Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles.

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

Diagnosis of Major Depressive Disorder Using Machine Learning Based on Multisequence MRI Neuroimaging Features.

BACKGROUND: Previous studies have found qualitative structural and functional brain changes in major depressive disorder (MDD) patients. However, most studies ignored the complementarity of multisequence MRI neuroimaging features and cannot determine accurate biomarkers. PURPOSE: To evaluate machine-learning models combined with multisequence MRI neuroimaging features to diagnose patients with MDD. STUDY TYPE: Prospective. SUBJECTS: A training cohort including 111 patients and 90 healthy controls (HCs) and a test cohort including 28 patients and 22 HCs. FIELD STRENGTH/SEQUENCE: A 3.0 T/T1-weighted imaging, resting-state functional MRI with echo-planar sequence, and single-shot echo-planar diffusion tensor imaging. ASSESSMENT: Recruitment and integration were used to reflect the dynamic changes of functional networks, while gray matter volume and fractional anisotropy were used to reflect the changes in the morphological and anatomical network. We then fused features with significant differences in functional, morphological, and anatomical networks to evaluate a random forest (RF) classifier to diagnose patients with MDD. Furthermore, a support vector machine (SVM) classifier was used to verify the stability of neuroimaging features. Linear regression analyses were conducted to investigate the relationships among multisequence neuroimaging features and the suicide risk of patients. STATISTICAL TESTS: The comparison of functional network attributes between patients and controls by two-sample t-test. Network-based statistical analysis was used to identify structural and anatomical connectivity changes between MDD and HCs. The performance of the model was evaluated by receiver operating characteristic (ROC) curves. RESULTS: The performance of the RF model integrating multisequence neuroimaging features in the diagnosis of depression was significantly improved, with an AUC of 93.6%. In addition, we found that multisequence neuroimaging features could accurately predict suicide risk in patients with MDD (r = 0.691). DATA CONCLUSION: The RF model fusing functional, morphological, and anatomical network features performed well in diagnosing patients with MDD and provided important insights into the pathological mechanisms of MDD. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.

Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network.

BACKGROUND: Characterization of the dynamics of functional brain network has gained increased attention in the study of depression. However, most studies have focused on single temporal dimension, while ignoring spatial dimensional information, hampering the discovery of validated biomarkers for depression. PURPOSE: To integrate temporal and spatial functional MRI variability features of dynamic brain network in machine-learning techniques to distinguish patients with major depressive disorder (MDD) from healthy controls (HCs). STUDY TYPE: Prospective. POPULATION: A discovery cohort including 119 patients and 106 HCs and an external validation cohort including 126 patients and 124 HCs from Rest-meta-MDD consortium. FIELD STRENGTH/SEQUENCE: A 3.0 T/resting-state functional MRI using the gradient echo sequence. ASSESSMENT: A random forest (RF) model integrating temporal and spatial variability features of dynamic brain networks with separate feature selection method (MSFS ) was implemented for MDD classification. Its performance was compared with three RF models that used: temporal variability features (MTVF ), spatial variability features (MSVF ), and integrated temporal and spatial variability features with hybrid feature selection method (MHFS ). A linear regression model based on MSFS was further established to assess MDD symptom severity, with prediction performance evaluated by the correlations between true and predicted scores. STATISTICAL TESTS: Receiver operating characteristic analyses with the area under the curve (AUC) were used to evaluate models' performance. Pearson's correlation was used to assess relationship of predicted scores and true scores. P < 0.05 was considered statistically significant. RESULTS: The model with MSFS achieved the best performance, with AUCs of 0.946 and 0.834 in the discovery and validation cohort, respectively. Additionally, altered temporal and spatial variability could significantly predict the severity of depression (r = 0.640) and anxiety (r = 0.616) in MDD. DATA CONCLUSION: Integration of temporal and spatial variability features provides potential assistance for clinical diagnosis and symptom prediction of MDD. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

Estimates of genomic inbreeding and identification of candidate regions in Beijing-You chicken populations.

