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BackgroundWheat germ is known for its antioxidant, anti-inflammatory, and disease resistance properties in animals. However, its effect on the gut of Sichuan white geese remains unclear.MethodIn this study, thirty 250-day-old geese were divided into three equal groups, the control group, LWG group (21.8% wheat germ) and HWG group (43.6% wheat germ), the experiment lasted 12 weeks. We assessed various aspects of geese intestinal health, including barrier function, digestibility, antioxidant capacity, immunity, microbiota, and metabolism.ResultsThe study revealed a significant increase in villus height (VH), villus height-to-crypt depth (VH/CD) ratio, amylase, and lipase activities in the duodenum and ileum, increased putrescine levels in the duodenum and jejunum, as well as spermidine levels in the jejunum (P < 0.05). LWG increased the total antioxidant capacity (T-AOC) in the duodenum, while decreasing levels of intestinal malondialdehyde (MDA), serum lipopolysaccharide (LPS), interleukin-6 (IL-6), and diamine oxidase (DAO) activity (P < 0.05). Furthermore, LWG increased the relative abundance of Oscillospiraceae_unclassified, Ligilactobacillus, and Roseburia, as well as increased levels of acetic acid, butyric acid, and valeric acid, while decreasing the relative abundance of Subdoligranulum, Flavonifractor, and Klebsiella. Additionally, we observed 17 up-regulated genes and 25 down-regulated genes in the jejunum, which are associated with the cell cycle and immunity. These genes play roles in pathways such as the p53 signaling pathway, cell cycle regulation, and pathways associated with immune modulation. On the other hand, HWG increased intestinal VH and spermidine levels, as well as amylase and lipase activities in the duodenum (P < 0.05). It also elevated ileal T-AOC and sIgA levels (P < 0.05), while reducing intestinal MDA content, serum LPS levels, DAO activity, and propionic acid in cecum contents (P < 0.05). Moreover, HWG increased the relative abundance of Ligilactobacillus, Oscillospiraceae_unclassified, and Roseburia (P < 0.05).ConclusionOverall, wheat germ diets, particularly the LWG diet demonstrated the ability to enhance antioxidant capacity, digestibility, immunity, and barrier properties of the intestinal tract, while modulating the gut microbiota and metabolism. Therefore, wheat germ diets hold promise in improving intestinal health by preserving barrier function and regulating flora structure.

BackgroundGestational diabetes mellitus (GDM) significantly affects the fetal metabolic environment, elevating risks of neonatal hypoglycemia and macrosomia. Metabolomics offers promising avenues for early prediction and diagnosis of GDM and associated adverse offspring outcomes.MethodsThis study analyzed serum samples from pregnant women diagnosed with GDM at 24 to 28 weeks of gestation using untargeted metabolomics. We monitored the health outcomes of their offspring to explore the correlation between initial serum metabolite profiles and subsequent health outcomes, to uncover the predictive markers for hypoglycemia and macrosomia in these offspring.ResultsOut of 200 participants, 154 had normal newborns, 33 had offspring with hypoglycemia, and 19 had offspring with macrosomia. From 448 identified metabolites, 66 showed significant differences in cases of hypoglycemia, and 45 in macrosomia. A panel of serum metabolite biomarkers achieved Area Under the Curve (AUC) values of 0.8712 for predicting hypoglycemia and 0.9434 for macrosomia.ConclusionThe study delineated metabolic disruptions in GDM during 24–28 weeks of gestation and pinpointed biomarkers capable of forecasting adverse neonatal outcomes. These findings could inform GDM management strategies and minimize the incidence of such outcomes.

In this study, we used chitosan/sodium alginate hydrogel as a carrier to prepare berberine sustained-release capsule materials that can inhibit algae for a long time and safely. The preparation conditions of the material were optimized by the response surface method, and the optimized capsule material was characterized and the sustained release characteristics were analyzed to study the change of the algae inhibition effect of the material within 30 days. The results showed that the optimum preparation parameters of the material were 0.54% chitosan content, 2.46% sodium alginate content and 1.09% anhydrous calcium chloride content by response surface optimization design, which was consistent with the parameters set by each factor at the central point. The algae inhibition rate of the material under this preparation condition was 93.75 ± 1.01%, which was similar to the predicted value. The release characteristics analysis showed that the material continuously released up to 90% of berberine within 24 days, and its release characteristics were sustained release after burst release, with good sustained release effect. The results of material characterization showed that chitosan/sodium alginate hydrogel could effectively load berberine and was beneficial to the loading and release of berberine. The results of algae inhibition experiments showed that low concentration materials could control the outbreak of cyanobacterial blooms in a short time, while under high concentration conditions, the materials could inhibit Microcystis aeruginosa efficiently and for a long time.

Mycotoxins are toxic metabolites produced by fungi during their growth and they are important detrimental factors endangering the quality and safety of agricultural products. Essential oils are natural inhibitors of fungal growth and accumulation of mycotoxins, but characteristics of strong volatility, poor stability and low water solubility limit their applications. In recent years, the development and utilization of nanoformulations can solve the above drawbacks of essential oils, and improve their bioavailability. This paper summarizes that essential oil can reduce the contamination level of mycotoxins in agricultural products by inhibiting the production of mycotoxins and degrading mycotoxins, overviews the inhibitory mechanism of essential oil against the growth of fungi and production of mycotoxins, reviews the research status of the prevention and control of mycotoxins in agricultural products using essential oils and their nanoformulations, and discusses the existing problems, in order to provide useful references for the further development and utilization of essential oils for the prevention and control of mycotoxins.

IntroductionIntestinal health is very important to the health of livestock and poultry, and is even a major determining factor in the performance of livestock and poultry production. Spermidine is a type of polyamine that is commonly found in a variety of foods, and can resist oxidative stress, promote cell proliferation and regulate intestinal flora.MethodsIn this study, we explored the effects of spermidine on intestinal health under physiological states or oxidative stress conditions by irrigation with spermidine and intraperitoneal injection of 3-Nitropropionic acid (3-NPA) in Sichuan white goose.Results and discussionOur results showed that spermidine could increase the ratio of intestinal villus to crypt and improve intestinal morphology. In addition, spermidine can also reduce malondialdehyde (MDA) accumulation caused by 3-NPA by increasing superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPX) enzyme activity, thus alleviating intestinal damage. Furthermore, spermidine can regulate intestinal digestive enzyme activities and affect intestinal digestion and absorption ability. Spermidine can also promote an increase in intestinal microbial diversity and abundance and alleviate the change of microflora structure caused by 3-NPA. In conclusion, spermidine promotes the production of beneficial intestinal metabolites such as Wikstromol, Alpha-bisabolol and AS 1–5, thus improving the level of intestinal health. Taken together, these results indicate that spermidine can improve intestinal health by improving intestinal morphology, increasing antioxidant capacity and regulating intestinal flora structure.

