Advances in research on spexin-mediated regulation of reproductive function in vertebrates.

Spexin (SPX, NPQ) is a 14-amino acid neuroactive peptide identified using bioinformatics. This amino acid sequence of the mature spexin peptide has been highly conserved during species evolution and is widely distributed in the central nervous system and peripheral tissues and organs. Therefore, spexin may play a role in various biological functions. Spexin, the cognate ligand for GALR2/3, acting as a neuromodulator or endocrine signaling factor, can inhibit reproductive performance. However, controversies and gaps in knowledge persist regarding spexin-mediated regulation of animal reproductive functions. This review focuses on the hypothalamic-pituitary-gonadal axis and provides a comprehensive overview of the impact of spexin on reproduction. Through this review, we aim to enhance understanding and obtain in-depth insights into the regulation of reproduction by spexin peptides, thereby providing a scientific basis for future investigations into the molecular mechanisms underlying the influence of spexin on reproductive function. Such investigations hold potential benefits for optimizing farming practices in livestock, poultry, and fish industries.

Second near-infrared fluorescent Metal-Organic framework sensors for in vivo extracellular adenosine triphosphate monitoring.

Plant nanobionic sensors enable real-time monitoring of signaling molecules in plants by interfacing them with specifically designed nanoprobes, which have been acknowledged as species-independent analytical tools. In this study, we developed a plant nanobionic sensor for in vivo detection of extracellular adenosine triphosphate (eATP) in living plants by designing a novel second near-infrared (NIR-II) fluorescent metal-organic framework (MOF) nanoprobe. The NIR-II fluorescent nanoprobe (IR-1061 micelle@ZIF-90) with a sandwich structure was synthesized by successive encapsulation of the hydrophobic NIR-II dye IR-1061 with the amphipathic polymer DSPE-mPEG 2000 and MOF ZIF-90. Interestingly, coating ZIF-90 around IR-1061 micelles increased the NIR-II fluorescence 16.6-fold. Utilizing the ultrahigh NIR-II fluorescent emission of the designed nanoprobes and specific recognition of ZIF-90 to ATP, the nanoprobes were applied to spatial and temporal monitoring eATP in model and non-model plants under environmental stress.

Dietary bile acids supplementation improves the growth performance and alleviates fatty liver in broilers fed a high-fat diet via improving the gut microbiota.

This experiment aims to evaluate the effect of bile acids (BAs) in alleviating fatty liver disease induced by a high-fat diet (HFD) in broilers, and the modulation of the gut microbiota involved in this process. A total of 192 one-day-old Arbor Acres (AA) commercial male broilers were randomly divided into 4 groups and treated with the following diet: a basal-fat diet (BFD), a basal-fat diet plus bile acids (BFD + BAs), an HFD, and a high-fat diet plus bile acids (HFD + BAs). Bile acids were supplemented at the early growth stage (3-7 d), middle stage (17-21 d), and late stage (31-35 d). Results showed that BAs treatment had a significant effect on body weight on 14 d and 35 d, and increased the breast muscle weight and its index, but decreased the liver weight and abdominal fat weight on 35 d (P < 0.05). The supplementation of BAs significantly improved the serum lipid profile and decreased the level of triglycerides (TG), total cholesterol (TCHO), and nonesterified fatty acids (NEFA) on 35 d (P < 0.05). Dietary BAs supplementation significantly alleviated the hepatic TG deposition induced by HFD (P < 0.05), which was accompanied by upregulation of peroxisome proliferator-activated receptor gamma (PPARγ) and lipoprotein lipase (LPL) gene expression (P < 0.05). Moreover, the expression levels of hepatic gene adipose triglyceride lipase (ATGL), peroxisome proliferator-activated receptor α (PPARα), and apolipoprotein B (APOB) were greatly increased by BAs treatment. The analysis of 16S rRNA sequencing showed that the microbial diversity of the cecal digesta was increased by BAs in broilers with elevated abundances of Firmicutes, Lactobacillus, Anaerostipes, Sellimonas, and CHKCI002 and decreased abundances of Barnesiella and Akkermansia genus (P < 0.05). Hepatic TG content was positively correlated with the abundance of Oscillospiraceae, but it was negatively correlated with the abundance of Lactobacillus in cecal digesta (P < 0.05). These results indicate that dietary BAs can improve growth performance and alleviate fatty liver disease induced by an HFD via modulating gut microbiota in broilers.

Comparison of the Effects of Feeding Compound Probiotics and Antibiotics on Growth Performance, Gut Microbiota, and Small Intestine Morphology in Yellow-Feather Broilers.

