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BMC Genomics Jul 2024Breeding polled goats is a welfare-friendly approach for horn removal in comparison to invasive methods. To gain a comprehensive understanding of the genetic basis...
BACKGROUND
Breeding polled goats is a welfare-friendly approach for horn removal in comparison to invasive methods. To gain a comprehensive understanding of the genetic basis underlying polledness in goats, we conducted whole-genome sequencing of 106 Xinong Saanen dairy goats, including 33 horned individuals, 70 polled individuals, and 3 polled intersexuality syndrome (PIS) individuals.
METHODS
The present study employed a genome-wide association study (GWAS) and linkage disequilibrium (LD) analysis to precisely map the genetic locus underlying the polled phenotype in goats.
RESULTS
The analysis conducted in our study revealed a total of 320 genome-wide significant single nucleotide polymorphisms (SNPs) associated with the horned/polled phenotype in goats. These SNPs exhibited two distinct peaks on chromosome 1, spanning from 128,817,052 to 133,005,441 bp and from 150,336,143 to 150,808,639 bp. The present study identified three genome-wide significant SNPs, namely Chr1:129789816, Chr1:129791507, and Chr1:129791577, as potential markers of PIS-affected goats. The results of our LD analysis suggested a potential association between MRPS22 and infertile intersex individuals, as well as a potential association between ERG and the polled trait in goats.
CONCLUSION
We have successfully identified three marker SNPs closely linked to PIS, as well as several candidate genes associated with the polled trait in goats. These results may contribute to the development of SNP chips for early prediction of PIS in goats, thereby facilitating breeding programs aimed at producing fertile herds with polled traits.
Topics: Animals; Goats; Genome-Wide Association Study; Polymorphism, Single Nucleotide; Phenotype; Linkage Disequilibrium; Disorders of Sex Development; Female; Male; Whole Genome Sequencing; Horns
PubMed: 38956513
DOI: 10.1186/s12864-024-10568-9 -
BMC Psychiatry Jul 2024Increasing evidence suggested that immune abnormalities involved in the pathophysiology of schizophrenia. However, the relationship between immunity and clinical...
BACKGROUND
Increasing evidence suggested that immune abnormalities involved in the pathophysiology of schizophrenia. However, the relationship between immunity and clinical features has not been clarified. The aim of this study was to measure the plasma levels of tumor necrosis factor alpha (TNF-α) and soluble TNF-α receptor 1 (sTNF-α R1) and to investigate their association with agitation in first episode patients with schizophrenia (FEPS).
METHODS
The plasma TNF-α and sTNF-α R1 levels were measured using sandwich enzyme-linked immunosorbent assay (ELISA) in the FEPS with (n = 36) and without agitation (n = 49) symptoms, and healthy controls (HCs, n = 54). The psychopathology was assessed by the Positive and Negative Syndrome Scale (PANSS), and the agitation symptoms were evaluated by the PANSS excitatory component (PANSS-EC).
RESULTS
The plasma TNF-α levels in patients with and without agitation symptoms were significantly higher than those in HCs. The patients with agitation had significantly higher plasma TNF-α levels compared to the patients without agitation. There were no significant differences in the sTNF-α R1 levels among the three groups. Furthermore, the plasma TNF-α levels were positively correlated with the PANSS total score, Positive and General psychopathological subscores, and PANSS-EC score in the FEPS, but the relationships were not found for the plasma sTNF-α R1 levels.
CONCLUSIONS
These results suggested that TNF-α might play an important role in the onset and development of agitation symptoms of schizophrenia.
Topics: Humans; Schizophrenia; Female; Male; Tumor Necrosis Factor-alpha; Psychomotor Agitation; Adult; Receptors, Tumor Necrosis Factor, Type I; Young Adult; Psychiatric Status Rating Scales
PubMed: 38956509
DOI: 10.1186/s12888-024-05796-y -
Acta Pharmacologica Sinica Jul 2024Abnormal accumulation of hyperphosphorylated tau protein plays a pivotal role in a collection of neurodegenerative diseases named tauopathies, including Alzheimer's...