Runs of homozygosity (ROHs) has become an effective method for analysing inbreeding in livestock populations. Moreover, ROHs is well-suited to detect signatures of selection via ROH islands. This study aimed to investigate the occurrence and distribution of ROHs, compare the genomic inbreeding coefficients and identify the genomic regions with high ROH frequencies in different Beijing-You chicken (BY) populations, including a random conservation population (BY_R), a pedigree conservation population (BY_P), and a commercial population obtained from the market (BY_C). Among them, BY_R in 2010 and 2019 were BY_R1 and BY_R2 respectively. A total of 27 916 ROHs were identified. The average number of ROHs per individual across the three BY populations ranged from 213 (BY_P) to 161 (BY_C), and the average length of ROHs ranged from 0.432 Mb (BY_R2) to 0.451 Mb (BY_P). The highest inbreeding coefficient calculated based on ROHs (FROH ) was 0.1 in BY_P, whereas the lowest FROH was 0.0743 in BY_C. In addition, the inbreeding coefficient of BY_R2 (FROH  = 0.0798) was higher than that of BY_R1 (FROH  = 0.0579). Furthermore, the highest proportion of long ROH fragments (>4 Mb) was observed in BY_P and BY_C. This study showed the top 10 ROH islands of each population, and these ROH islands harboured 53 genes, some of which were related to limb development, body size and immune response. These findings contribute to the understanding of genetic diversity and population demography, and might help improve breeding and conservation strategies for BY populations.

Small-Signal Stability Analysis and MOSMA-Based Optimization Control Strategy of OWF with MMC-HVDC Grid Connection.

The recent oscillation events in offshore wind farms (OWFs) connected via a modular multilevel-converter-based HVDC (MMC-HVDC) system are developing towards a wider frequency band, which causes complex a small-signal interaction phenomenon and difficulties in the stability analysis and control. In this paper, the wideband dynamic interaction mechanism is investigated based on the impedance analysis method and an improved control strategy using an optimization algorithm is proposed to improve the small-signal stability and reduce the oscillation risks. First, the detailed impedance models of the grid-connected system are established considering the distribution characteristics of the submarine cable, control delay and frequency coupling effect. Then, combined with the active damping control method, the wideband resonance mechanism is analyzed, and the stability constraints of controller parameters are obtained using the impedance stability criterion. Finally, an improved multi-objective slime mold algorithm (MOSMA)-based coordinated optimization control strategy is proposed to enhance the adaptability of the controller parameters and the wideband damping ability of a grid-connected system, which can improve the wideband stability of the system. The simulation and experimental results verify the proposed control strategy.

Gene Co-Expression Network Analysis Reveals the Hub Genes and Key Pathways Associated with Resistance to Salmonella Enteritidis Colonization in Chicken.

Salmonella negatively impacts the poultry industry and threatens animals' and humans' health. The gastrointestinal microbiota and its metabolites can modulate the host's physiology and immune system. Recent research demonstrated the role of commensal bacteria and short-chain fatty acids (SCFAs) in developing resistance to Salmonella infection and colonization. However, the complex interactions among chicken, Salmonella, host-microbiome, and microbial metabolites remain unelucidated. Therefore, this study aimed to explore these complex interactions by identifying the driver and hub genes highly correlated with factors that confer resistance to Salmonella. Differential gene expression (DEGs) and dynamic developmental genes (DDGs) analyses and weighted gene co-expression network analysis (WGCNA) were performed using transcriptome data from the cecum of Salmonella Enteritidis-infected chicken at 7 and 21 days after infection. Furthermore, we identified the driver and hub genes associated with important traits such as the heterophil/lymphocyte (H/L) ratio, body weight post-infection, bacterial load, propionate and valerate cecal contents, and Firmicutes, Bacteroidetes, and Proteobacteria cecal relative abundance. Among the multiple genes detected in this study, EXFABP, S100A9/12, CEMIP, FKBP5, MAVS, FAM168B, HESX1, EMC6, and others were found as potential candidate gene and transcript (co-) factors for resistance to Salmonella infection. In addition, we found that the PPAR and oxidative phosphorylation (OXPHOS) metabolic pathways were also involved in the host's immune response/defense against Salmonella colonization at the earlier and later stage post-infection, respectively. This study provides a valuable resource of transcriptome profiles from chicken cecum at the earlier and later stage post-infection and mechanistic understanding of the complex interactions among chicken, Salmonella, host-microbiome, and associated metabolites.

Switchable Tuning CO2 Hydrogenation Selectivity by Encapsulation of the Rh Nanoparticles While Exposing Single Atoms.