ABSTRACT: Spermidine have been reported a role in antioxidative, antiaging, and antiinflammatory. Oxidative stress causes granulosa cell (GC) apoptosis, follicular atresia, and impairs poultry reproductive functions. Studies have found that autophagy is the protective mechanism against antioxidant stress and apoptosis in cells. However, the relationship between spermidine-induced autophagy, oxidative stress, and apoptosis in goose GCs remains unclear. In this study, we investigated the autophagy mechanism to mediate spermidine effects on the alleviation of oxidative stress and apoptosis in goose GCs. Follicular GCs were treated with spermidine combination with 3-Nitropropanoic acid (3-NPA), rapamycin (RAPA), and chloroquine (CQ) or with hydrogen peroxide, RAPA, and CQ. Spermidine upregulated the ratio of LC3-II/I, inhibited the accumulation of p62 protein, and induced autophagy. 3-NPA treatment significantly increased ROS production, MDA content, SOD activity, cleaved CASPASE-3 protein expression, and decreased BCL-2 protein expression in follicular GCs. Spermidine inhibited oxidative stress and apoptosis induced by 3-NPA. In addition, hydrogen peroxide-induced oxidative stress was inhibited by spermidine. However, the inhibitory effect of spermidine was eliminated under chloroquine. Our results demonstrated that spermidine relieved oxidative stress and apoptosis of GCs by inducing autophagy, indicating that spermidine has a great potential to maintain proteostasis and sustain granulosa cell viability in geese.

The use of radiotherapy for hypopharyngeal cancer (HC) treatment is increasing, and it is currently the primary treatment option for this cancer. However, radioresistance occurs in a proportion of patients. Here, we found that radiation increased proteasomal gene expression and that proteasome assembly was dependent on the induction of transcription factor NRF1 in HC. Through screening assays, we identified a mechanism by which proteasome-mediated degradation of DEP domain-containing mTOR-interacting protein (DEPTOR) contributes to the elevation of mTORC1 signaling after radiation. Therefore, after treatment with proteasome inhibitors (PIs), stabilization of DEPTOR inhibited mTORC1 signaling elevated by radiation and ultimately sensitized HC to radiotherapy. Mechanically, PIs not only interrupted the deubiquitination and degradation of DEPTOR but also suppressed the ubiquitination of DEPTOR mediated by β-TrCP. Clinically, the high levels of DEPTOR in HC cells were associated with sensitivity to radiotherapy and favorable prognosis. Stabilizing DEPTOR through targeting proteasome-mediated degradation is a potential strategy for sensitizing HC to radiotherapy.

Abstract Background The proliferation ability and autophagy level of pulmonary artery endothelial cells (PAECs) play an important role in promoting the development of pulmonary artery hypertension (PAH), and there is still no effective treatment for PAH. Farnesyl diphosphate synthase (FDPS) is a key enzyme in the mevalonate pathway. The intermediate metabolites of this pathway are closely related to the activity of autophagy-associated small G proteins, including Ras-related C3 botulinum toxin substrate 1 (Rac1). Studies have shown that the mevalonate pathway affects the activation levels of different small G proteins, autophagy signaling pathways, vascular endothelial function, and so on. However, the exact relationship between them is still unclear in PAH. Method In vitro, western blotting and mRFP-GFP-LC3 puncta formation assays were used to observe the expression of FDPS and the level of autophagy in PAECs treated with monocrotaline pyrrole (MCTP). In addition, cell proliferation and migration assays were used to assess the effect of FDPS on endothelial function, and Rac1 activity assays were used to evaluate the effect of Rac1 activation on PAEC autophagy via the PI3K/AKT/mTOR signaling pathway. In vivo, the right heart catheterization method, hematoxylin and eosin (H&E) staining and western blotting were used to determine the effect of FDPS on PAEC autophagy and monocrotaline (MCT)-induced PAH. Results We show that the expression of FDPS is increased in the PAH module in vitro and in vivo, concomitant with the induction of autophagy and the activation of Rac1. Our data demonstrate that inhibition of FDPS ameliorates endothelial function and decreases MCT-induced autophagy levels. Mechanistically, we found that FDPS promotes autophagy, Rac1 activity and endothelial disfunction through the PI3K/AKT/mTOR signaling pathway. Conclusion Our study suggests that FDPS contributes to active small G protein-induced autophagy during MCT-induced PAH, which may serve as a potential therapeutic target against PAH.

Information regarding relationships between forage yield and soil enzymes of legume–grass mixtures under nitrogen (N) fertilization can guide the decision-making during sustainable forage production. The objective was to evaluate the responses of forage yield, nutritional quality, soil nutrients, and soil enzyme activities of different cropping systems under various N inputs. Alfalfa (Medicago sativa L.), white clover (Trifolium repens L.), orchardgrass (Dactylis glomerata L.), and tall fescue (Festuca arundinacea Schreb.) were grown in monocultures and mixtures (A1: alfalfa, orchardgrass, and tall fescue; A2: alfalfa, white clover, orchardgrass, and tall fescue) under three N inputs (N1: 150 kg ha−1; N2, 300 kg ha−1; and N3: 450 kg ha−1) in a split plot arrangement. The results highlight that A1 mixture under N2 input had a greater forage yield of 13.88 t ha−1 year−1 than the other N inputs, whereas A2 mixture under N3 input had a greater forage of 14.39 t ha−1 year−1 than N1 input, but it was not substantially greater than N2 input (13.80 t ha−1 year−1). The crude protein (CP) content of grass monocultures and mixtures significantly (P < 0.05) increased with an increase in the rate of N input, and A1 and A2 mixtures under N3 input had a greater CP content of 18.91% and 18.94% dry matter, respectively, than those of grass monocultures under various N inputs. The A1 mixture under N2 and N3 inputs had a substantially greater (P < 0.05) ammonium N content of 16.01 and 16.75 mg kg−1, respectively, whereas A2 mixture under N3 had a greater nitrate N content of 4.20 mg kg−1 than the other cropping systems under various N inputs. The A1 and A2 mixtures under N2 input had a substantial higher (P < 0.05) urease enzyme activity of 0.39 and 0.39 mg g−1 24 h−1 and hydroxylamine oxidoreductase enzyme activity of 0.45 and 0.46 mg g−1 5 h−1, respectively, than the other cropping systems under various N inputs. Taken together, growing legume–grass mixtures under N2 input is cost-effective, sustainable, and eco-friendly, which provide greater forage yield and improved nutritional quality by the better utilization of resources.

ABSTRACT: Oxidative stress is the major culprits responsible for ovarian dysfunction by damaging granulosa cells (GCs). Ferritin heavy chain (FHC) may participate in the regulation of ovarian function by mediating GCs apoptosis. However, the specific regulatory function of FHC in follicular GCs remains unclear. Here, 3-nitropropionic acid (3-NPA) was utilized to establish an oxidative stress model of follicular GCs of Sichuan white geese. To explore the regulatory effects of FHC on oxidative stress and apoptosis of primary GCs in geese by interfering or overexpressing FHC gene. After transfection of siRNA-FHC to GCs for 60 h, the expressions of FHC gene and protein decreased significantly (P < 0.05). After FHC overexpression for 72 h, the expressions of FHC mRNA and protein upregulated considerably (P < 0.05). The activity of GCs was impaired after interfering with FHC and 3-NPA coincubated (P < 0.05). When overexpression of FHC combined with 3-NPA treatment, the activity of GCs was remarkably enhanced (P < 0.05). After interference FHC and 3-NPA treatment, NF-κB and NRF2 gene expression decreased (P < 0.05), the intracellular reactive oxygen species (ROS) level increased greatly (P < 0.05), BCL-2 expression reduced, BAX/BCL-2 ratio intensified (P < 0.05), the mitochondrial membrane potential decreased notably (P < 0.05), and the apoptosis rate of GCs aggravated (P < 0.05). While overexpression of FHC combined with 3-NPA treatment could promote BCL-2 protein expression and reduce BAX/BCL-2 ratio, indicating that FHC regulated the mitochondrial membrane potential and apoptosis of GCs by mediating the expression of BCL-2. Taken together, our research manifested that FHC alleviated the inhibitory effect of 3-NPA on the activity of GCs. FHC knockdown could suppress the expression of NRF2 and NF-κB genes, reduce BCL-2 expression and augment BAX/BCL-2 ratio, contributing to the accumulation of ROS and jeopardizing mitochondrial membrane potential, as well as exacerbating GCs apoptosis.