Abnormal accumulation of hyperphosphorylated tau protein plays a pivotal role in a collection of neurodegenerative diseases named tauopathies, including Alzheimer's disease (AD). We have recently conceptualized the design of hetero-bifunctional chimeras for selectively promoting the proximity between tau and phosphatase, thus specifically facilitating tau dephosphorylation and removal. Here, we sought to optimize the construction of tau dephosphorylating-targeting chimera (DEPTAC) and obtained a new chimera D14, which had high efficiency in reducing tau phosphorylation both in cell and tauopathy mouse models, while showing limited cytotoxicity. Moreover, D14 ameliorated neurodegeneration in primary cultured hippocampal neurons treated with toxic tau-K18 fragments, and improved cognitive functions of tauopathy mice. These results suggested D14 as a cost-effective drug candidate for the treatment of tauopathies.
PubMed: 38956416
DOI: 10.1038/s41401-024-01326-4 -
Scientific Reports Jul 2024Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations...
Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and cognitive tasks have been studied many times. However, any significant dissimilarity in the resting-state low-frequency bands is yet to be established. Spectral analysis of the alpha and delta band waves shows the effectiveness of stimulus-independent EEG in identifying the abnormal activity patterns of pathological brains. A generalized model incorporating multiple frequency bands should be more efficient in associating potential EEG biomarkers with first-episode psychosis (FEP), leading to an accurate diagnosis. We explore multiple machine-learning methods, including random-forest, support vector machine, and Gaussian process classifier (GPC), to demonstrate the practicality of resting-state power spectral density (PSD) to distinguish patients of FEP from healthy controls. A comprehensive discussion of our preprocessing methods for PSD analysis and a detailed comparison of different models are included in this paper. The GPC model outperforms the other models with a specificity of 95.78% to show that PSD can be used as an effective feature extraction technique for analyzing and classifying resting-state EEG signals of psychiatric disorders.
Topics: Humans; Psychotic Disorders; Electroencephalography; Female; Male; Adult; Support Vector Machine; Young Adult; Rest; Machine Learning; Brain; Adolescent; Signal Processing, Computer-Assisted
PubMed: 38956297
DOI: 10.1038/s41598-024-66110-0 -
Scientific Reports Jul 2024The prenatal diagnosis of fetal heart disease potentially influences parental decision-making regarding pregnancy termination. Existing literature indicates that the...
The prenatal diagnosis of fetal heart disease potentially influences parental decision-making regarding pregnancy termination. Existing literature indicates that the severity, whether in complexity or lethality, significantly influences parental decisions concerning abortion. However, questions remain as to how fetal heart disease severity impacts parental decisions, given recent advancements in postsurgical outcomes. Therefore, we investigated risk factors associated with parents' decision-making regarding abortion following a prenatal diagnosis of fetal heart disease. Our analysis included 73 (terminated: n = 37; continued: n = 36) pregnancies with a fetal heart disease diagnosed before 22 weeks of gestation. Increased gestational age at diagnosis reduced the likelihood of parents' decision on termination (Model 1: adjusted odds ratio, 0.94; 95% confidence interval 0.89-0.99; Model 2: 0.95 0.90-0.997). Critical disease (5.25; 1.09-25.19) and concurrent extracardiac or genetic abnormalities (Model 1: 4.19, 1.21-14.53; Model 2: 5.47, 1.50-19.96) increased the likelihood of choosing abortion. Notably, complex disease did not significantly influence parental decisions (0.56; 0.14-2.20). These results suggest that parental decision-making regarding abortion may be influenced by earlier gestational age at diagnosis, the lethality of heart disease, and extracardiac or genetic abnormalities, but not its complexity if prenatal diagnosis and parental counseling are provided at a cardiovascular-specialized facility.
Topics: Humans; Female; Pregnancy; Abortion, Induced; Decision Making; Adult; Parents; Prenatal Diagnosis; Gestational Age; Heart Defects, Congenital; Heart Diseases; Risk Factors; Fetal Diseases; Male; Severity of Illness Index
PubMed: 38956291
DOI: 10.1038/s41598-024-66027-8 -
Scientific Reports Jul 2024Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by abnormal blood glucose metabolism resulting from insufficient insulin...
Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by abnormal blood glucose metabolism resulting from insufficient insulin secretion or reduced insulin activity. Epidemiological survey results show that about one third of diabetes patients have signs of diabetic retinopathy, and another third may suffer from serious retinopathy that threatens vision. However, the pathogenesis of diabetic retinopathy is still unclear, and there is no systematic method to detect the onset of the disease and effectively predict its occurrence. In this study, we used medical detection data from diabetic retinopathy patients to determine key biomarkers that induce disease onset through back propagation neural network algorithm and hierarchical clustering analysis, ultimately obtaining early warning signals of the disease. The key markers that induce diabetic retinopathy have been detected, which can also be used to explore the induction mechanism of disease occurrence and deliver strong warning signal before disease occurrence. We found that multiple clinical indicators that form key markers, such as glycated hemoglobin, serum uric acid, alanine aminotransferase are closely related to the occurrence of the disease. They respectively induced disease from the aspects of the individual lipid metabolism, cell oxidation reduction, bone metabolism and bone resorption and cell function of blood coagulation. The key markers that induce diabetic retinopathy complications do not act independently, but form a complete module to coordinate and work together before the onset of the disease, and transmit a strong warning signal. The key markers detected by this algorithm are more sensitive and effective in the early warning of disease. Hence, a new method related to key markers is proposed for the study of diabetic microvascular lesions. In clinical prediction and diagnosis, doctors can use key markers to give early warning of individual diseases and make early intervention.
Topics: Humans; Diabetic Retinopathy; Biomarkers; Neural Networks, Computer; Cluster Analysis; Algorithms; Male; Female; Early Diagnosis; Middle Aged; Glycated Hemoglobin
PubMed: 38956257
DOI: 10.1038/s41598-024-65694-x -
Scientific Reports Jul 2024Rapamycin slows cystogenesis in murine models of polycystic kidney disease (PKD) but failed in clinical trials, potentially due to insufficient drug dosing. To improve...
Rapamycin slows cystogenesis in murine models of polycystic kidney disease (PKD) but failed in clinical trials, potentially due to insufficient drug dosing. To improve drug efficiency without increasing dose, kidney-specific drug delivery may be used. Mesoscale nanoparticles (MNP) selectively target the proximal tubules in rodents. We explored whether MNPs can target cystic kidney tubules and whether rapamycin-encapsulated-MNPs (RapaMNPs) can slow cyst growth in Pkd1 knockout (KO) mice. MNP was intravenously administered in adult Pkd1KO mice. Serum and organs were harvested after 8, 24, 48 or 72 h to measure MNP localization, mTOR levels, and rapamycin concentration. Pkd1KO mice were then injected bi-weekly for 6 weeks with RapaMNP, rapamycin, or vehicle to determine drug efficacy on kidney cyst growth. Single MNP injections lead to kidney-preferential accumulation over other organs, specifically in tubules and cysts. Likewise, one RapaMNP injection resulted in higher drug delivery to the kidney compared to the liver, and displayed sustained mTOR inhibition. Bi-weekly injections with RapaMNP, rapamycin or vehicle for 6 weeks resulted in inconsistent mTOR inhibition and little change in cyst index, however. MNPs serve as an effective short-term, kidney-specific delivery system, but long-term RapaMNP failed to slow cyst progression in Pkd1KO mice.
Topics: Animals; Sirolimus; Mice; Polycystic Kidney Diseases; Mice, Knockout; Nanoparticles; Disease Models, Animal; TOR Serine-Threonine Kinases; TRPP Cation Channels; Kidney; Drug Delivery Systems; Male
PubMed: 38956234
DOI: 10.1038/s41598-024-65830-7 -
Scientific Reports Jul 2024Laboratory mice are typically housed in "shoebox" cages with limited opportunities to engage in natural behaviour. Temporary access to environments with increased space...
