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Abstract Background: Nonspecific Orbital Inflammation (NSOI) remains a perplexing enigma among proliferative inflammatory disorders. Its etiology is idiopathic, characterized by distinctive and polymorphous lymphoid infiltration within the orbital region. Preliminary investigations suggest that PALMD localizes within the cytosol, potentially playing a crucial role in cellular processes, including plasma membrane dynamics and myogenic differentiation. The potential of PALMD as a biomarker for NSOI warrants meticulous exploration. Methods: PALMD was identified through the intersection analysis of common DEGs from datasets GSE58331 and GSE105149 from the GEO database, alongside immune-related gene lists from the ImmPort database, using Lasso regression and SVM-RFE analysis. GSEA and GSVA were conducted with gene sets co-expressed with PALMD. To further investigate the correlation between PALMD and immune-related biological processes, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate immune microenvironment characteristics of each sample. The expression levels of PALMD were subsequently validated using GSE105149. Results: Among the 314 DEGs identified, several showed significant differences. Lasso and SVM-RFE algorithms pinpointed 15 hub genes. Functional analysis of PALMD emphasized its involvement in cell-cell adhesion, leukocyte migration, and leukocyte-mediated immunity. Enrichment analysis revealed that gene sets positively correlated with PALMD were enriched in immune-related pathways. Immune infiltration analysis indicated that resting dendritic cells, resting mast cells, activated NK cells, and plasma cells positively associate with PALMD expression. Conversely, naive B cells, activated dendritic cells, M0 and M1 macrophages, activated mast cells, activated CD4 memory T cells, and naive CD4 T cells showed a negative correlation with PALMD expression. PALMD demonstrated significant diagnostic potential in differentiating NSOI. Conclusions: This study identifies PALMD as a potential biomarker linked to NSOI, providing insights into its pathogenesis and offering new avenues for tracking disease progression.

Abstract Idiopathic orbital inflammation, formerly known as NSOI (nonspecific orbital inflammation), is characterized as a spectrum disorder distinguished by the polymorphic infiltration of lymphoid tissue, presenting a complex and poorly understood etiology. Recent advancements have shed light on the HLF (Human lactoferrin), proposing its critical involvement in the regulation of hematopoiesis and the maintenance of innate mucosal immunity. This revelation has generated significant interest in exploring HLF's utility as a biomarker for NSOI, despite the existing gaps in our understanding of its biosynthetic pathways and operational mechanisms. Intersecting multi-omic datasets—specifically, common differentially expressed genes between GSE58331 and GSE105149 from the Gene Expression Omnibus and immune-related gene compendiums from the ImmPort database—we employed sophisticated analytical methodologies, including Lasso regression and support vector machine-recursive feature elimination, to identify HLF. Gene set enrichment analysis and gene set variation analysis disclosed significant immune pathway enrichment within gene sets linked to HLF. The intricate relationship between HLF expression and immunological processes was further dissected through the utilization of CIBERSORT and ESTIMATE algorithms, which assess characteristics of the immune microenvironment, highlighting a noteworthy association between increased HLF expression and enhanced immune cell infiltration. The expression levels of HLF were corroborated using data from the GSE58331 dataset, reinforcing the validity of our findings. Analysis of 218 HLF-related differentially expressed genes revealed statistically significant discrepancies. Fifteen hub genes were distilled using LASSO and SVM-RFE algorithms. Biological functions connected with HLF, such as leukocyte migration, ossification, and the negative regulation of immune processes, were illuminated. Immune cell analysis depicted a positive correlation between HLF and various cells, including resting mast cells, activated NK cells, plasma cells, and CD8 T cells. Conversely, a negative association was observed with gamma delta T cells, naive B cells, M0 and M1 macrophages, and activated mast cells. Diagnostic assessments of HLF in distinguishing NSOI showed promising accuracy. Our investigation delineates HLF as intricately associated with NSOI, casting light on novel biomarkers for diagnosis and progression monitoring of this perplexing condition.