Abstract Background This review was conducted to investigate the association between serum vitamin B12 levels as well as folic acid/vitamin B12 during pregnancy and the risk of gestational diabetes mellitus (GDM). Methods A comprehensive search of electronic databases (Embase, PubMed, and Web of Science) was performed. The odds ratios (ORs) with 95% confidence intervals (CIs) of GDM risk were summarized using a random effects model. We also performed subgroup analyses to explore the source of heterogeneity. Results A total of 10 studies, including 10,595 pregnant women were assessed. Women with vitamin B12 deficiency were at higher risk for developing GDM when compared with those who were vitamin B12 sufficient (OR, 1.46; 95% CI 1.21–1.79; I2: 59.0%). Subgroup analysis indicated that this association might differ based on sample size and geographical distribution. Elevated vitamin B12 levels may decrease the risk of GDM by 23%. The role of excess folic acid and low vitamin B12 levels in the occurrence of GDM is also controversial. Conclusion In summary, vitamin B12 deficiency is associated with increased risk of GDM, it is necessary to pay more attention to the balance of vitamin B12 and folic acid. However, more in-depth studies across multiple populations are needed to verify these results.

IntroductionEndoplasmic reticulum stress (ERS) has sizeable affect on cancer proliferation, metastasis, immunotherapy and chemoradiotherapy resistance. However, the effect of ERS on the biochemical recurrence (BCR) of prostate cancer patients remains elusive. Here, we generated an ERS-related genes risk signature to evaluate the physiological function of ERS in PCa with BCR.MethodsWe collected the ERS-related genes from the GeneCards. The edgeR package was used to screen the differential ERS-related genes in PCa from TCGA datasets. ERS-related gene risk signature was then established using LASSO and multivariate Cox regression models and validated by GEO data sets. Nomogram was developed to assess BCR-free survival possibility. Meanwhile, the correlations between ERS-related signature, gene mutations, drug sensitivity and tumor microenvironment were also investigated. ResultsWe obtained an ERS risk signature consisting of five genes (AFP, COL10A1, DNAJB1, EGF and PTGS2). Kaplan Meier survival analysis and ROC Curve analysis indicated that the high risk score of ERS-related gene signature was associated with poor BCR-free prognosis in PCa patients. Besides, immune cell infiltration and immune checkpoint expression levels differed between high- and low-risk scoring subgroups. Moreover, drug sensitivity analyzed indicated that high-risk score group may be involved in apoptosis pathway. DiscussionThis study comprehensively analyzed the characteristics of ERS related genes in PCa, and created a five-gene signature, which could effectively predict the BCR time of PCa patients. Targeting ERS related genes and pathways may provide potential guidance for the treatment of PCa.

Abstract We previously reported that ibandronate (IBAN) could improve endothelial function in spontaneously hypertensive rats. However, the mechanism by which IBAN improves endothelial function is unclear. The IBAN-induced autophagic process in vitro experiments were determined by detection of LC3, Beclin1, and P62 protein levels via western blotting. The autophagy flux was detected by confocal microscopy and transmission electron microscopy. For in vivo experiments, spontaneously hypertensive rats were orally administered with IBAN. Utilizing angiotensin II (Ang II) to stimulate the human umbilical vein endothelial cells (HUVECs) and human pulmonary microvascular endothelial cells (HPMECs) as a model of endothelial cell injury in hypertension, we found that IBAN promoted autophagy and protected cell viability in Ang II-treated-endothelial cells while these effects could be reversed by autophagy inhibitor. In terms of mechanism, IBAN treatment decreased the levels of Rac1 and mammalian target of rapamycin (mTOR) pathway. Activating either Rac1 or mTOR could reverse IBAN-induced autophagy. Furthermore, the in vivo experiments also indicated that IBAN promotes autophagy by downregulating Rac1-mTOR. Taken together, our results firstly revealed that IBAN enhances autophagy via inhibiting Rac1-mTOR signaling pathway, and thus alleviates Ang II-induced injury in endothelial cells.

Combined treatments were designed based on iron-carbon micro-electrolysis treatment (ICME), physical adsorption (PA) with zeolite (Z) or vermiculite (V) and microalgae cultivation (MC, Chlorella vulgaris) for removing pollutants from swine wastewater (SW): ICME + MC (IM), ICME + Z + MC (IZM) and ICME + V + MC (IVM). Results showed that the minimum total nitrogen (TN) of 43.66 mg L−1, NH4+-N of 1.33 mg−1 and total phosphorus (TP) of 0.14 mg−1 were obtained by IVM, while the minimum chemical oxygen demand (COD) was 105 mg−1 via IM. During the process of combined treatments, ICME contributed most to the removal of TN (84.52% by IZM), TP (97.78% by IVM and IZM) and COD (62.44% by IVM), and maximum NH4+-N removal (55.64%) was obtained by MC procedure in IM process. Vermiculite performed better than zeolite during all the combined treatments. Besides, the maximum cell dry weight (CDW, 0.74 g−1) of C. vulgaris was obtained by IM on day 13. The results provide an efficient integrated method for swine wastewater treatment. HIGHLIGHTS Process combining iron-carbon microelectrolysis, vermiculite adsorption and microalgae cultivation was the most efficient for treatment on TN, NH4+-N, TP removal.; Iron carbon micro-electrolysis combined with microalgae cultivation was the most efficient treatment for COD removal.; The maximum biomass harvest was observed on day 13 via combined iron-carbon microelectrolysis and microalgae cultivation.;

Ovarian aging and disease-related decline in fertility are challenging medical and economic issues with an increasing prevalence. Polyamines are a class of polycationic alkylamines widely distributed in mammals. They are small molecules essential for cell growth and development. Polyamines alleviate ovarian aging through various biological processes, including reproductive hormone synthesis, cell metabolism, programmed cell death, etc. However, an abnormal increase in polyamine levels can lead to ovarian damage and promote the development of ovarian disease. Therefore, polyamines have long been considered potential therapeutic targets for aging and disease, but their regulatory roles in the ovary deserve further investigation. This review discusses the mechanisms by which polyamines ameliorate human ovarian aging and disease through different biological processes, such as autophagy and oxidative stress, to develop safe and effective polyamine targeted therapy strategies for ovarian aging and the diseases.

Electroencephalography (EEG) is widely used for mental stress classification, but effective feature extraction and transfer across subjects remain challenging due to its variability. In this paper, a novel deep neural network combining convolutional neural network (CNN) and adversarial theory, named symmetric deep convolutional adversarial network (SDCAN), is proposed for stress classification based on EEG. The adversarial inference is introduced to automatically capture invariant and discriminative features from raw EEG, which aims to improve the classification accuracy and generalization ability across subjects. Experiments were conducted with 22 human subjects, where each participant’s stress was induced by the Trier Social Stress Test paradigm while EEG was collected. Stress states were then calibrated into four or five stages according to the changing trend of salivary cortisol concentration. The results show that the proposed network achieves improved accuracies of 87.62% and 81.45% on the classification of four and five stages, respectively, compared to conventional CNN methods. Euclidean space data alignment approach (EA) was applied and the improved generalization ability of EA-SDCAN across subjects was also validated via the leave-one-subject-out-cross-validation, with the accuracies of four and five stages being 60.52% and 48.17%, respectively. These findings indicate that the proposed SDCAN network is more feasible and effective for classifying the stages of mental stress based on EEG compared with other conventional methods.