The switch of CO2 hydrogenation selectivity from CH4 to CO over TiO2 supported Rh catalysts is accomplished via selective encapsulation of Rh nanoparticles while exposing Rh single atoms by high-temperature reduction (HTR) according to their different strong metal-support interaction (SMSI) occurrence conditions, which can be reversed by subsequent oxidation treatment.

SPOP promotes ubiquitination and degradation of MyD88 to suppress the innate immune response.

As a canonical adaptor for the Toll-like receptor (TLR) family, myeloid differentiation primary response protein 88 (MyD88) has crucial roles in host defense against infection by microbial pathogens, and its dysregulation might induce autoimmune diseases. Here, we demonstrate that the chicken Cullin 3-based ubiquitin ligase adaptor Speckle-type BTB-POZ protein (chSPOP) recognizes the intermediate domain of chicken MyD88 (chMyD88) and degrades it through the proteasome pathway. Knockdown or genetic ablation of chSPOP leads to aberrant elevation of chMyD88 protein. Through this interaction, chSPOP negatively regulates NF-κB pathway activity and thus the production of IL-1ß upon LPS challenge in chicken macrophages. Furthermore, Spop-deficient mice are more susceptible to infection with Salmonella typhimurium. Collectively, these findings demonstrate MyD88 as a bona fide substrate of SPOP and uncover a mechanism by which SPOP regulates MyD88 abundance and disease susceptibility.

Comparison of genomic prediction methods for residual feed intake in broilers.

Residual feed intake (RFI) is a measure of the feed efficiency of animals. Previous studies have identified SNPs associated with RFI. The objective of this study was to compare the GBLUP model with the GA-BLUP model including previously identified associated SNPs. The nine associated SNPs were obtained from the genome-wide association study on a discovery population as preselection information. These models were analysed using ASREML software using a 5-fold cross-validation method on a validation population. With the genetic architecture (GA) matrix used, which was conducted with the nine RFI-associated SNPs, the prediction accuracy of RFI was improved compared with the original GBLUP model. The calculated optimal ω was 0.981 for RFI, which is in line with the optimal range from 0.9 to 1.0 in the gradient test. The prediction accuracy increased by 2% in the GA-BLUP model with ω being 0.981 compared with the GBLUP model. In conclusion, the GA-BLUP with the nine RFI-associated SNPs and an optimal ω can improve the prediction accuracy for a specific trait compared with GBLUP.

Effects of rapamycin and OSI-027 on α-SMA in lung tissue of SD rat pups with hyperoxic lung injury.

OBJECTIVE: To investigate the effect and significance of mammalian target of rapamycin (mTOR) inhibitors on the expression of α-SMA in lung injury induced by high volume fraction of inspired oxygen (hyperoxygen) in SD rat pups. METHODS: Seventy-two Sprague-Dawley rat pups (age: 3 weeks) were randomly divided into air + saline, hyperoxia + saline, hyperoxia + OSI-027, and hyperoxia + rapamycin groups. Animal models were constructed (n = 18). Hyperoxia was induced by continuous administration of 90% oxygen. Normal saline, OSI-027, and rapamycin are administered by intraperitoneal injection on 1d, 3d, 6d, 8d, 10d, 13d of the observation period, respectively. Following assessments were made on the 3rd, 7th, and 14th day of modeling: pathological changes in lung tissues, lung injury score, Western Blot to assess the distribution and expressions of mTOR, pS6K1, and α-SMA protein in lung tissues. RESULTS: In terms of time factors, the protein expressions of mTOR, pS6K1, and α-SMA increased with time. Except for the air group, the lung injury scores of the other groups increased with time, In terms of grouping factors, lung injury score in the air group was significantly lower than that in the other groups. In the hyperoxia group, the protein expressions of mTOR, PS6K1, and α-SMA were significantly higher than those in the other groups. The lung injury score in the hyperoxia group was significantly higher than that in the other groups. The lung injury score in the hyperoxia OSI group was significantly lower than that in the hyperoxia rapamycin group. CONCLUSION: In hyperoxia lung injury, inhibiting the activation of mTOR signaling pathway can effectively reduce the expression of α-SMA; however, only mTORC1/2 dual inhibitor OSI-027 exhibited an anti-proliferative effect, and alleviated hyperoxia-induced lung injury and fibrosis in SD rat pups.

Identification of QTL regions and candidate genes for growth and feed efficiency in broilers.