Abstract Background Nonspecific Orbital Inflammation (NSOI) represents a persistent and idiopathic proliferative inflammatory disorder, characterized by polymorphous lymphoid infiltration within the orbit. The transcription factor Interferon Regulatory Factor 8 (IRF8), integral to the IRF protein family, was initially identified as a pivotal element for the commitment and differentiation of myeloid cell lineage. Serving as a central regulator of innate immune receptor signaling, IRF8 orchestrates a myriad of functions in hematopoietic cell development. However, the intricate mechanisms underlying IRF8 production remain to be elucidated, and its potential role as a biomarker for NSOI is yet to be resolved. Methods IRF8 was extracted from the intersection analysis of common DEGs of GSE58331 and GSE105149 from the GEO and immune- related gene lists in the ImmPort database using The Lasso regression and SVM-RFE analysis. We performed GSEA and GSVA with gene sets coexpressed with IRF8, and observed that gene sets positively related to IRF8 were enriched in immune-related pathways. To further explore the correlation between IRF8 and immune-related biological process, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate TME characteristics of each sample and confirmed that high IRF8 expression might give rise to high immune cell infiltration. Finally, the GSE58331 was utilized to confirm the levels of expression of IRF8. Results Among the 314 differentially expressed genes (DEGs), some DEGs were found to be significantly different. With LASSO and SVM-RFE algorithms, we obtained 15 hub genes. For biological function analysis in IRF8, leukocyte mediated immunity, leukocyte cell-cell adhesion, negative regulation of immune system process were emphasized. B cells naive, Macrophages M0, Macrophages M1, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD4 naive, and T cells gamma delta were shown to be positively associated with IRF8. While, Mast cells resting, Monocytes, NK cells activated, Plasma cells, T cells CD8, and T cells regulatory (Tregs) were shown to be negatively linked with IRF8. The diagnostic ability of the IRF8 in differentiating NSOI exhibited a good value. Conclusions This study discovered IRF8 that are linked to NSOI. IRF8 shed light on potential new biomarkers for NSOI and tracking its progression.

BackgroundNon-specific Orbital Inflammation (NSOI) is a chronic idiopathic condition marked by extensive polymorphic lymphoid infiltration in the orbital area. The integration of metabolic and immune pathways suggests potential therapeutic roles for C-peptide and G protein-coupled receptor 146 (GPR146) in diabetes and its sequelae. However, the specific mechanisms through which GPR146 modulates immune responses remain poorly understood. Furthermore, the utility of GPR146 as a diagnostic or prognostic marker for NSOI has not been conclusively demonstrated.MethodsWe adopted a comprehensive analytical strategy, merging differentially expressed genes (DEGs) from the Gene Expression Omnibus (GEO) datasets GSE58331 and GSE105149 with immune-related genes from the ImmPort database. Our methodology combined LASSO regression and support vector machine-recursive feature elimination (SVM-RFE) for feature selection, followed by Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) to explore gene sets co-expressed with GPR146, identifying a significant enrichment in immune-related pathways. The tumor microenvironment’s immune composition was quantified using the CIBERSORT algorithm and the ESTIMATE method, which confirmed a positive correlation between GPR146 expression and immune cell infiltration. Validation of GPR146 expression was performed using the GSE58331 dataset.ResultsAnalysis identified 113 DEGs associated with GPR146, with a significant subset showing distinct expression patterns. Using LASSO and SVM-RFE, we pinpointed 15 key hub genes. Functionally, these genes and GPR146 were predominantly linked to receptor ligand activity, immune receptor activity, and cytokine-mediated signaling. Specific immune cells, such as memory B cells, M2 macrophages, resting mast cells, monocytes, activated NK cells, plasma cells, and CD8+ T cells, were positively associated with GPR146 expression. In contrast, M0 macrophages, naive B cells, M1 macrophages, activated mast cells, activated memory CD4+ T cells, naive CD4+ T cells, and gamma delta T cells showed inverse correlations. Notably, our findings underscore the potential diagnostic relevance of GPR146 in distinguishing NSOI.ConclusionOur study elucidates the immunological signatures associated with GPR146 in the context of NSOI, highlighting its prognostic and diagnostic potential. These insights pave the way for GPR146 to be a novel biomarker for monitoring the progression of NSOI, providing a foundation for future therapeutic strategies targeting immune-metabolic pathways.

Abstract Background Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking. Methods This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149. Results Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results. Conclusions This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