Abstract. Background:. Acquired immune deficiency syndrome (AIDS)-related non-Hodgkin lymphoma (AR-NHL) is a high-risk factor for morbidity and mortality in patients with AIDS. This study aimed to determine the prognostic factors associated with overall survival (OS) and to develop a prognostic nomogram incorporating computed tomography imaging features in patients with acquired immune deficiency syndrome-related non-Hodgkin lymphoma (AR-NHL). Methods:. A total of 121 AR-NHL patients between July 2012 and November 2019 were retrospectively reviewed. Clinical and radiological independent predictors of OS were confirmed using multivariable Cox analysis. A prognostic nomogram was constructed based on the above clinical and radiological factors and then provided optimum accuracy in predicting OS. The predictive accuracy of the nomogram was determined by Harrell C-statistic. Kaplan–Meier survival analysis was used to determine median OS. The prognostic value of adjuvant therapy was evaluated in different subgroups. Results:. In the multivariate Cox regression analysis, involvement of mediastinal or hilar lymph nodes, liver, necrosis in the lesions, the treatment with chemotherapy, and the CD4 ≤100 cells/μL were independent risk factors for poor OS (all P

Video emotion recognition aims to infer human emotional states from the audio, visual, and text modalities. Previous approaches are centered around designing sophisticated fusion mechanisms, but usually ignore the fact that text contains global semantic information, while speech and face video show more fine-grained temporal dynamics of emotion. From the perspective of cognitive sciences, the process of emotion expression, either through facial expression or speech, is implicitly regulated by high-level semantics. Inspired by this fact, we propose a multimodal interaction enhanced representation learning framework for emotion recognition from face video, where a semantic enhancement module is first designed to guide the audio/visual encoder using the semantic information from text, then the multimodal bottleneck Transformer is adopted to further reinforce the audio and visual representations by modeling the cross-modal dynamic interactions between the two feature sequences. Experimental results on two benchmark emotion databases indicate the superiority of our proposed method. With the semantic enhanced audio and visual features, it outperforms the state-of-the-art models which fuse the features or decisions from the audio, visual and text modalities.

Objective To conserve and utilize the genetic resources of a traditional Chinese indigenous pig breed, Liangshan pig, we assessed the genetic diversity, genetic structure, and genetic distance in this study. Methods We used 50K single nucleotide polymorphism (SNP) chip for SNP detection of 139 individuals in the Liangshan Pig Conservation Farm. Results The genetically closed conserved population consisted of five overlapping generations, and the total effective content of the population (Ne) was 15. The whole population was divided into five boar families and one non-boar family. Among them, the effective size of each generation subpopulation continuously decreased. However, the proportion of polymorphic markers (PN) first decreased and then increased. The average genetic distance of these 139 Liangshan pigs was 0.2823±0.0259, and the average genetic distance of the 14 boars was 0.2723±0.0384. Thus, it can be deduced that the genetic distance changed from generation to generation. In the conserved population, 983 runs of homozygosity (ROH) were detected, and the majority of ROH (80%) were within 100 Mb. The inbreeding coefficient calculated based on ROH showed an average value of 0.026 for the whole population. In addition, the inbreeding coefficient of each generation subpopulation initially increased and then decreased. In the pedigree of the whole conserved population, the error rate of paternal information was more than 11.35% while the maternal information was more than 2.13%. Conclusion This molecular study of the population genetic structure of Liangshan pig showed loss of genetic diversity during the closed cross-generation reproduction process. It is necessary to improve the mating plan or introduce new outside blood to ensure long-term preservation of Liangshan pig.

Faba bean (Vicia faba L.), although a kind of high-quality and high-yield forage, could hardly achieve a great quality of silage because of its high buffering capacity. Mixed silage of faba bean with forage wheat (Triticum aestivum L.) or oat (Avena sativa L.) at different ratios could improve the fermentation quality and bacterial community. Compared with 100% faba bean silage (BS), mixed silage improved the fermentation quality, not only increased lactic acid production and reduced pH, but reduced the production of propionic acid and ammonia nitrogen. The chemical compositions of faba bean with forage wheat (BT) mixed silage were better than that of faba bean with oat (BO) mixed silage, and that of 3:7, 5:5 (fresh matter basis) mixing ratios were better than 1:9. However, the fermentation quality of BO mixed silage was better than that of BT, and that of 3:7 mixed silage (BO30) was the best overall. Analysis of the bacterial community showed that mixed silage increased the relative abundance of lactic acid bacteria after ensiling, and the relatively higher abundance of Lactobacillus showed the inhibitory effects on the proliferation of Serratia and Hafnia_Obesumbacterium, so that it alleviated their negative effects on silage and stabilized the fermentation quality. This present study exhibited that mixed silage of faba bean with forage wheat or oat not only had significant effects on chemical compositions and fermentation quality of materials but modified bacterial community so that improved the fermentation quality effectively. The mixed silage of 30% faba bean with 70% oat (BO30) is recommended in the faba bean mixed silage.

Spermidine is a naturally occurring polyamine compound that has many biological functions, such as inducing autophagy and anti-inflammatory and anti-aging effects. Spermidine can affect follicular development and thus protect ovarian function. In this study, ICR mice were fed exogenous spermidine drinking water for three months to explore the regulation of ovarian function by spermidine. The results showed that the number of atretic follicles in the ovaries of spermidine-treated mice was significantly lower than that in the control group. Antioxidant enzyme activities (SOD, CAT, T-AOC) significantly increased, and MDA levels significantly decreased. The expression of autophagy protein (Beclin 1 and microtubule-associated protein 1 light chain 3 LC3 II/I) significantly increased, and the expression of the polyubiquitin-binding protein p62/SQSTM 1 significantly decreased. Moreover, we found 424 differentially expressed proteins (DEPs) were upregulated, and 257 were downregulated using proteomic sequencing. Gene Ontology and KEGG analyses showed that these DEPs were mainly involved in lipid metabolism, oxidative metabolism and hormone production pathways. In conclusion, spermidine protects ovarian function by reducing the number of atresia follicles and regulating the level of autophagy protein, antioxidant enzyme activity, and polyamine metabolism in mice.

Although convolutional neural networks (CNNs) have made significant progress, their deployment onboard is still challenging because of their complexity and high processing cost. Tensors provide a natural and compact representation of CNN weights via suitable low-rank approximations. A novel decomposed module called DecomResnet based on Tucker decomposition was proposed to deploy a CNN object detection model on a satellite. We proposed a remote sensing image object detection model compression framework based on low-rank decomposition which consisted of four steps, namely (1) model initialization, (2) initial training, (3) decomposition of the trained model and reconstruction of the decomposed model, and (4) fine-tuning. To validate the performance of the decomposed model in our real mission, we constructed a dataset containing only two classes of objects based on the DOTA and HRSC2016. The proposed method was comprehensively evaluated on the NWPU VHR-10 dataset and the CAST-RS2 dataset created in this work. The experimental results demonstrated that the proposed method, which was based on Resnet-50, could achieve up to 4.44 times the compression ratio and 5.71 times the speedup ratio with merely a 1.9% decrease in the mAP (mean average precision) of the CAST-RS2 dataset and a 5.3% decrease the mAP of the NWPU VHR-10 dataset.