This study was devoted to the comparison of the probiotic effect of compound probiotics to antibiotics as a feed additive for chicken. Two hundred and seventy newly hatched yellow-feather broilers were randomly divided into three groups: the control group (Con), probiotics (Pb), and antibiotics group (Ab). The Pb group received compound probiotics (Bifidobacterium, Lactobacillus acidophilus, Streptococcus faecalis, and yeast) via drinking water for 24 days. The Ab group received antibiotics (zinc bacitracin and colistin sulfate) in their diet for 24 days. All broilers were slaughtered on day 42. Compared with the Con group, the body weight was significantly increased on days 13, 28, and 42 in the Pb group (p < 0.05), and markedly increased on day 28 in the Ab group (p < 0.05). Compared with the Ab group, the body weight of the broilers in the Pb group increased significantly on day 13 (p < 0.05). Compared to the Con and Pb groups, the antibiotics treatment reduced the feed intake (p < 0.05), but there was no significant difference in the feed conversion ratio between the Ab and Pb groups (p > 0.05). The feed conversion ratio of the broilers treated with antibiotics or probiotics significantly decreased compared to the Con group (p < 0.05). The depth of duodenum, jejunum, and ileum crypts in the Pb group decreased significantly compared to the Con and Ab group (p < 0.05). The ratio of the villi length to crypt depth of duodenum, jejunum, and ileum epithelium was significantly increased in the Pb group compared to the Con group (p < 0.05). The genera Bacteroides and Barnesiella were the most significantly enriched bacteria in the Ab and Pb groups, respectively (p < 0.05). The expression of the genes related to antibiotic resistance was significantly decreased in the Pb group compared to the Ab group (p < 0.05). Although both compound probiotics and antibiotics can improve growth performance, antibiotics increased the abundance of harmful bacteria and drug-resistant genes, while probiotics increased Barnesiella abundance, which is related to a decrease in the drug-resistant gene expression. Moreover, the probiotics treatment improved small intestinal morphology and fecal emissions, while antibiotics have no significant effect on these indicators, indicating a bright future for probiotics as an alternative to feed antibiotics in the yellow-feather broiler industry.

Transcriptome Profiling of Goose Ovarian Follicle Granulosa Cells Reveals Key Regulatory Networks for Follicle Selection.

The selection of follicles determines the reproductive performance of birds, but the process of follicle selection in geese is still elusive. This study focuses on Yangzhou geese during the egg-laying period and divides the follicular development process into three stages: small follicle development, follicle selection, and follicle maturation. Transcriptome sequencing was performed on granulosa cells from large white follicles, small yellow follicles, and F5 and F4 follicles. In addition, we selected the transcripts that remained unchanged during the development and maturation of small follicles but significantly changed during the follicular selection stage as the transcript collection that plays an important role in the follicular selection process. Then, we performed functional analysis on these transcripts and constructed a ceRNA network. The results showed that during the follicular selection stage, the number of differentially expressed mRNAs, miRNAs, and lncRNAs was the highest. In addition, miR-222-3p, miR-2954-3p, miR-126-5p, miR-2478, and miR-425-5p are potential key core regulatory molecules in the selection stage of goose follicles. These results can provide a reference for a better understanding of the basic mechanisms of the goose follicle selection process and potential targets for the precise regulation of goose egg production performance.

Self-Illuminating NIR-II Chemiluminescence Nanosensor for In Vivo Tracking H2 O2 Fluctuation.

Chemiluminescence (CL) imaging, as an excitation-free technique, exhibits a markedly improved signal-to-noise ratio (SNR) owing to the absence of an excitation light source and autofluorescence interference. However, conventional chemiluminescence imaging generally focuses on the visible and first near-infrared (NIR-I) regions, which hinders high-performance biological imaging due to strong tissue scattering and absorption. To address the issue, self-luminescent NIR-II CL nanoprobes with a second near-infrared (NIR-II) luminescence in the presence of hydrogen peroxide are rationally designed. A cascade energy transfer, including chemiluminescence resonance energy transfer (CRET) from the chemiluminescent substrate to NIR-I organic molecules and Förster resonance energy transfer (FRET) from NIR-I organic molecules to NIR-II organic molecules, occurs in the nanoprobes, contributing to NIR-II light with great efficiency and good tissue penetration depth. Based on excellent selectivity, high sensitivity to hydrogen peroxide, and long-lasting luminescence performance, the NIR-II CL nanoprobes are applied to detect inflammation in mice, showing a 7.4-fold enhancement in SNR compared with that of fluorescence.

Dietary γ-Aminobutyric Acid Supplementation Inhibits High-Fat Diet-Induced Hepatic Steatosis via Modulating Gut Microbiota in Broilers.