BackgroundNonspecific orbital inflammation (NSOI) represents a perplexing and persistent proliferative inflammatory disorder of idiopathic nature, characterized by a heterogeneous lymphoid infiltration within the orbital region. This condition, marked by the aberrant metabolic activities of its cellular constituents, starkly contrasts with the metabolic equilibrium found in healthy cells. Among the myriad pathways integral to cellular metabolism, purine metabolism emerges as a critical player, providing the building blocks for nucleic acid synthesis, such as DNA and RNA. Despite its significance, the contribution of Purine Metabolism Genes (PMGs) to the pathophysiological landscape of NSOI remains a mystery, highlighting a critical gap in our understanding of the disease’s molecular underpinnings.MethodsTo bridge this knowledge gap, our study embarked on an exploratory journey to identify and validate PMGs implicated in NSOI, employing a comprehensive bioinformatics strategy. By intersecting differential gene expression analyses with a curated list of 92 known PMGs, we aimed to pinpoint those with potential roles in NSOI. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), facilitated a deep dive into the biological functions and pathways associated with these PMGs. Further refinement through Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) enabled the identification of key hub genes and the evaluation of their diagnostic prowess for NSOI. Additionally, the relationship between these hub PMGs and relevant clinical parameters was thoroughly investigated. To corroborate our findings, we analyzed expression data from datasets GSE58331 and GSE105149, focusing on the seven PMGs identified as potentially crucial to NSOI pathology.ResultsOur investigation unveiled seven PMGs (ENTPD1, POLR2K, NPR2, PDE6D, PDE6H, PDE4B, and ALLC) as intimately connected to NSOI. Functional analyses shed light on their involvement in processes such as peroxisome targeting sequence binding, seminiferous tubule development, and ciliary transition zone organization. Importantly, the diagnostic capabilities of these PMGs demonstrated promising efficacy in distinguishing NSOI from non-affected states.ConclusionsThrough rigorous bioinformatics analyses, this study unveils seven PMGs as novel biomarker candidates for NSOI, elucidating their potential roles in the disease’s pathogenesis. These discoveries not only enhance our understanding of NSOI at the molecular level but also pave the way for innovative approaches to monitor and study its progression, offering a beacon of hope for individuals afflicted by this enigmatic condition.

Abstract Thyroid eye disease (TED), an autoimmune inflammatory disorder affecting the orbit, exhibits a range of clinical manifestations. While the disease presentation can vary, cases that adhere to a prototypical pattern typically commence with mild symptoms that subsequently escalate in severity before entering a phase of stabilization. Notably, the metabolic activity of cells implicated in the disease substantially deviates from that of healthy cells, with purine metabolism representing a critical facet of cellular material metabolism by supplying components essential for DNA and RNA synthesis. Nevertheless, the precise involvement of Purine Metabolism Genes (PMGs) in the defensive mechanism against TED remains largely unexplored. The present study employed a bioinformatics approach to identify and validate potential PMGs associated with TED. A curated set of 65 candidate PMGs was utilized to uncover novel PMGs through a combination of differential expression analysis and a PMG dataset. Furthermore, GSEA and GSVA were employed to explore the biological functions and pathways associated with the newly identified PMGs. Subsequently, the Lasso regression and SVM-RFE algorithms were applied to identify hub genes and assess the diagnostic efficacy of the top 10 PMGs in distinguishing TED. Additionally, the relationship between hub PMGs and clinical characteristics was investigated. Finally, the expression levels of the identified ten PMGs were validated using the GSE58331 and GSE105149 datasets. This study revealed ten PMGs related with TED. PRPS2, PFAS, ATIC, NT5C1A, POLR2E, POLR2F, POLR3B, PDE3A, ADSS, and NTPCR are among the PMGs. The biological function investigation revealed their participation in processes such as RNA splicing, purine-containing chemical metabolism, and purine nucleotide metabolism. Furthermore, the diagnostic performance of the 10 PMGs in differentiating TED was encouraging. This study was effective in identifying ten PMGs linked to TED. These findings provide light on potential new biomarkers for TED and open up possibilities for tracking disease development.

Abstract Oxidative stress is an important mechanism of aging, and in turn, aging can also aggravate oxidative stress, which leads to a vicious cycle. In the process of the brain converting light into visual signals, the eye is stimulated by harmful blue‐light radiation directly. Thus, the eye is especially vulnerable to oxidative stress and becomes one of the organs most seriously involved during the aging process. Cataracts, age‐related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and dry eye are inextricably linked to the aging process and oxidative stress. Chlorogenic acid (CGA) has been demonstrated to have antioxidant and anti‐inflammatory activities, and its validity has been established experimentally in numerous fields, including cardiovascular disease, metabolic disorders, cancers, and other chronic diseases. There has previously been evidence of CGA's therapeutic effect in the field of ophthalmopathy. Considering that many ophthalmic drugs lead to systemic side effects, CGA may act as a natural exogenous antioxidant for patients to take regularly, controlling their condition while minimizing side effects. In this paper, in vitro and in vivo studies of CGA in the treatment of age‐related eye diseases are reviewed, and the prospects of CGA's antioxidant application for the eye are discussed. The aim of this review is to summarize the relevant knowledge and provide theoretical support for future research.