With the acceleration of urbanization and industrialization, coal cities in China are suffering from the conflicts between urban construction and coal mining (land- mining). Land-mining conflicts in coal cities have caused serious destruction of land resources and the aggravation of ecological and economic conflicts. In order to deal with the land-mining conflict, we proposed a new three-dimensional spatial analysis framework to overall plan the underground coal exploitation and aboveground land use based on economic comparative advantage and value equilibrium theory. First, estimating aboveground land resource value (LP) and underground coal resource value (MP), then comparing MP and LP by equilibrium analysis method to recognize three-dimensional development boundary. Last three boundaries derived were used to divide the study area into four parts (construction/mining-forbidden area, construction put-off/mining-limited area, construction limited/mining-put-off area and construction forbidden/mining area). Ji’ning, a typical Chinese land-mining conflict city, is taken as a case to verify the effectiveness of the new method. The results show that the amount of coal mining and urban construction area increased by about 2 times, the new method can resolve land-mining conflicts in coal cities. It can contribute to a better reference for the design of coal city regulation and control policies design.

Abstract Sparse representation based on classification and collaborative representation based classification with regularized least square has been successfully used in face recognition. The over-completed dictionary is crucial for the approaches based on sparse representation or collaborative representation because it directly determines recognition accuracy and recognition time. In this paper, we proposed an algorithm of adaptive dictionary learning according to the inputting testing image. First, nearest neighbors of the testing image are labeled in local configuration pattern (LCP) subspace employing statistical similarity and configuration similarity defined in this paper. Then the face images labeled as nearest neighbors are used as atoms to build the adaptive representation dictionary, which means all atoms of this dictionary are nearest neighbors and they are more similar to the testing image in structure. Finally, the testing image is collaboratively represented and classified class by class with this proposed adaptive over-completed compact dictionary. Nearest neighbors are labeled by local binary pattern and microscopic feature in the very low dimension LCP subspace, so the labeling is very fast. The number of nearest neighbors is changeable for the different testing samples and is much less than that of all training samples generally, which significantly reduces the computational cost. In addition, atoms of this proposed dictionary are these high dimension face image vectors but not lower dimension LCP feature vectors, which ensures not only that the information included in face image is not lost but also that the atoms are more similar to the testing image in structure, which greatly increases the recognition accuracy. We also use the Fisher ratio to assess the robustness of this proposed dictionary. The extensive experiments on representative face databases with variations of lighting, expression, pose, and occlusion demonstrate that the proposed approach is superior both in recognition time and in accuracy.

Depression disorder has become one of the major psychological diseases endangering human health. Researcher in the affective computing community is supporting the development of reliable depression severity estimation system, from multiple modalities (speech, face, text), to assist doctors in their diagnosis. However, the limited amount of annotated data has become the main bottleneck restricting the study on depression screening, especially when deep learning models are used. To alleviate this issue, in this work we propose to use Deep Convolutional Generative Adversarial Network (DCGAN) for features augmentation to improve depression severity estimation from speech. To the best of our knowledge, this approach is the first attempt to apply the Generative Adversarial Network for depression severity estimation from speech. Besides, to measure the quality of the augmented features, we propose three different measurement criteria, characterizing the spatial, frequency and representation learning of the augmented features. Finally, the augmented features are used to train depression estimation models. Experiments are carried out on speech signals from the Audio Visual Emotion Challenge (AVEC2016) depression dataset, and the relationship between the model performance and data size is explored. Our experimental results show that: 1) The combination of the three proposed evaluation criteria can effectively and comprehensively evaluate the quality of the augmented features. 2) When increasing the size of the augmented data, the performance of depression severity estimation gradually improves and the model converges to a certain stable state. 3) The proposed DCGAN based data augmentation approach effectively improves the performance of depression severity estimation, with the root mean square error (RMSE) reduced to 5.520 and mean absolute error (MAE) reduced to 4.634, which is better than most of the state of the art results on AVEC 2016.

In the temporal process of expressing the emotions, some intervals embed more salient emotion information than others. In this paper, by introducing an attentive temporal pooling module into the deep neural network (DNN) architecture, we present a simple but effective speech emotion recognition (SER) framework, which is able to automatically highlight the emotionally salient segments while suppressing the influence of less relevant ones. For an input speech utterance, the extracted feature sequence of hand-crafted low-level descriptors (LLDs) are evenly split into several overlapping temporal segments, and the segment-level features are computed by performing functionals on the LLDs of each segment. These segment-level features are then input into a DNN model outputting the emotion probabilities as well as the more condensed representation of each segment. An attentive temporal pooling module, consisting of an auxiliary DNN and a Gaussian Mixture Model (GMM), is proposed to learn the emotional saliency weights of different temporal segments from the condensed representations, which are then assigned to the segment-level emotion probabilities for the final utterance-level prediction. Notably, the attentive temporal pooling module and the DNN architecture for feature abstraction can be jointly trained using only the utterance-level labels, while without any frame-level or segment-level supervisory information. Experimental results on the three public released emotion datasets RML, EMO-DB, and IEMOCAP show that the proposed framework obtains state-of-the-art performance on SER.

Background Bladder cancer (BC) is a common urinary tract system tumor with high recurrence rate and different populations show distinct response to immunotherapy. Novel biomarkers that can accurately predict prognosis and therapeutic responses are urgently needed. Here, we aim to identify a novel prognostic and therapeutic responses immune-related gene signature of BC through a comprehensive bioinformatics analysis. Methods The robust rank aggregation was conducted to integrate differently expressed genes (DEGs) in datasets of the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO). Lasso and Cox regression analyses were performed to formulate a novel mRNA signature that could predict prognosis of BC patients. Subsequently, the prognostic value and predictive value of the signature was validated with two independent cohorts GSE13507 and IMvigor210. Finally, quantitative Real-time PCR (qRT-PCR) analysis was conducted to determine the expression of mRNAs in BC cell lines (UM-UC-3, EJ-1, SW780 and T24). Results We built a signature comprised the eight mRNAs: CNKSR1, COPZ2, CXorf57, FASN, PCOLCE2, RGS1, SPINT1 and TPST1. Our prognostic signature could be used to stratify BC population into two risk groups with distinct immune profile and responsiveness to immunotherapy. The results of qRT-PCR demonstrated that the eight mRNAs exhibited different expression levels in BC cell lines. Conclusion Our study constructed a convenient and reliable 8-mRNA gene signature, which might provide prognostic prediction and aid treatment decision making of BC patients in clinical practice.

Exchange bias (EB) occurring in ferromagnetic (FM)/antiferromagnetic (AFM) bilayers conventionally can lead to a unidirectional magnetic anisotropy ( ${K_{{\text{eb}}}}$ ) as well as an accompanied uniaxial magnetic anisotropy ( ${K_{\text{u}}}$ ). We observed an additional fourfold magnetic anisotropy ( ${K_4}$ ) induced by interfacial exchange coupling in amorphous CoFeB/epitaxial IrMn bilayers with an EB. Because of the combined effect of the three kinds of magnetic anisotropies, one- and two-step magnetic switching processes were observed at different magnetic field orientations, which usually appear in single-crystal FM layer with an intrinsic magnetocrystalline anisotropy but not in amorphous FM layer. The angular dependent magnetic switching fields can be nicely fitted by a phenomenological model based on domain wall nucleation and propagation with the in-plane ${K_4}$ along . The ferromagnetic resonance measurements indicate that the specific strength of ${K_4}$ for EB along [100] is larger than that for EB along [110]. The induced ${K_4}$ can be understood by considering two types of AFM domains caused by both monatomic steps and defects and their induced net uncompensated spins along the in-plane axes. The different dependence of ${K_4}$ on the EB direction are because of the different effects of growth magnetic field on the presence of AFM domains.

