Towards an accurate autism spectrum disorder diagnosis: multiple connectome views from fMRI data.

Functional connectome has revealed remarkable potential in the diagnosis of neurological disorders, e.g. autism spectrum disorder. However, existing studies have primarily focused on a single connectivity pattern, such as full correlation, partial correlation, or causality. Such an approach fails in discovering the potential complementary topology information of FCNs at different connection patterns, resulting in lower diagnostic performance. Consequently, toward an accurate autism spectrum disorder diagnosis, a straightforward ambition is to combine the multiple connectivity patterns for the diagnosis of neurological disorders. To this end, we conduct functional magnetic resonance imaging data to construct multiple brain networks with different connectivity patterns and employ kernel combination techniques to fuse information from different brain connectivity patterns for autism diagnosis. To verify the effectiveness of our approach, we assess the performance of the proposed method on the Autism Brain Imaging Data Exchange dataset for diagnosing autism spectrum disorder. The experimental findings demonstrate that our method achieves precise autism spectrum disorder diagnosis with exceptional accuracy (91.30%), sensitivity (91.48%), and specificity (91.11%).

Molecular insights into the hedgehog signaling pathway correlated non-coding RNAs in acute lymphoblastic leukemia, a bioinformatics study.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is a common hematologic cancer with unique incidence and prognosis patterns in people of all ages. Recent molecular biology advances have illuminated ALL's complex molecular pathways, notably the Hedgehog (Hh) signaling system and non-coding RNAs (ncRNAs). This work aimed to unravel the molecular complexities of the link between Hh signaling and ALL by concentrating on long non-coding RNAs (lncRNAs) and their interactions with significant Hh pathway genes. METHODS: To analyze differentially expressed lncRNAs and genes in ALL, microarray data from the Gene Expression Omnibus (GEO) was reanalyzed using a systems biology approach. Hh signaling pathway-related genes were identified and their relationship with differentially expressed long non-coding RNAs (DElncRNAs) was analyzed using Pearson's correlation analysis. A regulatory network was built by identifying miRNAs that target Hh signaling pathway-related mRNAs. RESULTS: 193 DEGs and 226 DElncRNAs were found between ALL and normal bone marrow samples. Notably, DEGs associated with the Hh signaling pathway were correlated to 26 DElncRNAs. Later studies showed interesting links between DElncRNAs and biological processes and pathways, including drug resistance, immune system control, and carcinogenic characteristics. DEGs associated with the Hh signaling pathway have miRNAs in common with miRNAs already known to be involved in ALL, including miR-155-5p, and miR-211, highlighting the complexity of the regulatory landscape in this disease. CONCLUSION: The complex connections between Hh signaling, lncRNAs, and miRNAs in ALL have been unveiled in this study, indicating that DElncRNAs linked to Hh signaling pathway genes could potentially serve as therapeutic targets and diagnostic biomarkers for ALL.

On the pixel selection criterion for the calculation of the Pearson's correlation coefficient in fluorescence microscopy.

Colocalisation microscopy analysis provides an intuitive and straightforward way of determining if two biomolecules occupy the same diffraction-limited volume. A popular colocalisation coefficient, the Pearson's correlation coefficient (PCC), can be calculated using different pixel selection criteria: PCCALL includes all image pixels, PCCOR only pixels exceeding the intensity thresholds for either one of the detection channels, and PCCAND only pixels exceeding the intensity thresholds for both detection channels. Our results show that PCCALL depends on the foreground to background ratio, producing values influenced by factors unrelated to biomolecular association. PCCAND focuses on areas with the highest intensities in both channels, which allows it to detect low levels of colocalisation, but makes it inappropriate for evaluating spatial cooccurrence between the signals. PCCOR produces values influenced both by signal proportionality and spatial cooccurrence but can sometimes overemphasise the lack of the latter. Overall, PCCAND excels at detecting low levels of colocalisation, PCCOR provides a balanced quantification of signal proportionality and spatial coincidence, and PCCALL risks misinterpretation yet avoids segmentation challenges. Awareness of their distinct properties should inform their appropriate application with the aim of accurately representing the underlying biology.

Predicting the multivariate zero-inflated counts: A novel model averaging method under Pearson loss.

Excessive zeros in multivariate count data are often observed in scenarios of biomedicine and public health. To provide a better analysis on this type of data, we first develop a marginalized multivariate zero-inflated Poisson (MZIP) regression model to directly interpret the overall exposure effects on marginal means. Then, we define a multiple Pearson residual for our newly developed MZIP regression model by simultaneously taking heterogeneity and correlation into consideration. Furthermore, a new model averaging prediction method is introduced based on the multiple Pearson residual, and the asymptotical optimality of this model averaging prediction is proved. Simulations and two empirical applications in medicine are used to illustrate the effectiveness of the proposed method.