Study region: The Tonghui River–a treated effluent-affected urban river located in Beijing, China. Study focus: Inspired by the signal processing theory, this study presented a simulation scheme for the treated effluent-affected river based on hydrologic monitoring, pattern recognization, pattern extraction, and hydrologic/hydraulic modelling. It aimed to precisely depict the river flow patterns when detailed wastewater treatment plant effluent data was absent and to fill in the gap of the application of signal-based hydrological time series processing methods in physically based hydraulic simulation. New hydrological insights for the region: Diurnal and semidiurnal patterns caused by the wastewater treatment plant (WWTP) effluent were recognized from the water level series using the continuous wavelet transform. Due to their small amplitudes, they were masked during flood events but dominated the flow regime in dry seasons. Based on the discrete wavelet decomposition and Fourier series fitting, these periodical patterns were extracted and fitted. With a preliminarily calibrated hydraulic model and a linear signal amplifier, a simulated WWTP effluent was retrieved. Dry seasons simulation utilizing the simulated effluent obtained significantly better performance than using the average effluent data from the aspects of conventional evaluation metrics, cross-wavelet transform, and wavelet coherence.

The successful establishment of endometrial receptivity is a key factor in ensuring the fertility of ewes and their economic benefits. Hu sheep have attracted attention due to their high fecundity and year-round estrus. In this study, we found that in the luteal phase, the uterine gland density, uterine coefficient, and number of uterine caruncles of high-fertility Hu sheep were higher than those of low-fertility Hu sheep. Thousands of differentially expressed genes were identified in the endometrium of Hu sheep with different fertility potential using RNA sequencing (RNA-Seq). Several genes involved in endometrial receptivity were screened using bioinformatics analysis. The qRT-PCR analysis further revealed the differential expression of cAMP reactive element binding protein-1 (CREB1) in the Hu sheep endometrium during the estrous cycle. Functionally, our results suggested that CREB1 significantly affected the expression level of endometrial receptivity marker genes, promoted cell proliferation by facilitating the transition from the G1 phase to the S phase, and inhibited cell apoptosis and autophagy. Moreover, we observed a negative linear correlation between miR-134-5p and CREB1 in the endometrium. In addition, CREB1 overexpression prevented the negative effect of miR-134-5p on endometrial stromal cell (ESC) growth. Taken together, these data indicated that CREB1 was regulated by miR-134-5p and may promote the establishment of uterine receptivity by regulating the function of ESCs. Moreover, this study provides new theoretical references for identifying candidate genes associated with fertility.

IntroductionThis study aims to investigate the long-term effects of spirulina supplementation in a high-fat diet (HFD) on rumen morphology, rumen fermentation, and the composition of rumen microbiota in lambs. Spirulina is a blue-green microalgae that has been shown to have high nutritional value for livestock.MethodsFifty-four lambs were randomly divided into three groups: a normal chow diet (NCD) group, a high-fat diet (HFD) group, and a high-fat diet supplemented with 3% spirulina (HFD+S) group. Rumen morphology, rumen fermentation, and rumen microbiota were analyzed at the end of the study.ResultsSpirulina supplementation improved the concentration of volatile fatty acids and rumen papilla length. Additionally, there was a tendency for an increase in rumen weight and an upregulation of the genes Claudin-1, Claudin-4, and Occludin in the HFD+S group. Pyrosequencing of the 16S ribosomal RNA gene also showed that spirulina supplementation significantly changed the rumen microbiota composition in the HFD group, with a decrease in richness and diversity. Specifically, the relative abundance of Prevotella 9 and Megasphaera was significantly increased in the HFD group compared to the NCD group, while spirulina supplementation reversed these changes.DiscussionThis study suggests that 3% spirulina supplementation can improve rumen development and fermentation, and effectively relieve rumen microbe disorders in lambs caused by a high-fat diet. However, further research is needed to confirm the findings and to examine the long-term effects of spirulina supplementation in different types of livestock and under different dietary conditions.

Long non-coding RNAs (lncRNAs) regulate the development of follicles and reproductive diseases, but the mechanisms by which lncRNAs regulate ovarian functions and fertility remain elusive. We profiled the expression of lncRNAs in ovarian tissues of Hu sheep with different prolificacy and identified 21,327 lncRNAs. Many of the lncRNAs were differentially expressed in different groups. We further characterized an lncRNA that was predominantly expressed in the ovaries of the low prolificacy FecB+ (LPB+) group and mainly present in granulosa cells (GCs), and the expression of this lncRNA decreased during follicular development, which we named follicular development-associated lncRNA (FDNCR). Next, we found that FDNCR directly binds miR-543-3p, and decorin (DCN) was identified as a target of miR-543-3p. FDNCR overexpression promoted GC apoptosis through increased expression of DCN, which could be attenuated by miR-543-3p. Furthermore, miR-543-3p increased and FDNCR reduced the expression of transforming growth factor-β (TGF-β) pathway-related genes, including TGF-β1 and inhibin beta A (INHBA), which were upregulated upon DCN silencing. Our results demonstrated that FDNCR sponges miR-543-3p in GCs and prevents miR-543-3p from binding to the DCN 3′ UTR, resulting in DCN transactivation and TGF-β pathway inhibition and promotion of GC apoptosis in Hu sheep. These findings provide insights into the mechanisms underlying prolificacy in sheep.