BACKGROUND: Feed accounts for about 70% of the total cost of poultry meat production. Residual feed intake (RFI) has become the preferred measure of feed efficiency because it is phenotypically independent of growth rate and body weight. In this study, our aim was to estimate genetic parameters and identify quantitative trait loci (QTL) for feed efficiency in 3314 purebred broilers using a genome-wide association study. Broilers were genotyped using a custom 55 K single nucleotide polymorphism (SNP) array. RESULTS: Estimates of genomic heritability for seven growth and feed efficiency traits, including body weight at 28 days of age (BW28), BW42, average daily feed intake (ADFI), RFI, and RFI adjusted for weight of abdominal fat (RFIa), ranged from 0.12 to 0.26. Eleven genome-wide significant SNPs and 15 suggestively significant SNPs were detected, of which 19 clustered around two genomic regions. A region on chromosome 16 (2.34-2.66 Mb) was associated with both BW28 and BW42, and the most significant SNP in this region, AX_101003762, accounted for 7.6% of the genetic variance of BW28. The other region, on chromosome 1 (91.27-92.43 Mb) was associated with RFI and ADFI, and contains the NSUN3 and EPHA6 as candidate genes. The most significant SNP in this region, AX_172588157, accounted for 4.4% of the genetic variance of RFI. In addition, a genomic region containing the gene AGK on chromosome 1 was found to be associated with RFIa. The NSUN3 and AGK genes were found to be differentially expressed in breast muscle, thigh muscle, and abdominal fat between male broilers with high and low RFI. CONCLUSIONS: We identified QTL regions for BW28 and BW42 (spanning 0.32 Mb) and RFI (spanning 1.16 Mb). The NSUN3, EPHA6, and AGK were identified as the most likely candidate genes for these QTL. These genes are involved in mitochondrial function and behavioral regulation. These results contribute to the identification of candidate genes and variants for growth and feed efficiency in poultry.

Genome-Wide Detection of Key Genes and Epigenetic Markers for Chicken Fatty Liver.

Chickens are one of the most important sources of meat worldwide, and the occurrence of fatty liver syndrome (FLS) is closely related to production efficiency. However, the potential mechanism of FLS remains poorly understood. An integrated analysis of data from whole-genome bisulfite sequencing and long noncoding RNA (lncRNA) sequencing was conducted. A total of 1177 differentially expressed genes (DEGs) and 1442 differentially methylated genes (DMGs) were found. There were 72% of 83 lipid- and glucose-related genes upregulated; 81% of 150 immune-related genes were downregulated in fatty livers. Part of those genes was within differentially methylated regions (DMRs). Besides, sixty-seven lncRNAs were identified differentially expressed and divided into 13 clusters based on their expression pattern. Some lipid- and glucose-related lncRNAs (e.g., LNC_006756, LNC_012355, and LNC_005024) and immune-related lncRNAs (e.g., LNC_010111, LNC_010862, and LNC_001272) were found through a co-expression network and functional annotation. From the expression and epigenetic profiles, 23 target genes (e.g., HAO1, ABCD3, and BLMH) were found to be hub genes that were regulated by both methylation and lncRNAs. We have provided comprehensive epigenetic and transcriptomic profiles on FLS in chicken, and the identification of key genes and epigenetic markers will expand our understanding of the molecular mechanism of chicken FLS.

A new chicken 55K SNP genotyping array.

