactions: The Particle Shape Matters.

The study on the nanoparticle-polymer interactions is very important for the design/preparation of high performance polymer nanocomposite. Here we present a method to quantify the polymer-particle interaction at single molecule level by using AFM-based single molecule force spectroscopy (SMFS). As a proof-of-concept study, we choose poly-l-lysine (PLL) as the polymer and several different types of polyoxometalates (POM) as the model particles to construct several different polymer nanocomposites and to reveal the binding mode and quantify the binding strength in these systems. Our results reveal that the shape of the nanoparticle and the binding geometry in the composite have significantly influenced the binding strength of the PLL/POM complexes. Our dynamic force spectroscopy studies indicate that the disk-like geometry facilitate the unbinding of PLL/AlMo6 complexes in shearing mode, while the unzipping mode becomes dominate in spherical PLL-P8W48 system. We have also systematically investigated the effects of charge numbers, particle size, and ionic strength on the binding strength and binding mode of PLL/POM, respectively. Our results show that electrostatic interactions dominate the stability of PLL/POM complexes. These findings provide a way for tuning the mechanical properties of polyelectrolyte-nanoparticle composites.

Potential effects of telbivudine and entecavir on renal function: a systematic review and meta-analysis.

BACKGROUND: To assess the potential effects of telbivudine (LdT) and entecavir (ETV) on renal function in patients with chronic hepatitis B (CHB), we performed a meta-analysis of the relevant data available on these agents to evaluate their effects on the estimated glomerular filtration rate (eGFR) during treatment. METHODS: The PubMed, EMBASE, Scopus, CNKI (China National Knowledge Infrastructure), Cochrane Library, and WanFang databases were searched for relevant articles appearing in the literature up to July 1, 2015. A total of 6 studies (1960 CHB patients) with 1-year eGFR outcomes were retrieved and analyzed. RESULTS: Generally, the results of the 6 studies analyzed showed that eGFR was improved after LdT treatment, but was decreased after ETV treatment. Using a fixed-effects approach, the change in eGFR was found to be significantly different between LdT and ETV treatment (Z = 3.64; P = 0.0003). Whereas the eGFR was slightly decreased with ETV compared with baseline (-1.45 mL/min/1.73 m(2)), the eGFR was improved with LdT (2.99 mL/min/1.73 m(2)) after 1 year of treatment. An overall test of effect in the meta-analysis showed that the eGFR in LdT-treated patients was significantly improved after 1-year of treatment (Z = 3.71; P = 0.0002). CONCLUSION: This meta-analysis has confirmed that LdT has a renal protective effect whereas ETV does not. However, whether the benefit on renal function outweighs the occurrence of resistance in specific clinical situations is not yet clear.

[Prevention and treatment of aromatase inhibitor-associated bone loss by shugan jiangu recipe in postmenopausal women with breast cancer: a clinical study].

OBJECTIVE: To study the effect of Shugan Jiangu Recipe (SJR) on bone mineral density (BMD) and serum bone metabolic biochemical markers in postmenopausal breast cancer patients with osteopenia. METHODS: Totally 38 patients of postmenopausal women with breast cancer, who received aromatase inhibitors (AIs), were assigned to the treatment group (21 cases) and the control group (17 cases) by using random digit table. All patients took Caltrate D Tablet (containing Ca 600 mg and Vit D3 125 IU), one tablet daily. Patients in the treatment group took SJR, 6 g each time, twice daily for 6 successive months. The bone mineral density (BMD) level was detected before treatment and at months 6 after treatment. Levels of bone alkaline phosphatase (BALP), bone gla protein (BGP), tartrate-resistant acid phosphatase (TRAP), and C-terminal telopeptide of type II collagen (CTX-II) were detected by enzyme linked immunosorbent assay (ELISA). The drug safety was also assessed. RESULTS: Compared with before treatment, BMD of L2-4 and femur neck obviously increased in the treatment group at month 6 after treatment (P < 0.01), serum BALP and TRAP decreased (P < 0.05). Compared with before treatment, BMD of L2-4 and femur neck obviously decreased in the control group at month 6 after treatment (P < 0.05), serum BALP and TRAP increased (P < 0.01). Compared with the control group, lumbar and femur neck BMD obviously increased, serum levels of BGP and BALP obviously decreased, and serum levels of CTX-II and TRAP obviously increased in the treatment group at month 6 after treatment (P < 0.01). No serious adverse event occurred during the treatment period. Bone fracture occurred in one case of the control group (5.8%). CONCLUSION: SJR could attenuate bone loss of postmenopausal women with breast cancer who received AIs, increase BMD and improve abnormal bone metabolism.

