Therapeutic potential of single-nucleotide polymorphism-mediated IL6R inhibitors in ankylosing spondylitis treatment.

Objective: Interleukin-6 (IL-6) is a multiple-effect cell factor implicated in the etiopathogenesis of several rheumatologic disorders. The blockade of the IL-6 pathway via IL6R inhibitors effectively treats these disorders. However, the clinical significance of the IL6R blockade for ankylosing spondylitis (AS) therapy remains controversial. With advances in genomics, increasing evidence has revealed the role of heritability in the etiology of disease, and Mendelian randomization (MR) analyses are being used more broadly to infer causation. Therefore, this MR study aims to evaluate the potential therapeutic utility of IL6R-targeted approaches in AS. Methods: The C-reactive protein (CRP) level was used as an exposure factor, and rheumatoid arthritis (RA) was used as a positive control. As-related genome-wide association study (GWAS) data were used as the primary outcome of drug-targeted MR analyses to test the relation between IL6R blockers and AS. Inverse variance weighting (IVW) is the primary analytical approach. Various sensitivity tests were performed to check the robustness and trustworthiness of the causality estimation, including consistency, heterogeneity, and pleiotropy analyses. In addition, repeated analysis was conducted using different GWAS data related to exposures and outcomes to examine the results for stability. Results: According to the IVW results, IL6R inhibitors significantly reduced the risk of AS in ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.996, P = 5.12 × 10-08) and ukb-a-88 (OR: 0.994, 95% CI 0.993-0.996, P = 6.25 × 10-15). Moreover, repeated analyses were performed using different exposure-related GWAS data, yielding similar results, ukb-b-18194 (OR: 0.995, 95% CI 0.993-0.997, P = 1.25 × 10-06) and ukb-a-88 (OR: 0.995, 95% CI 0.994-0.997, P = 7.81 × 10-09). Heterogeneity analyses and pleiotropy analyses indicated no significant heterogeneity or pleiotropy. Conclusion: This MR analysis result further validates that the IL-6 pathway may contribute to the pathogenesis of AS and that the inhibition of IL6R reduces the risk of AS. These findings may guide future studies and provide more favorable drug treatment options for people at high risk of AS.

Callicarpayongshunensis (Lamiaceae): A new species from Hunan, China.

This study provides detailed description of a newly-discovered Callicarpayongshunensis Wen B. Xu, Xiao D. Li & Yan Ling Liu (Lamiaceae) species from Hunan, China. The species shares similarities in the inflorescence, glandular colour and leaf shape features with C.luteopunctata H. T. Chang and C.giraldii Hesse ex Rehd., while its white fruits are similar to those of C.longifolia Lamk. However, its procumbent, evergreen shrub and white fruits are distinctly different from those of C.luteopunctata and C.giraldii, while its procumbent, scarless nodes and stellate pubescence free fruits distinguishes it from C.longifolia. Images, distribution, morphological features, molecular phylogenetic classification and conservation assessment of this new Callicarpa species are explored.

l-arginine promotes angio-osteogenesis to enhance oxidative stress-inhibited bone formation by ameliorating mitophagy.