BACKGROUND: China has the richest local chicken breeding resources in the world and is the world's second largest producer of meat-type chickens. Development of a moderate-density SNP array for genetic analysis of chickens and breeding of meat-type chickens taking utility of those resources is urgently needed for conventional farms, breeding industry, and research areas. RESULTS: Eight representative local breeds or commercial broiler lines with 3 pools of 48 individuals within each breed/line were sequenced and supplied the major SNPs resource. There were 7.09 million - 9.41 million SNPs detected in each breed/line. After filtering using multiple criteria such as preferred incorporation of trait-related SNPs and uniformity of distribution across the genome, 52.18 K SNPs were selected in the final array. It consists of: (i) 19.22 K SNPs from the genomes of yellow-feathered, cyan-shank partridge and white-feathered chickens; (ii) 5.98 K SNPs related to economic traits from the Illumina 60 K SNP Bead Chip, which were found as significant associated SNPs with 15 traits in a Beijing-You crossed Cobb F2 resource population by genome-wide association study analysis; (iii) 7.63 K SNPs from 861 candidate genes of economic traits; (iv) the 0.94 K SNPs related to residual feed intake; and (v) 18.41 K from chicken SNPdb. The polymorphisms of 9 extra local breeds and 3 commercial lines were examined with this array, and 40 K - 47 K SNPs were polymorphic (with minor allele frequency > 0.05) in those breeds. The MDS result showed that those breeds can be clearly distinguished by this newly developed genotyping array. CONCLUSIONS: We successfully developed a 55K genotyping array by using SNPs segregated from typical local breeds and commercial lines. Compared to the existing Affy 600 K and Illumina 60 K arrays, there were 21,41 K new SNPs included on our Affy 55K array. The results of the 55K genotyping data can therefore be imputed to high-density SNPs genotyping data. The array offers a wide range of potential applications such as genomic selection breeding, GWAS of interested traits, and investigation of diversity of different chicken breeds.

A 4-gene prognostic signature predicting survival in hepatocellular carcinoma.

OBJECTIVE: To develop an independent prognostic signature for patients with hepatocellular carcinoma (HCC). METHODS: HCC gene expression profile the cancer genome atlas-liver hepatocellular carcinoma and GSE14520 were used as discovery and test set, respectively. Differentially expressed genes (DEGs) were identified between HCC tissues and adjacent normal liver tissues. Univariate Cox proportional hazards regression analysis was performed to identify DEGs correlated with survival of HCC patients. A 4-gene-based signature was constructed based on a least absolute shrinkage and selection operator Cox penalized regression model. The predictive value of the signature was analyzed and validated. RESULTS: Two hundred sixty-three DEGs were identified between HCC and adjacent liver tissues. After univariate survival analysis, 90 DEGs were found to be significantly correlated with the overall survival (OS) of HCC patients, of which 4 genes (KPNA2, CDC20, SPP1, and TOP2A) with non-zero coefficient were used to construct a prognostic signature. The 4-gene signature was significantly associated with the age (P = 0.046), grade ( P = 0.022), and T stage ( P = 0.023) of HCC patients in the discovery set and it also significantly associated with TNM stage ( P = 0.033), and serum alpha-fetoprotein lever ( P = 0.034). Patients in the 4-gene low-risk group were associated with better OS and recurrence-free survival (RFS) than those in the high-risk group in the discovery and test set. Meanwhile, the 4-gene signature is an independent prognostic factor regarding OS and RFS in the discovery and test set. CONCLUSION: We developed a 4-gene-based signature, which could be a candidate prognostic factor for patients with HCC.

Decreased testosterone levels after caponization leads to abdominal fat deposition in chickens.

BACKGROUND: Caponization results in reduced androgen levels, which leads to abdominal fat accumulation in capons. In this study, we sought to understand the molecular mechanisms behind this fat accumulation. RESULTS: Abdominal fat (AF) content increased significantly (P < 0.05) and serum and AF testosterone levels decreased significantly (P < 0.05 or P < 0.01) after caponization. In AF tissue, 90 differentially expressed genes related to lipid metabolism were screened by gene expression profiling in caponized and sham-treated chickens. Among these, six representative genes were significantly up-regulated (APOA1, SCD, FABP7, RXRG, and FADS2) or down-regulated (FABP3) (P < 0.05 or P < 0.01) and were strongly associated with the PPAR pathway. In addition, cell junction pathways were also enriched. In vitro, Fat content was significantly lower in cells treated with testosterone compared with control cells (P < 0.01), and mRNA levels of RXRG, FABP7, and FABP3 changed accordingly, confirming the effect of testosterone on fat deposition. CONCLUSIONS: The results of this study indicate that testosterone reduction likely regulates gene expression through PPAR and cell junction pathways resulting in increased fat accumulation. These results provide increase our understanding of the biological mechanisms by which caponization induces greater fat accumulation.

Intramuscular preadipocytes impede differentiation and promote lipid deposition of muscle satellite cells in chickens.