Gradient synchronization for multivariate functional data, with application to brain connectivity.

Quantifying the association between components of multivariate random curves is of general interest and is a ubiquitous and basic problem that can be addressed with functional data analysis. An important application is the problem of assessing functional connectivity based on functional magnetic resonance imaging (fMRI), where one aims to determine the similarity of fMRI time courses that are recorded on anatomically separated brain regions. In the functional brain connectivity literature, the static temporal Pearson correlation has been the prevailing measure for functional connectivity. However, recent research has revealed temporally changing patterns of functional connectivity, leading to the study of dynamic functional connectivity. This motivates new similarity measures for pairs of random curves that reflect the dynamic features of functional similarity. Specifically, we introduce gradient synchronization measures in a general setting. These similarity measures are based on the concordance and discordance of the gradients between paired smooth random functions. Asymptotic normality of the proposed estimates is obtained under regularity conditions. We illustrate the proposed synchronization measures via simulations and an application to resting-state fMRI signals from the Alzheimer's Disease Neuroimaging Initiative and they are found to improve discrimination between subjects with different disease status.

Long-term hematopoietic dysfunction in patients with large-scale mitochondrial DNA deletion syndromes.

BACKGROUND: Pearson syndrome (PS) and Kearns-Sayre syndrome (KSS) are single large-scale mitochondrial DNA deletion (SLSMD) syndromes. PS is characterized by severe, transient childhood cytopenia, whereas KSS typically manifests later in life without hematologic abnormalities. Despite distinct clinical presentations, both share a common mitochondrial DNA deletion. Recent observations suggest a potential link between PS progression and myeloid malignancy development, indicating that bone marrow failure (BMF) may be a key aspect of PS pathology and potentially universal across SLSMDs. METHODS: This study explores longitudinal hematological manifestations of SLSMD syndromes, focusing on bone marrow (BM) dysfunction. RESULTS: Sixteen patients with SLSMDs (13 PS and 3 KSS) were followed, of whom 75% experienced cytopenia, necessitating blood transfusions in 56%. Despite achieving transfusion independence at a median age of 24 months, persistent hematological abnormalities were noted. Comprehensive longitudinal BM studies were conducted in 62% of subjects and consistently revealed signs of marrow dysfunction, even without concurrent cytopenia. Median BM cellularity at a median age of four years and eight months was 50%, with histological signs of dyserythropoiesis, abnormal megakaryocytes, and signs suggesting myelodysplasia. Reduced CD34+ counts and BM colony-forming unit capacity were noted, alongside chromosome 7 aberrations in 16% of patients on cytogenetic studies. CONCLUSIONS: Our findings establish BM dysfunction as a persistent hallmark of SLSMD syndromes, posing a risk of clonal evolution and acquisition of chromosome 7 aberrations. This aligns with recent literature, emphasizing enduring BMF in SLSMD syndromes and advocating for tailored hematological monitoring guidelines for this unique patient cohort.

Atypical presentation of Pearson syndrome in an infant with suspected myelodysplastic syndrome.

BACKGROUND: Anemia exhibits complex causation mechanisms and genetic heterogeneity. Some cases result in poor outcomes with multisystemic dysfunction, including renal tubulopathy. Early diagnosis is crucial to improve management. CASE-DIAGNOSIS/TREATMENT: A 21-month-old female patient was admitted with severe anemia. Persistent neutropenia and dysplastic signs suggested myelodysplastic syndrome, but targeted gene panel results were negative. After multiple transfusions, spontaneous hematologic recovery was observed. At 4 years old, she presented failure to thrive, renal Fanconi syndrome, and severe metabolic acidosis. Differential diagnosis included Pearson syndrome (PS), a life-threatening condition associated with mitochondrial DNA (mtDNA), featuring anemia and pancreatic insufficiency. Further analysis revealed a ~ 7.5 kb mtDNA deletion. Until the age of 5, supportive care has been provided, without pancreatic insufficiency. CONCLUSIONS: This PS case highlights the importance of genetic testing, even in the absence of typical features. Understanding the nature of mitochondrial disorders enables treatment tailoring and counseling about the prognosis.

Genome-wide identification of the SAUR gene family and screening for SmSAURs involved in root development in Salvia miltiorrhiza.