With the intensification of climate change, the coupling effect between climate variables plays an important role in meteorological drought identification. However, little is known about the contribution of climate variables to drought development. This study constructed four scenarios using the random forest model during 1981–2016 in the Luanhe River Basin (LRB) and quantitatively revealed the contribution of climate variables (precipitation; temperature; wind speed; solar radiation; relative humidity; and evaporative demand) to drought indices and drought characteristics, that is, the Standard Precipitation Evapotranspiration Index (SPEI), Standard Precipitation Index (SPI), and Evaporative Demand Drought Index (EDDI). The result showed that the R2 of the model is above 0.88, and the performance of the model is good. The coupling between climate variables can not only amplify drought characteristics but also lead to the SPEI, SPI, and EDDI showing different drought states when identifying drought. With the decrease in timescale, the drought intensity of the three drought indices became stronger and the drought duration shortened, but the drought frequency increased. For short-term drought (1 mon), four scenarios displayed that the SPEI and SPI can identify more drought events. On the contrary, compared with the SPEI and SPI, the EDDI can identify long and serious drought events. This is mainly due to the coupling of evaporative demand, solar radiation, and wind speed. Evaporation demand also contributed to the SPEI, but the contribution (6–13%) was much less than the EDDI (45–85%). For SPEI-1, SPEI-3, and SPEI-6, the effect of temperature cannot be ignored. These results are helpful to understand and describe drought events for drought risk management under the condition of global warming.

DNA methylation plays an important role in biological processes by affecting gene expression. However, how DNA methylation regulates phenotypic variation in Hu sheep remains unclear. Therefore, we generated genome-wide DNA methylation and transcriptomic profiles in the ovaries of Hu sheep with different prolificacies and genotypes (FecBB and FecB+). Results showed that ovary DNA methylome and transcriptome were significantly different between high prolificacy and low prolificacy Hu sheep. Comparative methylome analyses identified 10,644, 9,594, and 12,214 differentially methylated regions and 87, 1,121, and 2,375 genes, respectively, showing differential expression levels in three different comparison groups. Female reproduction-associated differentially methylated regions-related genes and differentially expressed genes were enriched, thereby the respective interaction networks were constructed. Furthermore, systematical integrative analyses revealed a negative correlation between DNA methylation around the transcriptional start site and gene expression levels, which was confirmed by testing the expression of integrin β2 subunit (ITGB2) and lysosome-associated protein transmembrane-4 beta (LAPTM4B) in vivo and in vitro. These findings demonstrated that DNA methylation influences the propensity for prolificacy by affecting gene expression in the ovaries, which may contribute to a greater understanding of the epigenome and transcriptome that will be useful for animal breeding.

Induction of estrus is an effective management tool for increasing the pregnancy rate in ewes, and there is a long estrus interval after lambing in spring in Small-tail Han ewe. In this study, norgestrel releasing intra-vaginal devices (PRID) and PRID + pregnant mare serum gonadotrophin (PMSG) were used for estrus induction in Small-tail Han ewe, and expression of follicle-stimulating hormone receptor (FSHR), luteinizing hormone receptor (LHR), estrogen receptor (ER) and progesterone receptor (PGR) mRNA in the ovarial stroma, oviduct ampulla and endometrium was analyzed by quantitative real-time PCR. The results showed that the estrus-induction with PRID and PRID + PMSG almost had the same effects on increasing the percentage of animals in estrus and conception rate of the ewes, and the estrus-induction had no significant effect on the expression of LHR, ER and PGR mRNA in the oviduct ampulla, ovarial stroma and endometrium, and FSHR in the ovarial stroma and endometrium. Furthermore, the estrus-induction could significantly decrease the expression of FSHR mRNA in the ovine oviduct ampulla (P