Background: Osteoporosis is one of the most common bone diseases in middle-aged and elderly populations worldwide. The development of new drugs to treat the disease is a key focus of research. Current treatments for osteoporosis are mainly directed at promoting osteoblasts and inhibiting osteoclasts. However, there is currently no ideal approach for osteoporosis treatment. l-arginine is a semi-essential amino acid involved in a number of cellular processes, including nitric production, protein biosynthesis, and immune responses. We previously reported that l-arginine-derived compounds can play a regulatory role in bone homeostasis. Purpose: To investigate the specific effect of l-arginine on bone homeostasis. Methods: Mildly aged and ovariectomized mouse models were used to study the effects of l-arginine on osteogenesis and angiogenesis, assessed by micro-computed tomography and immunostaining of bone tissue. The effect of l-arginine on osteogenesis, angiogenesis, and adipogenesis was further studied in vitro using osteoblasts obtained from cranial cap bone, endothelial cells, and an adipogenic cell line. Specific methods to assess these processes included lipid staining, cell migration, tube-forming, and wound-healing assays. Protein and mRNA expression was determined for select biomarkers. Results: We found that l-arginine attenuated bone loss and promoted osteogenesis and angiogenesis. l-arginine increased the activity of vascular endothelial cells, whereas it inhibited adipogenesis in vitro. In addition, we found that l-arginine altered the expression of PINK1/Parkin and Bnip3 in the mitochondria of osteoblast-lineage and endothelial cells, thereby promoting mitophagy and protecting cells from ROS. Similarly, l-arginine treatment effectively ameliorated osteoporosis in an ovariectomized mouse model. Conclusion: l-arginine promotes angio-osteogenesis, and inhibits adipogenesis, effects mediated by the PINK1/Parkin- and Bnip3-mediated mitophagy. The Translational Potential of this Article: L-arginine supplementation may be an effective adjunct therapy in the treatment of osteoporosis.

IRF4-BLOC1S5: the first rearrangement gene identified in TEMPI syndrome.

Not available.

Indisulam synergizes with melphalan to inhibit Multiple Myeloma malignancy via targeting TOP2A.

Multiple myeloma (MM) is the second most prevalent hematologic malignancy which remains uncurable. Numerous drugs have been discovered to inhibit MM cells. Indisulam, an aryl sulfonamide, has a potent anti-myeloma activity in vitro and in vivo. This study aims to explore the new mechanism of indisulam and investigate its potential use in combination with melphalan. We examined DNA damage in MM cells through various methods such as western blotting (WB), immunofluorescence, and comet assay. We also identified the role of topoisomerase IIα (TOP2A) using bioinformatic analyses. The impact of indisulam on the RNA and protein levels of TOP2A was investigated through qPCR and WB. Cell proliferation and apoptosis were assessed using CCK-8 assays, Annexin V/PI assays and WB. We predicted the synergistic effect of the combination treatment based on calculations performed on a website, and further explored the effect of indisulam in combination with melphalan on MM cell lines and xenografts. RNA sequencing data and basic experiments indicated that indisulam caused DNA damage and inhibited TOP2A expression by decreasing transcription and promoting degradation via the proteasome pathway. Functional experiments revealed that silencing TOP2A inhibited cell proliferation and induced apoptosis and DNA damage. Finally, Indisulam/melphalan combination treatment demonstrated a strong synergistic anti-tumor effect compared to single-agent treatments in vitro and in vivo. These findings suggest that combination therapies incorporating indisulam and melphalan have the potential to enhance treatment outcomes for MM.

Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization.

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.

Electroacupuncture Alleviates Post-stroke Cognitive Impairment Through Inhibiting miR-135a-5p/mTOR/NLRP3 Axis-mediated Autophagy.

Post-stroke cognitive impairment is a significant challenge with limited treatment options. Electroacupuncture (EA) has shown promise in improving cognitive function after stroke. Our study explores the underlying mechanism of EA in alleviating cognitive impairment through the inhibition of autophagy. We utilized a rat model of stroke induced by middle cerebral artery occlusion (MCAO) to evaluate the efficacy of EA. Treatment with EA was observed to markedly improve cognitive function and reduce inflammation in MCAO rats, as evidenced by decreased neurological deficit scores, shorter latencies in the water maze test, and diminished infarct volumes. EA also attenuated tissue damage in the hippocampus and lowered the levels of pro-inflammatory cytokines and oxidative stress markers. Although autophagy was upregulated in MCAO rats, EA treatment suppressed this process, indicated by a reduction in autophagosome formation and alteration of autophagy-related protein expression. The protective effects of EA were reversed by the autophagy activator rapamycin. EA treatment elevated the levels of microRNA (miR)-135a-5p expression, and suppression of this elevation attenuated the remedial efficacy of EA in addressing cognitive impairment and inflammation. MiR-135a-5p targeted mammalian target of rapamycin (mTOR)/NOD-like receptor protein 3 (NLRP3) signaling to repress autophagy. EA treatment inhibits autophagy and alleviates cognitive impairment in post-stroke rats. It exerts its beneficial effects by upregulating miR-135a-5p and targeting the mTOR/NLRP3 axis.