KEY MESSAGE: SmSAUR4, SmSAUR18, SmSAUR28, SmSAUR37, and SmSAUR38 were probably involved in the auxin-mediated root development in Salvia miltiorrhiza. Salvia miltiorrhiza is a widely utilized medicinal plant in China. Its roots and rhizomes are the main medicinal portions and are closely related to the quality of this herb. Previous studies have revealed that auxin plays pivotal roles in S. miltiorrhiza root development. Whether small auxin-up RNA genes (SAURs), which are crucial early auxin response genes, are involved in auxin-mediated root development in S. miltiorrhiza is worthy of investigation. In this study, 55 SmSAUR genes in S. miltiorrhiza were identified, and their physical and chemical properties, gene structure, cis-acting elements, and evolutionary relationships were analyzed. The expression levels of SmSAUR genes in different organs of S. miltiorrhiza were detected using RNA-seq combined with qRT‒PCR. The root development of S. miltiorrhiza seedlings was altered by the application of indole-3-acetic acid (IAA), and Pearson correlation coefficient analysis was conducted to screen SmSAURs that potentially participate in this physiological process. The diameter of primary lateral roots was positively correlated with SmSAUR4. The secondary lateral root number was positively correlated with SmSAUR18 and negatively correlated with SmSAUR4. The root length showed a positive correlation with SmSAUR28 and SmSAUR37 and a negative correlation with SmSAUR38. The fresh root biomass exhibited a positive correlation with SmSAUR38 and a negative correlation with SmSAUR28. The aforementioned SmSAURs were likely involved in auxin-mediated root development in S. miltiorrhiza. Our study provides a comprehensive overview of SmSAURs and provides the groundwork for elucidating the molecular mechanism underlying root morphogenesis in this species.

The adipokine profile in the plasma and anterior pituitary of pigs during the estrous cycle.

Adipokines play crucial roles in both reproductive and energy metabolic processes. This study aimed to compare the hormonal plasma profile of adiponectin, apelin, vaspin, chemerin, resistin, visfatin, and adipolin, and the expression of their receptors in the anterior pituitary (AP) between normal-weight Large White (LW) and fat Meishan (MS) pigs during different phases of the estrous cycle. We measured adipokine levels in the plasma and assessed their gene expression in the AP. We used Pearson's correlation analysis to examine potential links between adipokines levels, their receptors, and metabolic parameters (body weight; backfat thickness) and reproductive parameters (pituitary weight; age at puberty; levels of gonadotropins, steroid hormones; and gene expression of gonadotropin-releasing hormone receptor and gonadotropins in AP). The plasma levels of the evaluated adipokines fluctuated with phase and breed, except for visfatin and adipolin. Moreover, adipokine expression in AP varied significantly between breeds and estrous cycle phases, except for resistin receptor CAP1. Notably, we observed a positive correlation between plasma levels of adiponectin and its transcript in the AP only in MS pigs. Apelin gene expression correlated negatively with its receptor in MS, while we observed a breed-dependent correlation between chemerin gene expression and its receptor CMKLR1. We identified significant positive or negative correlations between adipokines or their receptor levels in plasma and AP as well as metabolic or reproductive parameters, depending on the breed. In conclusion, we have demonstrated breed-specific and estrous cycle-dependent regulation of adipokines in AP, underscoring their potential impact on metabolic and reproductive processes in swine.

The Diagnostic Value of miR-124a Expression in Peripheral Blood and Synovial Fluid of Patients with Rheumatoid Arthritis.

INTRODUCTION: Rheumatoid arthritis (RA), a chronic autoimmune disorder, is currently a severe health threat. Previous studies have documented the altered expression of various miRNAs in RA patients. This study determined the expression of miR-124a in RA patients and estimated its diagnostic value for RA. METHODS: A total of 80 RA patients were enrolled as the study subjects, and 36 patients with osteoarthritis were included, with another 36 healthy people as the controls. miR-124a expression levels in peripheral blood plasma, peripheral blood mononuclear cells (PBMCs), and synovial fluid were measured using reverse transcription quantitative polymerase chain reaction, followed by Pearson correlation analysis. Additionally, the association between miR-124a and major clinical indicators was assessed, such as rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), and disease activity score of 28 joints (DAS28). The diagnostic efficacy of miR-124a expression in plasma, PBMCs, and synovial fluid for RA was evaluated by the receiver operating characteristic curve, and the difference in the area under the curve (AUC) was analyzed. RESULTS: miR-124a was downregulated in RA patients, and the expression levels of miR-124a in plasma, PBMCs, and synovial fluid showed a certain degree of positive correlation. miR-124a was inversely linked with RF, ESR, and DAS28. For the diagnosis of RA patients, the AUC of plasma miR-124a was 0.899 and the cut-off value was 0.800, with 68.75% sensitivity and 94.44% specificity; the AUC of miR-124a in PBMCs was 0.937 and the cut-off value was 0.805, with 82.50% sensitivity and 91.67% specificity; the AUC of miR-124a in plasma combined with PBMCs was 0.961, with a higher diagnostic value than independent plasma or PBMCs; the AUC of miR-124a in synovial fluid was 0.929 and the cut-off value was 0.835, with 80.00% sensitivity and 88.89% specificity. CONCLUSION: miR-124a expression is downregulated in the plasma, PBMCs, and synovial fluid of RA patients and has a high diagnostic value for RA.