Pituitary gonadotropins play a pivotal role in reproduction. Long noncoding RNAs (lncRNAs) have been identified as important regulators in the hypothalamic–pituitary–ovarian (HPO) axis associated with reproduction. However, the contributions of lncRNAs to pituitary gonadotropin secretion remain largely unknown. Therefore, this work was performed to uncover the functional mechanisms of the novel lncRNA TCONS_00083279 (lncRNA SM2) and its potential targeting pathway oar-miR-16b/TGF-beta/SMAD2, which is associated with gonadotropin secretion in sheep pituitary cells. In the present study, the lncRNA SM2 showed high expression levels in the sheep pituitary gland, and it was located in both the nucleus and the cytoplasm of pituitary cells. lncRNA SM2 knockdown inhibited pituitary cell proliferation and FSH and LH secretion. The function of the lncRNA SM2 was sponged by oar-miR-16b, and this regulated the growth and gonadotropin secretion of pituitary cells by modulating SMAD2, as shown by the dual-luciferase reporter assay. FSH and LH levels were both upregulated by SMAD2 overexpression. Moreover, the levels of the lncRNA SM2, SMAD2 and TGFR1, as well as FSH and LH, in sheep pituitary cells increased significantly under gonadotropin-releasing hormone (GnRH) stimulation (p < 0.05). This work illustrates that the lncRNA SM2 regulates gonadotropin secretion in the Hu sheep anterior pituitary by targeting the oar-miR-16b/TGF-β/SMAD2 signaling pathway, providing a valuable resource for understanding the molecular mechanisms underlying sheep reproduction.

The uterus, as part of the female reproductive tract, is essential for embryo survival and in the maintenance of multiple pregnancies in domestic animals. This study was conducted to investigate the effects of WNT6 on Hu sheep endometrial epithelial cells (EECs) and uterine glands (UGs) in Hu sheep, with high prolificacy rates. In the present study, Hu sheep with different fecundity, over three consecutive pregnancies, were divided into two groups: high prolificacy rate group (HP, litter size = 3) and low prolificacy rate group (LP, litter size = 1). A comparative analysis of the endometrial morphology was performed by immunofluorescence. RNA-seq was used to analyze the gene’s expression in endometrium of HP and LP Hu sheep, providing a candidate gene, which was investigated in EECs and organoid culture. Firstly, higher density of UGs was found in the HP Hu sheep groups (p < 0.05). The RNA-seq data revealed the importance of the WNT signaling pathway and WNT6 gene in Hu sheep endometrium. Functionally, WNT6 could promote the cell cycle progression of EECs via WNT/β-catenin signal and enhance UGs organogenesis. Taken together, WNT6 is a crucial regulator for sheep endometrial development; this finding may offer a new insight into understanding the regulatory mechanism of sheep prolificacy.

As the most direct indicator of drought, the dynamic assessment and prediction of actual evapotranspiration (AET) is crucial to regional water resources management. This research aims to develop a framework for the regional AET evaluation and prediction based on multiple machine learning methods and multi-source remote sensing data, which combines Boruta algorithm, Random Forest (RF), and Support Vector Regression (SVR) models, employing datasets from CRU, GLDAS, MODIS, GRACE (-FO), and CMIP6, covering meteorological, vegetation, and hydrological variables. To verify the framework, it is applied to grids of South America (SA) as a case. The results meticulously demonstrate the tendency of AET and identify the decisive role of T, P, and NDVI on AET in SA. Regarding the projection, RF has better performance in different input strategies in SA. According to the accuracy of RF and SVR on the pixel scale, the AET prediction dataset is generated by integrating the optimal results of the two models. By using multiple parameter inputs and two models to jointly obtain the optimal output, the results become more reasonable and accurate. The framework can systematically and comprehensively evaluate and forecast AET; although prediction products generated in SA cannot calibrate relevant parameters, it provides a quite valuable reference for regional drought warning and water allocating.

Reference evapotranspiration (ET0) in the hydrological cycle is one of the processes that is significantly affected by climate change. The Qinghai–Tibet Plateau (QTP) is universally recognized as a region that is sensitive to climate change. In this study, an area elevation curve is used to divide the study area into three elevation zones: low (below 2800 m), medium (2800–3800 m) and high (3800–5000 m). The cumulative anomaly curve, Mann–Kendall test, moving t-test and Yamamoto test results show that a descending mutation occurred in the 1980s, and an ascending mutation occurred in 2005. Moreover, a delay effect on the descending mutation in addition to an enhancement effect on the ascending mutation of the annual ET0 were coincident with the increasing altitude below 5000 m. The annual ET0 series for the QTP and different elevation zones showed an increasing trend from 1961 to 2017 and increased more significantly with the increase in elevation. Path analysis showed that the climate-driven patterns in different elevation zones are quite different. However, after the ascending mutations occurred in 2005, the maximum air temperature (Tmax) became the common dominant driving factor for the whole region and the three elevation zones.