Identification of Colon Immune Cell Marker Genes Using Machine Learning Methods.

Immune cell infiltration that occurs at the site of colon tumors influences the course of cancer. Different immune cell compositions in the microenvironment lead to different immune responses and different therapeutic effects. This study analyzed single-cell RNA sequencing data in a normal colon with the aim of screening genetic markers of 25 candidate immune cell types and revealing quantitative differences between them. The dataset contains 25 classes of immune cells, 41,650 cells in total, and each cell is expressed by 22,164 genes at the expression level. They were fed into a machine learning-based stream. The five feature ranking algorithms (last absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, minimum redundancy maximum relevance, and random forest) were first used to analyze the importance of gene features, yielding five feature lists. Then, incremental feature selection and two classification algorithms (decision tree and random forest) were combined to filter the most important genetic markers from each list. For different immune cell subtypes, their marker genes, such as KLRB1 in CD4 T cells, RPL30 in B cell IGA plasma cells, and JCHAIN in IgG producing B cells, were identified. They were confirmed to be differentially expressed in different immune cells and involved in immune processes. In addition, quantitative rules were summarized by using the decision tree algorithm to distinguish candidate immune cell types. These results provide a reference for exploring the cell composition of the colon cancer microenvironment and for clinical immunotherapy.

Plasmon-Determined Selectivity in Photocatalytic Transformations on Gold and Gold-Palladium Nanostructures.

Noble metal nanostructures absorb light producing coherent oscillations of the metal's electrons, so-called localized surface plasmon resonances (LSPRs). LSPRs can decay generating hot carriers, highly energetic species that trigger chemical transformations in the molecules located on the metal surfaces. The number of chemical reactions can be expanded by coupling noble and catalytically active metals. However, it remains unclear whether such mono- and bimetallic nanostructures possess any sensitivity toward one or another chemical reaction if both of them can take place in one molecular analyte. In this study, we utilize tip-enhanced Raman spectroscopy (TERS), an emerging analytical technique that has single-molecule sensitivity and sub-nanometer spatial resolution, to investigate plasmon-driven reactivity of 2-nitro-5-thiolobenzoic acid (2-N-5TBA) on gold and gold@palladium nanoplates (AuNPs and Au@PdNPs). This molecular analyte possesses both nitro and carboxyl groups, which can be reduced or removed by hot carriers. We found that on AuNPs, 2-N-5TBA dimerized forming 4,4'-dimethylazobenzene (DMAB), the bicarbonyl derivative of DMAB, as well as 4-nitrobenzenethiol (4-NBT). Our accompanying theoretical investigation based on density functional theory (DFT) and time-dependent density functional theory (TDDFT) confirmed these findings. The theoretical analysis shows that 2-N-5TBA first dimerized forming the bicarbonyl derivative of DMAB, which then decarboxylated forming DMAB. Finally, DMAB can be further reduced leading to 4-NBT. This reaction mechanism is supported by TERS-determined yields on these three molecules on AuNPs. We also found that on Au@PdNPs, 2-N-5TBA first formed the bicarbonyl derivative of DMAB, which is then reduced to both bihydroxyl-DMAB and 4-amino-3-mercaptobenzoic acid. The yield of these reaction products on Au@PdNPs strictly follows the free-energy potential of these molecules on the metallic surfaces.

Role of Plasmonic Antenna in Hot Carrier-Driven Reactions on Bimetallic Nanostructures.