A novel method for simultaneous detection of hematological tumors and infectious pathogens by metagenomic next generation sequencing of plasma.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) is valuable for pathogen identification; however, distinguishing between infectious diseases and conditions with potentially similar clinical manifestations, including malignant tumors, is challenging. Therefore, we developed a method for simultaneous detection of infectious pathogens and cancer in blood samples. METHODS: Plasma samples (n = 244) were collected from 150 and 94 patients with infections and hematological malignancies, respectively, and analyzed by mNGS for pathogen detection, alongside human tumor chromosomal copy number variation (CNV) analysis (≥5Mbp or 10Mbp CNV region). Further, an evaluation set, comprising 87 plasma samples, was analyzed by mNGS and human CNV analysis, to validate the feasibility of the method. RESULTS: Among 94 patients with hematological malignancy, sensitivity values of CNV detection for tumor diagnosis were 69.15 % and 32.98 % for CNV region 5Mbp and 10Mbp, respectively, with corresponding specificities of 92.62 % and 100 % in the infection group. Area under the ROC curve (AUC) values for 5Mbp and 10Mbp region were 0.825 and 0.665, respectively, which was a significant difference of 0.160 (95 % CI: 0.110-0.210; p < 0.001), highlighting the superiority of 5Mbp output region data. Six patients with high-risk CNV results were identified in the validation study: three with history of tumor treatment, two eventually newly-diagnosed with hematological malignancies, and one with indeterminate final diagnosis. CONCLUSIONS: Concurrent CNV analysis alongside mNGS for infection diagnosis is promising for detecting malignant tumors. We recommend adopting a CNV region of 10Mbp over 5Mbp for our model, because of the lower false-positive rate (FPR).

External validation of the prediction model of intradialytic hypotension: a multicenter prospective cohort study.

OBJECTIVE: Intradialytic hypotension (IDH) is a common and serious complication in patients with Maintenance Hemodialysis (MHD). The purpose of this study is to externally verify three IDH risk prediction models recently developed by Ma et al. and recalibrate, update and present the optimal model to improve the accuracy and applicability of the model in clinical environment. METHODS: A multicenter prospective cohort study of patients from 11 hemodialysis centers in Sichuan Province, China, was conducted using convenience sampling from March 2022 to July 2022, with a follow-up period of 1 month. Model performance was assessed by: (1) Discrimination: Evaluated through the computation of the Area Under Curve (AUC) and its corresponding 95% confidence intervals. (2) Calibration: scrutinized through visual inspection of the calibration plot and utilization of the Brier score. (3) The incremental value of risk prediction and the utility of updating the model were gauged using NRI (Net Reclassification Improvement) and IDI (Integrated Discrimination Improvement). Decision Curve Analysis (DCA) was employed to evaluate the clinical benefit of updating the model. RESULTS: The final cohort comprised 2235 individuals undergoing maintenance hemodialysis, exhibiting a 14.6% occurrence rate of IDH. The externally validated Area Under the Curve (AUC) values for the three original prediction models were 0.746 (95% CI: 0.718 to 0.775), 0.709 (95% CI: 0.679 to 0.739), and 0.735 (95% CI: 0.706 to 0.764) respectively. Conversely, the AUC value for the recalibrated and updated columnar plot model reached 0.817 (95% CI: 0.791 to 0.842), accompanied by a Brier score of 0.081. Furthermore, Decision Curve Analysis (DCA) exhibited a net benefit within the threshold probability range of 15.2% to 87.1%. CONCLUSION: Externally validated, recalibrated, updated, and presented IDH prediction models may serve as a valuable instrument for evaluating IDH risk in clinical practice. Furthermore, they hold the potential to guide clinical providers in discerning individuals at risk and facilitating judicious clinical intervention decisions.