Abstract Background Ovulation rate and litter size are important reproductive traits in sheep with high economic value. Recent work has revealed a potential link between DNA methylation and prolificacy. However, a genome-wide study that sought to identify potential DNA methylation sites involved in sheep prolificacy indicated that it is still unknown. Here, we aimed to investigate the genome-wide DNA methylation profiles of Hu sheep ovaries by comparing a high-prolificacy group (HP, litter size of three for at least 2 consecutive lambings) and low prolificacy group (LP, litter size of one for at least 2 consecutive lambings) using deep whole-genome bisulfite sequencing (WGBS). Results First, our results demonstrated lower expression levels of DNA methyltransferase (DNMT) genes in the ovaries of the HP group than that in the ovaries of the LP group. Both groups showed similar proportions of methylation at CpG sites but different proportions at non-CpG sites. Subsequently, we identified 70,899 differential methylated regions (DMRs) of CG, 16 DMRs of CHG, 356 DMRs of CHH and 12,832 DMR-related genes(DMGs). Gene Ontology (GO) analyses revealed that some DMGs were involved in regulating female gonad development and ovarian follicle development. Finally, we found that 10 DMGs, including BMP7, BMPR1B, CTNNB1, FST, FSHR, LHCGR, TGFB2 and TGFB3, are more likely to be involved in prolificacy of Hu sheep, as assessed by correlation analysis and listed in detail. Conclusions This study revealed the global DNA methylation pattern of sheep ovaries associated with high and low prolificacy groups, which may contribute to a better understanding of the epigenetic regulation of sheep reproductive capacity.

Abstract Background Cocaine- and amphetamine-regulated transcript (CART), discovered initially by via differential display RT-PCR analysis of brains of rats administered cocaine, is expressed mainly in central nervous system or neuronal origin cells, and is involved in a wide range of behaviors, such as regulation of food intake, energy homeostasis, and reproduction. The hens egg-laying rate mainly depends on the developmental status of follicles, expression of CART have not been identified from hen follicles, the regulatory mechanisms of CART biological activities are still unknown. The objective of this study was to characterize the mRNA expression of CART in hen follicular granulosa cells and determine CART peptide localization and regulatory role during follicular development. Methods Small white follicles (1–2 mm in diameter) were treated for RNA isolation; Small white follicles (1–2 mm in diameter) and large white follicles (4–6 mm in diameter) were treated for immunohistochemical localization and large white follicles (4–6 mm in diameter), small yellow follicles (6–8 mm in diameter), large yellow follicles (9–12 mm in diameter), mature follicles (F5, F4, F3, F2, F1, >12 mm in diameter) were treated for RNA isolation and Real time PCR. Results The results showed that full length of the CDS of hen CART was 336 bp encoding a 111 amino acid polypeptide. In the hen ovary, CART peptide was primarily localized to the theca layer, but not all, the oocyte and granulosa layer, with diffused, weaker staining than relative to the theca cell layer. Further, amount of CART mRNA was more (P

A gated recurrent unit (GRU) network, which is a kind of artificial neural network (ANN), has been increasingly applied to runoff forecasting. However, knowledge about the impact of different input data filtering strategies and the implications of different architectures on the GRU runoff forecasting model’s performance is still insufficient. This study has selected the daily rainfall and runoff data from 2007 to 2014 in the Wei River basin in Shaanxi, China, and assessed six different scenarios to explore the patterns of that impact. In the scenarios, four manually-selected rainfall or runoff data combinations and principal component analysis (PCA) denoised input have been considered along with single directional and bi-directional GRU network architectures. The performance has been evaluated from the aspect of robustness to 48 various hypermeter combinations, also, optimized accuracy in one-day-ahead (T + 1) and two-day-ahead (T + 2) forecasting for the overall forecasting process and the flood peak forecasts. The results suggest that the rainfall data can enhance the robustness of the model, especially in T + 2 forecasting. Additionally, it slightly introduces noise and affects the optimized prediction accuracy in T + 1 forecasting, but significantly improves the accuracy in T + 2 forecasting. Though with relevance (R = 0.409~0.763, Grey correlation grade >0.99), the runoff data at the adjacent tributary has an adverse effect on the robustness, but can enhance the accuracy of the flood peak forecasts with a short lead time. The models with PCA denoised input has an equivalent, even better performance on the robustness and accuracy compared with the models with the well manually filtered data; though slightly reduces the time-step robustness, the bi-directional architecture can enhance the prediction accuracy. All the scenarios provide acceptable forecasting results (NSE of 0.927~0.951 for T + 1 forecasting and 0.745~0.836 for T + 2 forecasting) when the hyperparameters have already been optimized. Based on the results, recommendations have been provided for the construction of the GRU runoff forecasting model.