BACKGROUND: Skeletal muscle satellite cells (MSC) are crucial for postnatal growth and regeneration of skeletal muscle. An interaction exists between MSC and intramuscular preadipocytes (IMPA). This study is the first to investigate the effects of IMPA on MSC in chickens and unveil the molecular mechanisms by transcriptome analysis. RESULTS: Primary MSC and IMPA were isolated from the pectoralis major muscle of 7-day-old chickens. After both cell types reached confluence, MSC were cultured alone or co-cultured with IMPA for 2 or 4 d. MSC treated for 2 d were subjected to RNA-seq. A total of 1653 known differentially expressed genes (DEG) were identified between co-cultured and mono-cultured MSC (|log2 FC| ≥ 1, FDR < 0.01). Based on Gene Ontology analysis, 48 DEG related to muscle development were screened, including the key genes MYOD1, MYOG, PAX7, and TMEM8C. The 44 DEG related to lipid deposition included the key genes CD36, FABP4, ACSBG2, CYP7A1 and PLIN2. Most of the DEG related to muscle development were downregulated in co-cultured MSC, and DEG related to lipid deposition were upregulated. Immunofluorescence of MHC supported IMPA impeding differentiation of MSC, and Oil Red O staining showed concurrent promotion of lipid deposition. Pathway analysis found that several key genes were enriched in JNK/MAPK and PPAR signaling, which may be the key pathways regulating differentiation and lipid deposition in MSC. Additionally, pathways related to cell junctions may also contribute to the effect of IMPA on MSC. CONCLUSIONS: The present study showed that IMPA impeded differentiation of MSC while promoting their lipid deposition. Pathway analysis indicated that IMPA might inhibit differentiation via the JNK/MAPK pathway, and promote lipid deposition via the PPAR pathway. This study supplies insights into the effect of IMPA on MSC, providing new clues on exposing the molecular mechanisms underlying the interplay between skeletal muscle and intramuscular fat in chickens.

Uncovering the embryonic development-related proteome and metabolome signatures in breast muscle and intramuscular fat of fast-and slow-growing chickens.

BACKGROUND: Skeletal muscle development is closely linked to meat production and its quality. This study is the first to quantify the proteomes and metabolomes of breast muscle in two distinct chicken breeds at embryonic day 12 (ED 12), ED 17, post-hatch D 1 and D 14 using mass spectrometry-based approaches. RESULTS: Results found that intramuscular fat (IMF) accumulation increased from ED 17 to D 1 and that was exactly the opposite of when most obvious growth of muscle occurred (ED 12 - ED 17 and D 1 - D 14). For slow-growing Beijing-You chickens, Ingenuity Pathway Analysis of 77-99 differential abundance (DA) proteins and 63-72 metabolites, indicated significant enrichment of molecules and pathways related to protein processing and PPAR signaling. For fast-growing Cobb chickens, analysis of 68-95 DA proteins and 56-59 metabolites demonstrated that molecules and pathways related to ATP production were significantly enriched after ED12. For IMF, several rate-limiting enzymes for beta-oxidation of fatty acid (ACADL, ACAD9, HADHA and HADHB) were identified as candidate biomarkers for IMF deposition in both breeds. CONCLUSIONS: This study found that ED 17 - D 1 was the earliest period for IMF accumulation. Pathways related to protein processing and PPAR signaling were enriched to support high capacity of embryonic IMF accumulation in Beijing-You. Pathways related to ATP production were enriched to support the fast muscle growth in Cobb. The beta-oxidation of fatty acid is identified as the key pathway regulating chicken IMF deposition at early stages.

Characteristics, Relationships, and Anatomical Basis of Leaf Hydraulic Traits and Economic Traits in Temperate Desert Shrub Species.