The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8+ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8+ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8+ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8+ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8+ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8+ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.

Epigenetic factors, including non-coding RNA regulation, play a vital role in the development of obesity and have been well researched. Transfer RNA-derived small RNA (tsRNA) is a class of non-coding RNA proven to be involved in various aspects of mammalian biology. Here we take pigs as a model for obesity research and use tsRNA-seq to investigate the difference in tsRNA expression in the subcutaneous adipose tissue of obese and lean pigs to elucidate the role of tsRNA in obesity development. A total of 482 tsRNAs were identified in pig adipose tissue, of which 123 were significantly differentially accumulated tsRNAs compared with the control group. The tRF-5c was the main type of these tsRNAs. The largest number of tsRNAs produced was the Gly-carrying tRNA, which produced 81 tsRNAs. Functional enrichment analysis revealed that differential tsRNAs indirectly participated in MAPK, AMPK, insulin resistance, the TNF signaling pathway, adipocytokine signaling pathway, and other signaling pathways by interacting with target genes. These are involved in bioenergetic metabolic regulatory processes, suggesting that tsRNAs may influence these pathways to mediate the regulation of energy metabolism in porcine adipocytes to promote lipid deposition, thus contributing to obesity. Our findings suggest a potential function of tsRNA in regulating obesity development.

ABSTRACT: Ornithine decarboxylase (ODC) plays an indispensable role in the process of polyamine biosynthesis. Polyamines are a pivotal part of living cells and have diverse roles in the regulation of cell proliferation and apoptosis, aging and reproduction. However, to date, there have been no reports about ODC regulating follicular development in goose ovaries. Here, we constructed ODC siRNA and overexpression plasmids and transfected them into goose primary granulosa cells (GCs) to elucidate the effects of ODC interference and overexpression on the polyamine metabolism, hormone levels, cell apoptosis and proliferation of granulosa cells. After interfering with ODC in GCs, the mRNA and protein levels of ODC and the content of putrescine were greatly decreased (P < 0.05). When ODC was overexpressed, ODC mRNA and protein levels and putrescine content were greatly increased (P < 0.05). The polyamine-metabolizing enzyme genes ornithine decarboxylase antizyme 1 (OAZ1) and spermidine / spermine-N1-acetyltransferase (SSAT) were significantly increased, and spermidine synthase (SPDS) was significantly decreased when ODC was downregulated (P < 0.05). OAZ1, SPDS and SSAT were significantly increased when ODC was upregulated (P < 0.05). In addition, after interference with ODC, progesterone (P4) levels in the culture medium of GCs increased greatly (P < 0.05), while the overexpression of ODC caused the P4 level to decrease significantly (P < 0.05). After ODC downregulation, granulosa cell activity was significantly reduced, the apoptosis rate was significantly increased, and the BCL-2 / BAX ratio was downregulated (P < 0.05). Under ODC overexpression, the activity of GCs was notably increased, the apoptosis rate was significantly reduced, and the BCL-2 / BAX protein ratio was upregulated (P < 0.05). Our study successfully induced ODC interference and overexpression in goose ovarian GCs, and ODC regulated mainly putrescine content in GCs with a slight influence on spermidine and spermine. Moreover, ODC participated in the adjustment of P4 levels in the culture medium of GCs, promoted granulosa cell proliferation and inhibited granulosa cell apoptosis.

Isothermal compression behaviors of as-extruded AA 2055 alloy (T6 state) were studied at temperature of 320, 380, 440 and 500 °C with strain rate of 0.001, 0.01, 0.1 and 1 s−1 by a Gleeble-3800 testing machine. A modified Johnson–Cook model fitted by polynomial and power-exponential functions were established to describe the flow stress of the alloy. The constitutive models fitted by higher-order polynomials were more accurate than the ones fitted by second-order polynomial and power-exponential functions. The constitutive model fitted by a fourth-order polynomial was chosen for the optimal constitutive model in order to balance the prediction accuracy and model complexity. The modified Johnson–Cook constitutive model could predict the flow stress well, especially in high-temperature zone (around 500 °C) and low-temperature zone (around 320 °C). The dynamic precipitation and dissolution of the T1 phase during hot compression were discussed. The unusual dynamic precipitation of the T2 phase was investigated during hot compression by XRD and TEM. The massive dense fine precipitates effectively pinned dislocations or subgrain boundaries to accelerate DRV but suppressed DRX, leading to a low frequency of HAGBs in compressed samples.

de Winter syndrome, also termed anterior ST-segment elevation myocardial infarction (STEMI) equivalent, is estimated to be present in approximately 2% of patients with acute myocardial infarction, but is often under-recognized by clinicians. Therefore, de Winter syndrome is associated with increased morbidity and mortality. We report a 51-year-old man with typical chest tightness and a characteristic electrocardiographic pattern without classic ST-segment elevation, but with acute nearly total occlusion of the left anterior descending coronary artery. Although the patient presented as a non-STEMI case, the definite diagnosis of de Winter syndrome was made on the basis of clinical and electrocardiographic findings. The patient’s symptom of chest tightness was relieved immediately after acute percutaneous coronary intervention and the left ventricular ejection fraction had not deteriorated at 1 month of follow-up.

Sparse representation has exhibited excellent performance in face recognition. However, this method requires some areas for improvement, especially on insufficient face samples. We aim to design a simple and efficient method to improve sparse representation to solve problems with a small sample size. This paper provides two primary contributions that are very effective in small sample face recognition. First, in order to enhance recognition robustness, we designed an intuitive and mathematically controllable transfer learning method of sparse representation by introducing labeled samples. Second, to obtain high recognition accuracy, we developed a weighted fusion scheme to integrate the sparse representation results generated from original and labeled samples. In the ORL dataset, our algorithm’s highest accuracy rate is 95%. In the FERET dataset, our highest classification accuracy rate is 95%. In the more complex LFW dataset, our highest classification accuracy rate has also reached 83.33%. This shows that our experimental results demonstrate that the proposed method can obtain sufficient performance, whereas the weighted fusion scheme can take advantage of sparse representation on the basis of original and labeled samples. This paper will be very useful for identification based on the Internet-of-Medical-Things.

Betaine is a natural compound present in commonly consumed foods and may have a potential role in the regulation of glucose and lipids metabolism. However, the underlying molecular mechanism of its action remains largely unknown. Here, we show that supplementation with betaine contributes to improved high-fat diet (HFD)-induced gut microbiota dysbiosis and increases anti-obesity strains such as Akkermansia muciniphila, Lactobacillus, and Bifidobacterium. In mice lacking gut microbiota, the functional role of betaine in preventing HFD-induced obesity, metabolic syndrome, and inactivation of brown adipose tissues are significantly reduced. Akkermansia muciniphila is an important regulator of betaine in improving microbiome ecology and increasing strains that produce short-chain fatty acids (SCFAs). Increasing two main members of SCFAs including acetate and butyrate can significantly regulate the levels of DNA methylation at host miR-378a promoter, thus preventing the development of obesity and glucose intolerance. However, these beneficial effects are partially abolished by Yin yang (YY1), a common target gene of the miR-378a family. Taken together, our findings demonstrate that betaine can improve obesity and associated MS via the gut microbiota-derived miR-378a/YY1 regulatory axis, and reveal a novel mechanism by which gut microbiota improve host health.