Aimed at reducing simulation uncertainty of hydrological models in data-sparse basins where soil hydraulic data are unavailable, a method of estimating soil water parameters of soil and water assessment tool (SWAT) from readily available soil information using pedotransfer functions was introduced. The method was evaluated through a case study of Jinjiang Basin, China and was performed based on comparison between two model calibrations: (1) soil parameters estimated from pedotransfer functions and other parameters obtained from calibration; and (2) all parameters derived from calibration. The generalized likelihood uncertainty estimation (GLUE) was used as a model calibration and uncertainty analysis tool. The results show that information contained in streamflow data is insufficient to derive physically reasonable soil parameter values via calibration. The proposed method can reduce simulation uncertainty, resulting from greater average performance of behavioral parameter sets identified by GLUE. Exploring the parameter space reveals that the means of estimating soil parameters has little influence on other parameters. These facts indicate the decrease in uncertainty most likely results from a more realistic description of soil water characteristics than calibration. Thus, the proposed method is superior to calibration for estimating soil parameters of SWAT model when basin data are sparse.

Reference evapotranspiration (ET0) is a key factor in the hydrological cycle and energy cycle. In the context of rapid climate change, studying the dynamic changes in ET0 in the Tibetan Plateau (TP) is of great significance for water resource management in Asian countries. This study uses the Penman–Monteith formula to calculate the daily ET0 of the TP and subsequently uses the Mann–Kendall (MK) test, cumulative anomaly curve, and sliding t-test to identify abrupt change points. Morlet wavelet analysis and the Hurst index based on rescaled range analysis (R/S) are utilized to predict the future trends of ET0. The Spearman correlation coefficient is used to explore the relationship between ET0 changes and other climate factors. The results show that the ET0 on the TP exhibited an increasing trend from 1961 to 2017, with the most significant increase occurring in winter; an abrupt change to a tendency to decrease occurred in 1988, and another abrupt change to a tendency to increase occurred in 2005. Spatially, the ET0 of the TP shows an increasing trend from east to west. The change trend of the ET0 on the TP will not be sustainable into the future. In addition, the mean temperature has the greatest impact on the ET0 changes in the TP.

The Heihe River Basin (HRB) is the second largest inland river basin in China, characterized by high diversity in geomorphology and irrigated agriculture in middle reaches. To improve the knowledge about the relationship between biotic and hydrological processes, this study used Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (NDVI) data (1982-2006) to analyze spatiotemporal variations in vegetation growth by using the Mann-Kendall test together with Sen's slope estimator. The results indicate that 10.1% and 1.6% of basin area exhibit statistically significant (p < 0.05) upward and downward trends, and maximum magnitude is 0.066/10a and 0.026/10a, respectively. More specifically, an increasing trend was observed in the Qilian Mountains and Hexi Corridor and a decreasing trend detected in the transitional region between them. Increases in precipitation and temperature may be one possible reason for the changes of vegetation growth in the Qilian Mountains. And decreasing trend in transitional region may be driven by the changes in precipitation. Increases of irrigation contribute to the upward trend of NDVI for cropland in the Hexi Corridor, reflecting that agricultural development becomes more intensive. Our study demonstrates the complexity of the response of vegetation growth in the HRB to climate change and anthropogenic activities and correspondingly adopting mechanistic ecological models capable of describing both factors is favorable for reasonable predictions of future vegetation growth. It is also indicated that improving irrigation water use efficiency is one practical strategy to balance water demand between human and natural ecosystems in the HRB.

The influences of climate change on water resources availability in Jinjiang Basin, China, were assessed using the Block-wise use of the TOPmodel with the Muskingum-Cunge routing method (BTOPMC) distributed hydrological model. The ensemble average of downscaled output from sixteen GCMs (General Circulation Models) for A1B emission scenario (medium CO2 emission) in the 2050s was adopted to build regional climate change scenario. The projected precipitation and temperature data were used to drive BTOPMC for predicting hydrological changes in the 2050s. Results show that evapotranspiration will increase in most time of a year. Runoff in summer to early autumn exhibits an increasing trend, while in the rest period of a year it shows a decreasing trend, especially in spring season. From the viewpoint of water resource availability, it is indicated that it has the possibility that water resources may not be sufficient to fulfill irrigation water demand in the spring season and one possible solution is to store more water in the reservoir in previous summer.