Noble metal nanostructures can efficiently harvest electromagnetic radiation, which, in turn, is used to generate localized surface plasmon resonances. Surface plasmons decay, producing hot carriers, that is, short-lived species that can trigger chemical reactions on metallic surfaces. However, noble metal nanostructures catalyze only a very small number of chemical reactions. This limitation can be overcome by coupling such nanostructures with catalytic-active metals. Although the role of such catalytically active metals in plasmon-driven catalysis is well-understood, the mechanistics of a noble metal antenna in such chemistry remains unclear. In this study, we utilize tip-enhanced Raman spectroscopy, an innovative nanoscale imaging technique, to investigate the rates and yields of plasmon-driven reactions on mono- and bimetallic gold- and silver-based nanostructures. We found that silver nanoplates (AgNPs) demonstrate a significantly higher yield of 4-nitrobenzenehtiol to p,p'-dimercaptoazobisbenzene (DMAB) reduction than gold nanoplates (AuNPs). We also observed substantially greater yields of DMAB on silver-platinum and silver-palladium nanoplates (Ag@PtNPs and Ag@PdNPs) compared to their gold analogues, Au@PtNPs and Au@PdNPs. Furthermore, Ag@PtNPs exhibited enhanced reactivity in 4-mercatophenylmethanol to 4-mercaptobenzoic acid oxidation compared to Au@PtNPs. These results showed that silver-based bimetallic nanostructures feature much greater reactivity compared to their gold-based analogues.

Characterizations of microRNAs involved in the molecular mechanisms underlying the therapeutic effects of noni (Morinda citrifolia L.) fruit juice on hyperuricemia in mice.

Background: Hyperuricemia is generally defined as the high level of serum uric acid and is well known as an important risk factor for the development of various medical disorders. However, the medicinal treatment of hyperuricemia is frequently associated with multiple side-effects. Methods: The therapeutic effect of noni (Morinda citrifolia L.) fruit juice on hyperuricemia and the underlying molecular mechanisms were investigated in mouse model of hyperuricemia induced by potassium oxonate using biochemical and high-throughput RNA sequencing analyses. Results: The levels of serum uric acid (UA) and xanthine oxidase (XOD) in mice treated with noni fruit juice were significantly decreased, suggesting that the noni fruit juice could alleviate hyperuricemia by inhibiting the XOD activity and reducing the level of serum UA. The contents of both serum creatinine and blood urine nitrogen of the noni fruit juice group were significantly lower than those of the model group, suggesting that noni fruit juice promoted the excretion of UA without causing deleterious effect on the renal functions in mice. The differentially expressed microRNAs involved in the pathogenesis of hyperuricemia in mice were identified by RNA sequencing with their target genes further annotated based on both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases to explore the metabolic pathways and molecular mechanisms underlying the therapeutic effect on hyperuricemia by noni fruit juice. Conclusion: Our study provided strong experimental evidence to support the further investigations of the potential application of noni fruit juice in the treatment of hyperuricemia.

Molecular and biochemical investigations of the anti-fatigue effects of tea polyphenols and fruit extracts of Lycium ruthenicum Murr. on mice with exercise-induced fatigue.

Background: The molecular mechanisms regulating the therapeutic effects of plant-based ingredients on the exercise-induced fatigue (EIF) remain unclear. The therapeutic effects of both tea polyphenols (TP) and fruit extracts of Lycium ruthenicum (LR) on mouse model of EIF were investigated. Methods: The variations in the fatigue-related biochemical factors, i.e., lactate dehydrogenase (LDH), superoxide dismutase (SOD), tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), interleukin-2 (IL-2), and interleukin-6 (IL-6), in mouse models of EIF treated with TP and LR were determined. The microRNAs involved in the therapeutic effects of TP and LR on the treatment of mice with EIF were identified using the next-generation sequencing technology. Results: Our results revealed that both TP and LR showed evident anti-inflammatory effect and reduced oxidative stress. In comparison with the control groups, the contents of LDH, TNF-α, IL-6, IL-1ß, and IL-2 were significantly decreased and the contents of SOD were significantly increased in the experimental groups treated with either TP or LR. A total of 23 microRNAs (21 upregulated and 2 downregulated) identified for the first time by the high-throughput RNA sequencing were involved in the molecular response to EIF in mice treated with TP and LR. The regulatory functions of these microRNAs in the pathogenesis of EIF in mice were further explored based on Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses with a total of over 20,000-30,000 target genes annotated and 44 metabolic pathways enriched in the experimental groups based on GO and KEGG databases, respectively. Conclusion: Our study revealed the therapeutic effects of TP and LR and identified the microRNAs involved in the molecular mechanisms regulating the EIF in mice, providing strong experimental evidence to support further agricultural development of LR as well as the investigations and applications of TP and LR in the treatment of EIF in humans, including the professional athletes.