Laboratory mice are typically housed in "shoebox" cages with limited opportunities to engage in natural behaviour. Temporary access to environments with increased space and complexity (playpens) may improve mouse welfare. Previous work by our group has shown that mice are motivated to access and use these environments, but it is unknown how other aspects of welfare are impacted. Female C57BL/6J, BALB/cJ, and DBA/2J mice (n = 21; 7 mice per strain) were housed in mixed-strain trios and given temporary access to a large playpen with their cage mates three times per week. Control mice (n = 21; 7 mice per strain) remained in their home cages. Home cage behaviour (development of stereotypic behaviour over time, aggression following cage-changing) and anxiety tests were used to assess how playpen access impacted welfare. Contrary to our predictions, we found increased time spent performing stereotypies in playpen mice; this difference may be related to negative emotional states, increased motivation to escape the home cage, or active coping strategies. Playpen access resulted in strain-dependent improvements in aggression and some measures of anxiety. Aggression was lower for C57BL/6J mice in the playpen treatment following cage changing than it was for C57BL/6J control mice, while playpen mice, and particularly the C57BL/6J strain, spent more time in the center of the open field test and produced fewer fecal boli during anxiety testing, supporting other research showing that strain differences play an important role in behaviour and stress resiliency.
Topics: Animals; Animal Welfare; Mice; Female; Mice, Inbred C57BL; Housing, Animal; Behavior, Animal; Aggression; Anxiety; Mice, Inbred BALB C; Mice, Inbred DBA; Stereotyped Behavior
PubMed: 38956228
DOI: 10.1038/s41598-024-65480-9 -
Scientific Reports Jul 2024Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal...
Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagnose and classify the tumor from several pictures. This work develops an intelligent method for accurately identifying brain tumors. This research investigates the identification of brain tumor types from MRI data using convolutional neural networks and optimization strategies. Two novel approaches are presented: the first is a novel segmentation technique based on firefly optimization (FFO) that assesses segmentation quality based on many parameters, and the other is a combination of two types of convolutional neural networks to categorize tumor traits and identify the kind of tumor. These upgrades are intended to raise the general efficacy of the MRI scan technique and increase identification accuracy. Using MRI scans from BBRATS2018, the testing is carried out, and the suggested approach has shown improved performance with an average accuracy of 98.6%.
Topics: Magnetic Resonance Imaging; Brain Neoplasms; Humans; Neural Networks, Computer; Image Processing, Computer-Assisted; Algorithms; Brain
PubMed: 38956224
DOI: 10.1038/s41598-024-65714-w -
Scientific Reports Jul 2024Diabetic retinopathy (DR) is a serious complication of diabetes featuring abnormal lipid metabolism. However, the specific lipid molecules associated with onset and...
Diabetic retinopathy (DR) is a serious complication of diabetes featuring abnormal lipid metabolism. However, the specific lipid molecules associated with onset and progression remain unclear. We used a broad-targeted lipidomics approach to assess the lipid changes that occur before the proliferative retinopathy stage and to identify novel lipid biomarkers to distinguish between patients without DR (NDR) and with non-proliferative DR (NPDR). Targeted lipomics analysis was carried out on serum samples from patients with type I diabetes, including 20 NDRs and 20 NPDRs. The results showed that compared with the NDR group, 102 lipids in the NPDR group showed specific expressions. Four lipid metabolites including TAG58:2-FA18:1 were obtained using the Least Absolute Shrink And Selection Operator (LASSO) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) methods. The four-lipid combination diagnostic models showed good predictive ability in both the discovery and validation sets, and were able to distinguish between NDR patients and NPDR patients. The identified lipid markers significantly improved diagnostic accuracy within the NPDR group. Our findings help to better understand the complexity and individual differences of DR lipid metabolism.
Topics: Humans; Diabetic Retinopathy; Biomarkers; Lipidomics; Male; Female; Lipids; Middle Aged; Adult; Lipid Metabolism; Diabetes Mellitus, Type 1
PubMed: 38956223
DOI: 10.1038/s41598-024-66157-z