Comparing Outcomes of Banana-Shaped and Straight Cages in Transforaminal Lumbar Interbody Fusion for Lumbar Degenerative Diseases: A Systematic Review and Meta-Analysis.

OBJECTIVE: This meta-analysis aims to refine the understanding of the optimal choice between different cage shapes in transforaminal lumbar interbody fusion (TLIF) by systematically comparing perioperative data, radiological outcomes, clinical results, and complications associated with banana-shaped and straight bullet cages. METHODS: A meticulous literature search encompassing PubMed, Embase, Scopus, Web of Science, China Knowledge Network, and Wanfang Data was executed up to October 5, 2023. Inclusion criteria focused on studies comparing banana-shaped and straight bullet cages in TLIF. The quality of included studies was assessed using appropriate tools such as the Newcastle-Ottawa Scale (NOS) for nonrandomized studies. Rigorous evaluations were performed for radiographic outcomes, including disc height (DH), segmental lordosis (SL), lumbar lordosis (LL), subsidence, and fusion rates. Clinical outcomes were meticulously evaluated using visual analogue scale (VAS), Oswestry Disability Index (ODI), and complications. RESULTS: The analysis incorporated 7 studies, involving 573 patients (297 with banana-shaped cages, 276 with straight cages), all with NOS ratings exceeding 5 stars. No statistically significant differences were observed in operative time, blood loss, or hospitalization between the 2 cage shapes. Banana-shaped cages exhibited greater changes in DH (p = 0.001), SL (p = 0.02), and LL (p = 0.01). Despite statistically higher changes in ODI for straight cages (26.33, p < 0.0001), the actual value remained similar to banana-shaped cages (26.15). Both cage types demonstrated similar efficacy in VAS, complication rates, subsidence, and fusion rates. CONCLUSION: Although banana-shaped cages can excel in restoring DH, SL, and LL, straight bullet cages can provide comparable functional improvements, pain relief, and complication rates.

Oncoprotein SET-associated transcription factor ZBTB11 triggers lung cancer metastasis.

Metastasis is the major cause of lung cancer-related death, but the mechanisms governing lung tumor metastasis remain incompletely elucidated. SE translocation (SET) is overexpressed in lung tumors and correlates with unfavorable prognosis. Here we uncover SET-associated transcription factor, zinc finger and BTB domain-containing protein 11 (ZBTB11), as a prometastatic regulator in lung tumors. SET interacts and collaborates with ZBTB11 to promote lung cancer cell migration and invasion, primarily through SET-ZBTB11 complex-mediated transcriptional activation of matrix metalloproteinase-9 (MMP9). Additionally, by transcriptional repression of proline-rich Gla protein 2 (PRRG2), ZBTB11 links Yes-associated protein 1 (YAP1) activation to drive lung tumor metastasis independently of SET-ZBTB11 complex. Loss of ZBTB11 suppresses distal metastasis in a lung tumor mouse model. Overexpression of ZBTB11 is recapitulated in human metastatic lung tumors and correlates with diminished survival. Our study demonstrates ZBTB11 as a key metastatic regulator and reveals diverse mechanisms by which ZBTB11 modulates lung tumor metastasis.

A nomogram prediction model for mild cognitive impairment in non-dialysis outpatient patients with chronic kidney disease.