Immune responses of different COVID-19 vaccination strategies by analyzing single-cell RNA sequencing data from multiple tissues using machine learning methods.

Multiple types of COVID-19 vaccines have been shown to be highly effective in preventing SARS-CoV-2 infection and in reducing post-infection symptoms. Almost all of these vaccines induce systemic immune responses, but differences in immune responses induced by different vaccination regimens are evident. This study aimed to reveal the differences in immune gene expression levels of different target cells under different vaccine strategies after SARS-CoV-2 infection in hamsters. A machine learning based process was designed to analyze single-cell transcriptomic data of different cell types from the blood, lung, and nasal mucosa of hamsters infected with SARS-CoV-2, including B and T cells from the blood and nasal cavity, macrophages from the lung and nasal cavity, alveolar epithelial and lung endothelial cells. The cohort was divided into five groups: non-vaccinated (control), 2*adenovirus (two doses of adenovirus vaccine), 2*attenuated (two doses of attenuated virus vaccine), 2*mRNA (two doses of mRNA vaccine), and mRNA/attenuated (primed by mRNA vaccine, boosted by attenuated vaccine). All genes were ranked using five signature ranking methods (LASSO, LightGBM, Monte Carlo feature selection, mRMR, and permutation feature importance). Some key genes that contributed to the analysis of immune changes, such as RPS23, DDX5, PFN1 in immune cells, and IRF9 and MX1 in tissue cells, were screened. Afterward, the five feature sorting lists were fed into the feature incremental selection framework, which contained two classification algorithms (decision tree [DT] and random forest [RF]), to construct optimal classifiers and generate quantitative rules. Results showed that random forest classifiers could provide relative higher performance than decision tree classifiers, whereas the DT classifiers provided quantitative rules that indicated special gene expression levels under different vaccine strategies. These findings may help us to develop better protective vaccination programs and new vaccines.

Identification of Type 2 Diabetes Biomarkers From Mixed Single-Cell Sequencing Data With Feature Selection Methods.

Diabetes is the most common disease and a major threat to human health. Type 2 diabetes (T2D) makes up about 90% of all cases. With the development of high-throughput sequencing technologies, more and more fundamental pathogenesis of T2D at genetic and transcriptomic levels has been revealed. The recent single-cell sequencing can further reveal the cellular heterogenicity of complex diseases in an unprecedented way. With the expectation on the molecular essence of T2D across multiple cell types, we investigated the expression profiling of more than 1,600 single cells (949 cells from T2D patients and 651 cells from normal controls) and identified the differential expression profiling and characteristics at the transcriptomics level that can distinguish such two groups of cells at the single-cell level. The expression profile was analyzed by several machine learning algorithms, including Monte Carlo feature selection, support vector machine, and repeated incremental pruning to produce error reduction (RIPPER). On one hand, some T2D-associated genes (MTND4P24, MTND2P28, and LOC100128906) were discovered. On the other hand, we revealed novel potential pathogenic mechanisms in a rule manner. They are induced by newly recognized genes and neglected by traditional bulk sequencing techniques. Particularly, the newly identified T2D genes were shown to follow specific quantitative rules with diabetes prediction potentials, and such rules further indicated several potential functional crosstalks involved in T2D.