Intercropping improves land-use efficiency under conditions of limited land and resources, but no information is currently available pertaining to land-use efficiency and silage quality based on whole-plant utilization. Therefore, a two-year field experiment was conducted with the following conditions: three maize–soybean strip intercropping patterns (SIPs), comprising two maize rows along with two, three, or four soybean rows (2M2S, 2M3S, and 2M4S, respectively); and two sole cropping patterns of maize (SM) and soybean (SS). The aim was to evaluate the biomass yield and silage quality under each condition. Our results showed that all SIPs had a land equivalent ratio (LER) of over 1.6 based on both fresh and dry matter yield, and a higher whole plant yield, compared to sole cropping. Specifically, 2M3S exhibited the highest whole crop dry matter LER (1.8–1.9) and yield (24.6–27.2 t ha−1) compared to SM and SS (20.88–21.49 and 3.48–4.79 t ha−1, respectively). Maize–soybean mixed silages also showed better fermentation quality with higher lactic acid content (1–3%) and lower ammonia-N content (2–8%) compared to SS silages, and higher crude protein content (1–1.5%) with lower ammonia-N content (1–2%) compared to SM silage. Among the intercropping patterns, 2M3S had the highest fermentation quality index V-score (92–95). Consequently, maize–soybean strip intercropping improved silage quality and biomass yield, with 2M3S being recommended, due to its highest LER and biomass yield, and most optimal silage quality.

Objectives Autophagy is divided into three phases: autophagosome engulfment of intracellular organelles and proteins, autophagosome fusion with lysosomes, and autolysosome degradation. The farnesyl pyrophosphate synthase inhibitor ibandronate (IBAN) has in vivo cardioprotective properties, potentially via anti-oxidant effects. Whether autophagy is involved in the cardioprotective effect of IBAN remains unexplored. Methods Human umbilical vein endothelial cells (HUVECs) were treated in vitro with IBAN to assess autophagy induction. Lysosomal activation and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling were assessed using a LysoTracker assay, acridine orange staining and western blotting. An MTS assay was used to assess cellular proliferation. Autophagy was inhibited using chloroquine or RNA silencing of autophagy-related 7 (Atg7) expression. Results IBAN induced autophagy in HUVECs. Moreover, IBAN activated lysosomal function, which is pivotal to autophagy induction. PI3K/AKT/mTOR activity was inhibited in IBAN-treated HUVECs, indicating the involvement of this pathway in IBAN-induced autophagy. Inhibition of autophagy using either chloroquine or Atg7 siRNA potentiated inhibition of HUVEC growth by IBAN, suggesting the involvement of non-autophagy pathways in the antiproliferative effects of IBAN. Conclusions These findings provide insights into the role of autophagy in the cardioprotective effects of IBAN and the molecular mechanisms underlying autophagy induction by IBAN.

There is a general agreement in the brain computer interface community that the feature extracting method called the common spatial pattern (CSP) combined with nonlinear classifiers can provide excellent results in some cases. However, CSP is also known to be very sensitive to noise and prone to over fitting, and the performance of this spatial filter is closely related to the operational frequency band of electroencephalogram data. To address this issue, we propose a new method FB-TRCSP+RF based on CSP and random forest. The FB-TRCSP is combined by the 8th-order Butterworth bandpass-filters and the CSP with Tikhonov regularization, which is a more robust feature extraction method compared to the CSP. Then, the model is applied to an experimental data set collected from 14 subjects and is compared with the non-regularization method FB-CSP+RF. The results show that the method we proposed yields relatively higher median classification accuracies and shows a stronger ability in subject-to-subject learning compared to prevailing approaches.

Background: Ornithine decarboxylase antizyme 1 (OAZ1) is an important regulator of polyamine synthesis and uptake. Our previous studies indicated that high OAZ1 expression in the ovaries of laying geese is responsible for poor egg production. In the present study, the molecular characterization of goose OAZ1 gene was analyzed, as well as the expression profile in various follicular tissues. Results: An 873-bp cDNA sequence of the OAZ1 gene (Accession No. KC845302) with a +1 frameshift site (+175T) was obtained. The sequence consisted of a 652-bp two overlapping open reading frames (a putative protein with 216 amino acids). The OAZ domain, OAZ signature and OAZ super family domain were prominent conserved regions among species. As the follicle size increased, OAZ1 abundance showed an increasing trend during follicular development, while it decreased during follicular regression. The level of OAZ1 mRNA expression was the lowest in the fifth largest preovulatory follicle, and was 0.65-fold compared to the small white follicle (P

Two types of polynuclear Cd-Ln complexes [CdLnL(NO3)Cl2(DMF)2] [Ln = La (1) and Nd (2)] and [Ln2CdL2(NO3)2(DMF)2](OH)2 [Ln = La (3) and Nd (4)] were constructed using a new Schiff base ligand which has a long backbone with two phenyl groups. The Schiff base ligands show a “twist” configuration in 1–4. The crystal structures show that the molecular dimensions of 3 and 4 are about 6 × 10 × 15 Å. The Cd-Nd complexes 2 and 4 exhibit the typical NIR luminescence of Nd3+. Interestingly, 4 shows the luminescent sensing of nitro explosives and exhibits a high sensitivity to 2-nitrophenol at the ppm level.

Latent autoimmune diabetes in adults (LADA) is characterized as a slow-progressing form of autoimmune diabetes. LADA resembles some phenotypes of type 1 diabetes (T1D) and type 2 diabetes (T2D), frequently leading to misdiagnosis and inappropriate therapeutic strategies. Understanding its transcriptome profiles aids in revealing the detailed molecular mechanisms of LADA and its therapy. In the present study, we performed RNA-seq analysis of LADA patients from Eastern China and showed that LADA exhibited 277 differentially expressed genes (DEGs) with 199 upregulated and 78 downregulated. Gene ontology and KEGG pathway enrichment analysis revealed that these DEGs were mainly related to immune function and cell death and growth. Furthermore, a comparison of DEGs in LADA with those in T1D and T2D identified from the online databases showed that there are very few overlapped genes between LADA and T1D or T2D, confirming LADA to be a distinct type of diabetes from T1D or T2D. In summary, our comprehensive analysis may aid in the understanding and treatment of LADA patients in Eastern China.

Onboard real-time object detection in remote sensing images is a crucial but challenging task in this computation-constrained scenario. This task not only requires the algorithm to yield excellent performance but also requests limited time and space complexity of the algorithm. However, previous convolutional neural networks (CNN) based object detectors for remote sensing images suffer from heavy computational cost, which hinders them from being deployed on satellites. Moreover, an onboard detector is desired to detect objects at vastly different scales. To address these issues, we proposed a lightweight one-stage multi-scale feature fusion detector called MSF-SNET for onboard real-time object detection of remote sensing images. Using lightweight SNET as the backbone network reduces the number of parameters and computational complexity. To strengthen the detection performance of small objects, three low-level features are extracted from the three stages of SNET respectively. In the detection part, another three convolutional layers are designed to further extract deep features with rich semantic information for large-scale object detection. To improve detection accuracy, the deep features and low-level features are fused to enhance the feature representation. Extensive experiments and comprehensive evaluations on the openly available NWPU VHR-10 dataset and DIOR dataset are conducted to evaluate the proposed method. Compared with other state-of-art detectors, the proposed detection framework has fewer parameters and calculations, while maintaining consistent accuracy.