BACKGROUND: The high prevalence of mild cognitive impairment (MCI) in non-dialysis individuals with chronic kidney disease (CKD) impacts their prognosis and quality of life. OBJECTIVE: This study aims to investigate the variables associated with MCI in non-dialysis outpatient patients with CKD and to construct and verify a nomogram prediction model. METHODS: 416 participants selected from two hospitals in Chengdu, between January 2023 and June 2023. They were categorized into two groups: the MCI group (n = 210) and the non-MCI (n = 206). Univariate and multivariate binary logistic regression analyses were employed to identify independent influences (candidate predictor variables). Subsequently, regression models was constructed, and a nomogram was drawn. The restricted cubic spline diagram was drawn to further analyze the relationship between the continuous numerical variables and MCI. Internally validated using a bootstrap resampling procedure. RESULTS: Among 416 patients, 210 (50.9%) had MCI. Logistic regression analysis revealed that age, educational level, occupational status, use of smartphones, sleep disorder, and hemoglobin were independent influencing factors of MCI (all p<.05). The model's area under the curve was 0.926,95% CI (0.902, 0.951), which was a good discriminatory measure; the Calibration curve, the Hosmer-Lemeshow test, and the Clinical Decision Curve suggested that the model had good calibration and clinical benefit. Internal validation results showed the consistency index was 0.926, 95%CI (0.925, 0.927). CONCLUSION: The nomogram prediction model demonstrates good performance and can be used for early screening and prediction of MCI in non-dialysis patients with CKD. It provides valuable reference for medical staff to formulate corresponding intervention strategies.

An edge cloud and Fibonacci-Diffie-Hellman encryption scheme for secure printer data transmission.

Network printers face increasing security threats from network attacks that can lead to sensitive information leakage and data tampering. To address these risks, we propose a novel Fibonacci-Diffie-Hellman (FIB-DH) encryption scheme using edge cloud collaboration. Our approach utilizes properties of third-order Fibonacci matrices combined with the Diffie-Hellman key exchange to encrypt printer data transmissions. The encrypted data is transmitted via edge cloud servers and verified by the receiver using inverse Fibonacci transforms. Our experiments demonstrate that the FIB-DH scheme can effectively improve printer data transmission security against common attacks compared to conventional methods. The results show reduced vulnerabilities to leakage and tampering attacks in our approach. This work provides an innovative application of cryptographic techniques to strengthen security for network printer communications.

Risk assessment of pesticide compounds: IPT and TCZ cause hepatotoxicity, activate stress pathway and affect the composition of intestinal flora in red swamp crayfish (Procambarusclarkii).

Isoprothiolane (IPT) and tricyclazole (TCZ) are widely used in rice farming and recently in combined rice-fish farming. However, co-cultured animals are affected by these pesticides. To investigate the organismal effects and toxicity of pesticides, crayfish were exposed to 0, 1, 10, or 100 ppt TCZ or IPT for 7 days. Pesticide bioaccumulation, survival rate, metabolic parameters, structure of intestinal flora, and antioxidant-, apoptosis-, and HSP-related gene expression were determined. Pesticide exposure caused bioaccumulation of IPT or TCZ in the hepatopancreas and muscles of crayfish; however, IPT bioaccumulation was higher than that of TCZ. Both groups showed significant changes in hepatopancreatic serum biochemical parameters. Mitochondrial damage and chromosomal agglutination were observed in hepatopancreatic cells exposed to 100 ppt IPT or TCZ. IPT induced more significant changes in serum biochemical parameters than TCZ. The results of intestinal flora showed that Vibro, Flavobacterium, Anaerorhabdus and Shewanella may have potential for use as a bacterial marker of TCZ and IPT. Antioxidant-, apoptosis-, and HSP-related gene expression was disrupted by pesticide exposure, and was more seriously affected by IPT. The results suggest that IPT or TCZ induce hepatopancreatic cell toxicity; however, IPT or TCZ content in dietary crayfish exposed to 1 ppt was below the food safety residue standard. The data indicated that IPT exposure may be more toxic than TCZ exposure in hepatopancreas and intestines and toxicity of organism are alleviated by activating the pathway of stress-response, providing an understanding of pesticide compounds in rice-fish farming and food safety.