Shrubs are a key component of desert ecosystems, playing a crucial role in controlling desertification and promoting revegetation, yet their growth is often impeded by drought. Leaf hydraulic traits and economic traits are both involved in the process of water exchange for carbon dioxide. Exploring the characteristics, relationships, and anatomical basis of these two suites of traits is crucial to understanding the mechanism of desert shrubs adapting to the desert arid environment. However, the relationship between these two sets of traits currently remains ambiguous. This study explored the leaf hydraulic, economic, and anatomical traits of 19 desert shrub species. The key findings include the following: Relatively larger LT values and smaller SLA values were observed in desert shrubs, aligning with the "slow strategy" in the leaf economics spectrum. The relatively high P50leaf, low HSMleaf, negative TLPleaf, and positive HSMtlp values indicated that severe embolism occurs in the leaves during the dry season, while most species were able to maintain normal leaf expansion. This implies a "tolerance" leaf hydraulic strategy in response to arid stress. No significant relationship was observed between P50leaf and Kmax, indicating the absence of a trade-off between hydraulic efficiency and embolism resistance. Certain coupling relationships were observed between leaf hydraulic traits and economic traits, both of which were closely tied to anatomical structures. Out of all of the leaf traits, LT was the central trait of the leaf traits network. The positive correlation between C content and WPleaf and HSMleaf, as well as the positive correlation between N content and HSMtlp, suggested that the cost of leaf construction was synergistic with hydraulic safety. The negative correlation between SLA, P content, GCL, and SAI suggested a functional synergistic relationship between water use efficiency and gas exchange rate. In summary, this research revealed that the coupling relationship between leaf hydraulic traits and economic traits was one of the important physiological and ecological mechanisms of desert shrubs for adapting to desert habitats.

Effect of Early Inhibition of Toll-Like Receptor 4 on Hippocampal Plasticity in a Neonatal Rat Model of Hypoxic-Ischemic Brain Damage.

Hippocampal plasticity is closely related to physiological brain functions such as learning and memory. However, the effect of toll-like receptor 4 (TLR4) activation on hippocampal plasticity after neonatal hypoxic-ischaemic brain damage (HIBD) remains unclear. In our study, seven-day-old rat pups were randomly categorised into three groups: control, hypoxic-ischemia (HI), and HI + TAK-242 (TAK-242). The pups were ligated in the left common carotid artery and then subjected to hypoxia to establish the neonatal HIBD model.The expression of the TLR4 in the left hippocampus of the HI group was increased compared to the control group, while TAK-242 reduced the expression level at 3 days after HIBD. Additionally, TAK-242 reversed the increased Zea-Longa score, increased the left/right hippocampal weight ratio, and increased the number of Nissl-positive neurons in the hippocampal CA1 region compared to HI group at 3 days after HIBD. Pre-injection of TAK-242 alleviated the decrease in PSD95, Aggrecan and NR1, BDNF, CREB, and pCREB expression in the hippocampus at 24 h after HIBD. It also alleviated the decrease in PSD95, BDNF, and NR2A/NR1 expression in the hippocampus at 7 days after HIBD. Furthermore, Pre-injection of TAK-242 alleviated the decrease in NR2A/NR1 expression at 21 days after HIBD. Finally,TAK-242 increased the percentage of third-grade dendritic mushroom spines processes in the basal and apical segments of neurons in the hippocampal CA1 region at 21 days after HIBD.Therefore, we conclude that preinhibition of TLR4 prior to neonatal HIBD improved the plasticity of the hippocampus.

The mediating effect of self-efficacy on family functioning and psychological resilience in prostate cancer patients.

Aims: Prostate cancer patients face impaired body image and psychological distress during the diagnosis and treatment of the disease, which leads to changes in mood, cognition and behavior. Psychological resilience has been shown to buffer shocks and stresses from the disease. Therefore, this study investigates the relationship between family functioning and psychological resilience in prostate cancer patients and the mediating role of self-efficacy between family functioning and psychological resilience to provide a relevant theoretical basis for improving patients' psychological status by providing relevant theoretical basis. Method: Using a cross-sectional design, participants were 215 patients with prostate cancer admitted to and treated in a tertiary hospital in Jiangsu province, China. Questionnaires were administered using the general information questionnaire, the Connor-Davidson Resilience Scale (CD-RISC), the Family Adaptation, Partnership, Growth, Affection, and Resolution Index (APGAR), and the General Self-efficacy Scale (GSES). Data were analyzed using descriptive and correlational analyses and the bootstrap mediation test was used to test the effect relationship between the variables. Results: Family functioning, self-efficacy and psychological resilience were significantly and positively correlated (r = 0.526, P < 0.01; r = 0.378, P < 0.01; r = 0.358, P < 0.01). The mediating effect of psychological resilience between family functioning and psychological resilience was significant, accounting for 42.56%. Conclusion: Family function and self-efficacy have been shown to increase the level of psychological resilience in prostate cancer patients. Attention should be paid to the mental health problems of prostate cancer patients, early screening and intervention, and the use of patients' family resources to improve their confidence in recovering from the disease, thus increasing their psychological resilience and improving their mental health.