The present study aims to investigate the effect of γ-aminobutyric acid (GABA) on liver lipid metabolism and on AA broilers. Broilers were divided into three groups and fed with low-fat diets, high-fat diets, and high-fat diets supplemented with GABA. Results showed that GABA supplementation decreased the level of triglyceride (TG) in the serum and liver of broilers fed high-fat diets, accompanied by up-regulated mRNA expression of genes related to lipolysis and ß-oxidation in the liver (p < 0.05). Furthermore, GABA supplementation increased liver antioxidant capacity, accompanied by up-regulated mRNA expression of antioxidant genes (p < 0.05). 16S rRNA gene sequencing showed that GABA improved high-fat diet-induced dysbiosis of gut microbiota, increased the relative abundance of Bacteroidetes phylum and Barnesiella genus, and decreased the relative abundance of Firmicutes phylum and Ruminococcus_torques_group and Romboutsia genus (p < 0.05). Moreover, GABA supplementation promoted the production of propionic acid and butyric acid in cecal contents. Correlation analysis further suggested the ratio of Firmicutes/Bacteroidetes negatively correlated with hepatic TG content, and positively correlated with cecal short chain fatty acids content (r > 0.6, p < 0.01). Together, these data suggest that GABA supplementation can inhibit hepatic TG deposition and steatosis via regulating gut microbiota in broilers.

Shear Exfoliated Metal-Organic Framework Nanosheet-Enabled Flexible Sensor for Real-Time Monitoring of Superoxide Anion.

Recently, two-dimensional metal-organic framework (2D MOF) nanosheets have drawn a lot of attention on account of their various advantages, like ultrathin thickness, ultralarge specific surface area, abundant accessible active sites, favorable solution dispersion properties, and ease of designability. However, until now, it is still difficult to produce 2D MOF nanosheets in large scale, which hinders the practical applications of 2D MOF nanosheets. Here, for the first time, we introduced a novel shear exfoliation method to prepare scalable 2D MOF nanosheets by using a commercial blender. As a proof of concept, we used two kinds of layer-structured MOFs (ELM-12, Cu(bpy)2(OTf)2, bpy = 4,4-bipyridine, OTf = trifluoromethanesulfonate and Zn2(bim)4, bim = benzimidazole) as samples to prepare MOF nanosheets. The thickness of the two kinds of MOF nanosheets obtained is 3-5 nm. Notably, the exfoliated MOF nanosheet (ELM-12) shows improved electrochemical catalytic activity compared with its bulk counterpart. Based on this, an ELM-12 nanosheet-based flexible sensor was developed for detecting superoxide anions (O2•-) released from cancer cells. The fabricated flexible sensor displays excellent sensitivity, selectivity, flexibility, stability, and reproducibility.

Laser-induced noble metal nanoparticle-graphene composites enabled flexible biosensor for pathogen detection.

Noble metal nanoparticle-3D graphene hybrid nanocomposites possess the advantage of nanoparticles and graphene, which have attracted extensive interest. Here we developed a one-step laser induction method to prepare various noble metal nanoparticle-3D graphene nanocomposites. The nanocomposites were converted from polyimide film coated with the corresponding metal precursor-chitosan hydrogel ink. These nanoparticles including gold nanoparticles (AuNPs), silver nanoparticles (AgNPs), and platinum nanoparticles (PtNPs), were evenly distributed on the surface of porous 3D graphene. Furthermore, we prepared an AuNPs-3D graphene interdigitated array electrode using the one-step laser induction method, which was used to fabricate a flexible impedimetric immunosensor for the detection of Escherichia coli O157:H7. The immunosensor shows excellent performance including low detection limit, high selectivity, and great flexibility.

Candidate gene prioritization for non-communicable diseases based on functional information: Case studies.

Candidate gene prioritization for complex non-communicable diseases is essential to understanding the mechanism and developing better means for diagnosing and treating these diseases. Many methods have been developed to prioritize candidate genes in protein-protein interaction (PPI) networks. Integrating functional information/similarity into disease-related PPI networks could improve the performance of prioritization. In this study, a candidate gene prioritization method was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease PPI networks with weights for nodes and edges based on functional information. Here, three types of non-communicable diseases with pathobiological similarity, Type 2 diabetes (T2D), coronary artery disease (CAD) and dilated cardiomyopathy (DCM), were used as case studies. Literature review and pathway enrichment analysis of top-ranked genes demonstrated the effectiveness of our method. Better performance was achieved after comparing our method with other existing methods. Pathobiological similarity among these three diseases was further investigated for common top-ranked genes to reveal their pathogenesis.