Structural and functional analysis of transforming growth factor beta regulator 1 (TBRG1) in the red swamp crayfish Procambarus clarkii: The initial insight into TBRG1's role in invertebrate immunity.

The transforming growth factor beta regulator 1 (TBRG1) is a growth inhibitory protein that acts as a tumor suppressor in human cancers, gaining its name for the transcriptional regulation by TGF-ß. While extensive research has been conducted on the tumor-related function of TBRG1 in mammals, its significance in invertebrates remains largely unexplored. In this study, a homolog of TBRG1 was first structurally and functionally analyzed in the red swamp crayfish Procambarus clarkii. The full-length cDNA sequence was 2143 base pairs (bp) with a 1305 bp open reading frame (ORF) encoding a deduced protein of 434 amino acids (aa). The changes of PcTBRG1 transcripts upon immune challenges indicated its involvement in innate immunity. After knocking down PcTBRG1, the decline of bacteria clearance capacity revealed the participation of PcTBRG1 in the immune response. Furthermore, the downregulation of AMPs' expression after the cotreatment of RNAi and bacteria challenge suggested that PcTBRG1 might participate in innate immunity through regulating AMPs' expression. These results provided initial insight into the immune-related function of TBRG1 in invertebrates.

Exploring the cuproptosis-related molecular clusters in the peripheral blood of patients with amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive and lethal neurodegenerative disease. Several studies have suggested the involvement of cuproptosis in its pathogenesis. In this research, we intend to explore the cuproptosis-related molecular clusters in ALS and develop a novel cuproptosis-related genes prediction model. METHODS: The peripheral blood gene expression data was downloaded from the Gene Expression Omnibus (GEO) online database. Based on the GSE112681 dataset, we investigated the critical cuproptosis-related genes (CuRGs) and pathological clustering of ALS. The immune microenvironment features of the peripheral blood in ALS patients were also examined using the CIBERSORT algorithm. Cluster-specific hub genes were determined by the WGCNA. The most accurate prediction model was selected by comparing the performance of four machine learning techniques. ROC curves and two independent datasets were applied to validate the prediction accuracy. The available compounds targeting these hub genes were filtered to investigate their efficacy in treating ALS. RESULTS: We successfully determined four critical cuproptosis-related genes and two pathological clusters with various immune profiles and biological characteristics in ALS. Functional analysis showed that genes in Cluster1 were primarily enriched in pathways closely associated with immunity. The Support Vector Machine (SVM) model exhibited the best discrimination properties with a large area under the curve (AUC = 0.862). Five hub prediction genes (BAP1, SMG1, BCLAF1, DHX15, EIF4G2) were selected to establish a nomogram model, suggesting significant risk prediction potential for ALS. The accuracy of this model in predicting ALS incidence was also demonstrated through calibration curves, nomograms, and decision curve analysis. Finally, three drugs targeting BAP1 were determined through drug-gene interactions. CONCLUSION: This study elucidated the complex associations between cuproptosis and ALS and constructed a satisfactory predictive model to explore the pathological characteristics of different clusters in ALS patients.

Automatic segmentation of brain glioma based on XY-Net.