Gene transcripts or mRNAs and long noncoding RNAs (lncRNAs) are differentially expressed during porcine skeletal muscle development. However, only a few studies have been conducted on skeletal muscle transcriptome in pigs based on timepoints according to the growth curve for porcine. Here, we investigated gene expression in Qingyu pigs at three different growth stages: the inflection point with the maximum growth rate (MGI), the inflection point of the gradually increasing stage to the rapidly increasing stage (GRI), and the inflection point of the rapidly increasing stage to the slowly increasing stage (RSI). Subsequently, we explored gene expression profiles during muscle development at the MGI, GRI and RSI stages by Ribo-Zero RNA sequencing. Qingyu pigs reached the MGI, GRI and RSI stages at 156.40, 23.82 and 288.97 days of age with 51.73, 3.14 and 107.03 kg body weight, respectively. A total of 14,530 mRNAs and 11,970 lncRNAs were identified at the three stages, and 645, 323 differentially expressed genes (DEGs) and 696, 760 differentially expressed lncRNAs (DELs) were identified in the GRI vs. MGI, and RSI vs. MGI, comparisons. Functional enrichment analysis revealed that genes involved in immune system development and energy metabolism (mainly relate to amino acid, carbohydrate and lipid) were enriched at the GRI and MGI stages, respectively, whereas genes involved in lipid metabolism were enriched at the RSI stage. We further characterized G1430, an abundant lncRNA. The full-length sequence (316 nt) of lncRNA G1430 was determined by rapid amplification of cDNA ends (RACE). Subcellular distribution analysis by quantitative real-time PCR (qRT-PCR) revealed that G1430 is a cytoplasmic lncRNA. Binding site prediction and dual luciferase assay showed that lncRNA G1430 directly binds to microRNA 133a (miR-133a). Our findings provide the basis for further investigation of the regulatory mechanisms and molecular genetics of muscle development in pigs.

Background: Prolactin (PRL) regulates development and reproduction, and its effects are mediated by the prolactin receptor (PRLR). In order to clarify the role of PRLR and PRL in the process of follicular development in the goose ovary, the level of PRLR mRNA expression in the ovary and follicles of the Sichuan white goose was determined, as well as the PRL concentration in ovarian follicles. Results: The level of PRLR mRNA in the hierarchical follicles (HFs) initially increased, and subsequently decreased, whereas PRLR expression was initially low and later increased in postovulatory follicles (POFs). The level of PRLR mRNA expression was the highest in the F4 follicles, and lowest in the F1 follicles in all of the examined follicles. Compared with the level of PRLR mRNA expression in the small white follicles (SWFs), the level of PRLR mRNA was 2.86- and 1.44-fold higher in the F4 and small yellow follicles (SYFs), respectively (P

Indigenous pig breeds are important biological resources and their diversity has been severely damaged. The Liangshan pig is a typical mountain-type local pig breed in southwest China. Here, the meat quality, amino acid, and fatty acid composition of Liangshan pigs were compared at seven stages within the weight range of 50–90 kg. A score for comprehensive factors of meat quality was maintained after rising and kept in a plateau within 74.9–91.5 kg of body weight. The total amount of amino acids in the longissimus dorsi muscle remained stable, and the total fatty acids showed an upward trend. Amino acid composition analysis revealed that as the body weight of Liangshan pigs increased, umami, basic, and acidic amino acid contents decreased, while the essential amino acids (EAA) content and the ratio of basic amino acids to acidic amino acids increased. Fatty acid composition analysis revealed that as body weight increased, the content of polyunsaturated fatty acids (PUFA) exhibited a downward trend, while the content of saturated fatty acids (SFA) exhibited an upward trend. This study is a primary step towards the development and utilization of Liangshan pigs and provides useful information for local pork processing and genetic improvement.

Cardiac hypertrophy is a common pathological condition and an independent risk factor that triggers cardiovascular morbidity. As an important epigenetic regulator, miRNA is widely involved in many biological processes. In this study, miRNAs expressed in rat hearts that underwent isoprenaline-induced cardiac hypertrophy were identified using high-throughput sequencing, and functional verification of typical miRNAs was performed using rat primary cardiomyocytes. A total of 623 miRNAs were identified, of which 33 were specifically expressed in cardiac hypertrophy rats. The enriched pathways of target genes of differentially expressed miRNAs included the FoxO signaling pathway, dopaminergic synapse, Wnt signaling pathway, MAPK (mitogen-activated protein kinase) signaling pathway, and Hippo signaling pathway. Subsequently, miR-144 was the most differentially expressed miRNA and was subsequently selected for in vitro validation. Inhibition of miR-144 expression in primary myocardial cells caused up-regulation of cardiac hypertrophy markers atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP). The dual luciferase reporter system showed that ANP may be a target gene of miR-144. Long non-coding RNA myocardial infarction associated transcript (LncMIAT) is closely related to heart disease, and here, we were the first to discover that LncMIAT may act as an miR-144 sponge in isoproterenol-induced cardiac hypertrophy. Taken together, these results enriched the understanding of miRNA in regulating cardiac hypertrophy and provided a reference for preventing and treating cardiac hypertrophy.

Two series of Zn-Ln and Cd-Ln nanoclusters [Ln4Zn8L2(OAc)20(OH)4] [Ln = Nd (1), Yb (2), and Sm (3)] and [Ln2Cd2L2(OAc)2(OH)2(OCH3)2] [Ln = Nd (4), Yb (5), and Sm (6)] were prepared using a long-chain Schiff base ligand with a flexible (CH2)2O(CH2)2O(CH2)2 chain. All these clusters show square-like structures. The Schiff base ligands show “linear” configurations in the structures of 1-6, and the metric dimensions of Zn-Ln and Cd-Ln clusters measure ~8 × 14 × 21 and 8 × 12 × 12 Å, respectively. The study of luminescence properties shows that the Zn/L and Cd/L chromophores can effectively transfer energy to the lanthanide ions, and 1-6 show visible and NIR emissions.

An increasing number of studies suggest that ornithine decarboxylase antizyme 1 (OAZ1), which is regarded as a tumor suppressor gene, regulates follicular development, ovulation, and steroidogenesis. The granulosa cells in the ovary play a critical role in these ovarian functions. However, the action of OAZ1 mediating physiological functions of granulosa cells is obscure. OAZ1 knockdown in granulosa cells of geese was carried out in the current study. The effect of OAZ1 knockdown on polyamine metabolism, cell proliferation, apoptosis, and hormone receptor transcription of primary granulosa cells in geese was measured. The viability of granulosa cells transfected with the shRNA OAZ1 at 48 h was significantly higher than the control (p

tRNA-derived fragments (tRFs), a novel type of non-coding RNA derived from tRNAs, play an important part in governing gene expressions at a post-transcriptional level. To date, the regulatory mechanism of tRFs governing fat deposition and adipogenesis is completely unknown. In this study, high fat diet was employed to induce an obese rat model, and tRFs transcriptome sequencing was conducted to identify differentially expressed tRFs that response to obesity. We found out that tRFGluTTC, which promoted preadipocyte proliferation by increasing expressions of cell cycle regulatory factors, had the highest fold change in the 296 differentially expressed tRFs. Moreover, tRFGluTTC also suppressed preadipocyte differentiation by reducing triglyceride content and lipid accumulation, and by decreasing expressions of genes that related to fatty acid synthesis. According to results of luciferase activity analysis, tRFGluTTC directly targeted Kruppel-like factor (KLF) 9, KLF11, and KLF12, thus significantly suppressing mRNA expressions of these target genes. Moreover, tRFGluTTC suppressed adipogenesis, accompanying by suppressing expressions of adipogenic transcription factors (aP2, PPARγ, and C/EBPα). In conclusion, these results imply that tRFGluTTC may act as a novel epigenetic molecule regulating adipogenesis and could provide a new strategy for the intervention treatment of obesity.