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.

Chronic obstructive pulmonary disease candidate gene prioritization based on metabolic networks and functional information.

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, in which metabolic disturbances played important roles. In this paper, functional information was integrated into a COPD-related metabolic network to assess similarity between genes. Then a gene prioritization method was applied to the COPD-related metabolic network to prioritize COPD candidate genes. The gene prioritization method was superior to ToppGene and ToppNet in both literature validation and functional enrichment analysis. Top-ranked genes prioritized from the metabolic perspective with functional information could promote the better understanding about the molecular mechanism of this disease. Top 100 genes might be potential markers for diagnostic and effective therapies.

A unique quantitative method of acid value of edible oils and studying the impact of heating on edible oils by UV-Vis spectrometry.

UV-Vis spectroscopy coupled with chemometrics was used effectively to study the impact of heating on edible oils (corn oil, sunflower oil, rapeseed oil, peanut oil, soybean oil and sesame oil) and determine their acid value. Analysis of their first derivative spectra showed that the peak at 370 nm was a common indicator of the heated oils. Partial least squares regression (PLS) and principle component regression (PCR) were applied to building individual quantitative models of acid value for each kind of oil, respectively. The PLS models had a better performance than PCR models, with determination coefficients (R(2)) of 0.9904-0.9977 and root mean square errors (RMSE) of 0.0230-0.0794 for the prediction sets of each kind of oil, respectively. An integrate quantitative model built by support vector regression for all the six kinds of oils was also developed and gave a satisfactory prediction with a R(2) of 0.9932 and a RMSE of 0.0656.

Qualitative and simultaneous quantitative analysis of cimetidine polymorphs by ultraviolet-visible and shortwave near-infrared diffuse reflectance spectroscopy and multivariate calibration models.

The object of the present study was to investigate the feasibility of applying ultraviolet-visible and shortwave near-infrared diffuse reflectance spectroscopy (UV-vis-SWNIR DRS) coupled with chemometrics in qualitative and simultaneous quantitative analysis of drug polymorphs, using cimetidine as a model drug. Three polymorphic forms (A, B and D) and a mixed crystal (M1) of cimetidine, obtained by preparation under different crystallization conditions, were characterized by microscopy, X-ray powder diffraction (XRPD) and infrared spectroscopy (IR). The discriminant models of four forms (A, B, D and M1) were established by discriminant partial least squares (PLS-DA) using different pretreated spectra. The R and RMSEP of samples in the prediction set by discriminant model with original spectra were 0.9959 and 0.1004. Among the quantitative models of binary mixtures (A and D) established by partial least squares (PLS) and least squares-support vector machine (LS-SVM) with different pretreated spectra, the LS-SVM models based on original and MSC spectra had better prediction effect with a R of 1.0000 and a RMSEP of 0.0134 for form A, and a R of 1.0000 and a RMSEP of 0.0024 for form D. For ternary mixtures, the established PLS quantitative models based on normalized spectra had relatively better prediction effect for forms A, B and D with R of 0.9901, 0.9820 and 0.9794 and RMSEP of 0.0471, 0.0529 and 0.0594, respectively. This research indicated that UV-vis-SWNIR DRS can be used as a simple, rapid, nondestructive qualitative and quantitative method for the analysis of drug polymorphs.

Injection-ultrasound-assisted emulsification microextraction based on using low-density organic solvent followed by high-performance liquid chromatography for the determination of pyrethroids in water samples.

A highly efficient, simple and rapid method, injection-ultrasound-assisted emulsification microextraction based on using low-density organic solvents followed by high-performance liquid chromatography-ultraviolet detection, was developed for the determination of trace level pyrethroids in water samples. Various parameters influencing the extraction efficiency, such as type of extractant, extractant volume, ultrasonic time, centrifugation time and salt addition, were studied and optimized by two methods: the single factor experiment and the Box-Behnken design. Under the optimum conditions, great enrichment factors (678-713) and good recoveries (92.48-97.31%) were obtained for the extraction and analysis of artificial water samples. Linearity of the method for three pyrethroids was in the range of 0.11-218 µg L(-1) for fenpropathrin, and 0.07-136 µg L(-1) for fenvalerate and permethrin, respectively, with correlation coefficients ranging from 0.9994 to 0.9999. The limits of detection for the target analytes were 12.13 to 20.16 ng L(-1), and the limits of quantification were 40.43 to 67.19 ng L(-1). The recoveries of the three pyrethroids from actual water samples at three spiked levels were in the range of 83.25 to 103.3% with relative standard deviation RSDs less than 7.40%.