Glioma is a malignant primary brain tumor, which can easily lead to death if it is not detected in time. Magnetic resonance imaging is the most commonly used technique to diagnose gliomas, and precise outlining of tumor areas from magnetic resonance images (MRIs) is an important aid to physicians in understanding the patient's condition and formulating treatment plans. However, relying on radiologists to manually depict tumors is a tedious and laborious task, so it is clinically important to investigate an automated method for outlining glioma regions in MRIs. To liberate radiologists from the heavy task of outlining tumors, we propose a fully convolutional network, XY-Net, based on the most popular U-Net symmetric encoder-decoder structure to perform automatic segmentation of gliomas. We construct two symmetric sub-encoders for XY-Net and build interconnected X-shaped feature map transmission paths between the sub-encoders, while maintaining the feature map concatenation between each sub-encoder and the decoder. Moreover, a loss function composed of the balanced cross-entropy loss function and the dice loss function is used in the training task of XY-Net to solve the class unevenness problem of the medical image segmentation task. The experimental results show that the proposed XY-Net has a 2.16% improvement in dice coefficient (DC) compared to the network model with a single encoder structure, and compare with some state-of-the-art image segmentation methods, XY-Net achieves the best performance. The DC, HD, recall, and precision of our method on the test set are 74.49%, 10.89 mm, 78.06%, and 76.30%, respectively. The combination of sub-encoders and cross-transmission paths enables the model to perform better; based on this combination, the XY-Net achieves an end-to-end automatic segmentation of gliomas on 2D slices of MRIs, which can play a certain auxiliary role for doctors in grasping the state of illness.

Reticulate evolution of the tertiary relict Osmanthus.

When interspecific gene flow is common, species relationships are more accurately represented by a phylogenetic network than by a bifurcating tree. This study aimed to uncover the role of introgression in the evolution of Osmanthus, the only genus of the subtribe Oleinae (Oleaceae) with its distribution center in East Asia. We built species trees, detected introgression, and constructed networks using multiple kinds of sequencing data (whole genome resequencing, transcriptome sequencing, and Sanger sequencing of nrDNA) combined with concatenation and coalescence approaches. Then, based on well-understood species relationships, historical biogeographic analyses and diversification rate estimates were employed to reveal the history of Osmanthus. Osmanthus originated in mid-Miocene Europe and dispersed to the eastern Tibetan Plateau in the late Miocene. Thereafter, it continued to spread eastwards. Phylogenetic conflict is common within the 'Core Osmanthus' clade and is seen at both early and late stages of diversification, leading to hypotheses of net-like species relationships. Incomplete lineage sorting proved ineffective in explaining phylogenetic conflicts and thus supported introgression as the main cause of conflicts. This study elucidates the diversification history of a relict genus in the subtropical regions of eastern Asia and reveals that introgression had profound effects on its evolutionary history.

Comparative analysis of hepatic transcriptomes and metabolomes of Changshun green-shell laying hens based on different green eggshell color intensities.

The eggshell color of avian species is an important trait that is predominantly determined by the pigments biliverdin and protoporphyrin. Various factors affect eggshell pigment deposition and coloration; however, the underlying mechanisms remain unclear. We analyzed the hepatic transcriptomes and metabolomes of Changshun green-shell hens laying dark green and light green eggs to investigate the potential role of the liver in regulating the intensity of the green eggshell color. In total, 350 differentially expressed genes and 211 differentially altered metabolites were identified. Gene set enrichment analysis revealed that the enriched pathways and Gene Ontology (GO) terms were mainly associated with energy, immunity, and nutrient metabolism. Metabolite set enrichment analysis revealed that the enriched pathways were mainly associated with amino acid, vitamin, bile acid, and lipid metabolism. Moreover, gene-metabolite interaction network analysis revealed 1 subnetwork. Most genes and metabolites in this subnetwork were determined to be related to melanin metabolism and transport. In conclusion, our results suggest that hepatic melanin metabolism and transport are critical for eggshell coloration. Six candidate genes (CDKN2B, DDC, PYCR1, ABCG5, SLC3A1, and P2RX2) and 7 candidate metabolites (serotonin, 5-hydroxyindoleacetic acid, ornithine, acetylcholine, L-tryptophan, D-ornithine, and ADP) were suggested to play important roles in this process. Meanwhile, this study suggests that changes in hepatic energy metabolism, immune status, antioxidation activity, nutrient availability, and bile acid synthesis can impair eggshell coloration.