Combined transcriptome and microbiome analysis reveals the thyrotoxic effects of PM2.5 in female rats.

Pervasive environmental pollutants, specifically particulate matter (PM2.5), possess the potential to disrupt homeostasis of female thyroid hormone (TH). However, the precise mechanism underlying this effect remains unclear. In this study, we established a model of PM2.5-induced thyroid damage in female rats through intratracheal instillation and employed histopathological and molecular biological methods to observe the toxic effects of PM2.5 on the thyroid gland. Transcriptome gene analysis and 16S rRNA sequencing were utilized to investigate the impact of PM2.5 exposure on the female rat thyroid gland. Furthermore, based on the PM2.5-induced toxic model in female rats, we evaluated its effects on intestinal microbiota, TH levels, and indicators of thyroid function. The findings revealed that PM2.5 exposure induced histopathological damage to thyroid tissue by disrupting thyroid hormone levels (total T3 [TT3], (P < 0.05); total T4 [TT4], (P < 0.05); and thyrotropin hormone [TSH], (P < 0.05)) and functional indices (urine iodine [UI], P > 0.05), thus further inducing histopathological injuries. Transcriptome analysis identified differentially expressed genes (DEGs), primarily concentrated in interleukin 17 (IL-17), forkhead box O (FOXO), and other signaling pathways. Furthermore, exposure to PM2.5 altered the composition and abundance of intestinal microbes. Transcriptome and microbiome analyses demonstrated a correlation between the DEGs within these pathways and the flora present in the intestines. Moreover, 16 S rRNA gene sequencing analysis or DEGs combined with thyroid function analysis revealed that exposure to PM2.5 significantly induced thyroid hormone imbalance. We further identified key DEGs involved in thyroid function-relevant pathways, which were validated using molecular biology methods for clinical applications. In conclusion, the homeostasis of the "gut-thyroid" axis may serve as the underlying mechanism for PM2.5-induced thyrotoxicity in female rats.

Optimizing short-term in-class process evaluation: analyzing the effectiveness of teaching interventions in pharmaceutical education using repeated measures analysis.

BACKGROUND: The assessment of the effectiveness of teaching interventions in enhancing students' understanding of the Pharmaceutical Care Network Europe (PCNE) Classification System is crucial in pharmaceutical education. This is especially true in regions like China, where the integration of the PCNE system into undergraduate teaching is limited, despite its recognized benefits in addressing drug-related problems in clinical pharmacy practice. Therefore, this study aimed to evaluate the effectiveness of teaching interventions in improving students' understanding of the PCNE Classification System in pharmaceutical education. METHODS: Undergraduate pharmacy students participated in a series of sessions focused on the PCNE system, including lectures (t1), case analyses (t2), and practical implementation (t3). The levels of understanding were evaluated using time-course questionnaires. Initially, paired samples t-Tests were used to compare understanding levels between different time points. Subsequently, Repeated Measures Analysis (RMA) was employed. Pearson correlation analysis was conducted to examine the relationship between understanding levels and the usability and likelihood of using the PCNE system, as reported in the questionnaires. RESULTS: The paired samples t-Tests indicated insignificant differences between t2 and t3, suggesting limited improvement following the practical implementation of the PCNE system. However, RMA revealed significant time effects on understanding levels in effective respondents and the focused subgroup without prior experience (random intercept models: all p < 0.001; random slope models: all p < 0.001). These results confirmed the effectiveness of all three teaching interventions. Pearson correlation analysis demonstrated significant positive correlations between understanding levels and the usability and likelihood of using the PCNE system at all examined time points. This finding highlighted the reliability of the understanding levels reported in the questionnaires. The homework scores were used as external calibration standards, providing robust external validation of the questionnaire's validity. CONCLUSION: The implementation of RMA provided robust evidence of the positive impact of time on understanding levels. This affirmed the effectiveness of all teaching interventions in enhancing students' comprehension of the PCNE Classification System. By utilizing RMA, potential errors inherent in common statistical methods, such as t-Tests, were mitigated. This ensured a more comprehensive and accurate assessment of the effectiveness of the teaching interventions.

Wideband Current Transducer Traceable Calibration up to 10 A and 1 MHz.

Energy efficiency is an important issue in industry, especially with the ever-increasing consumption of electrical energy. The power quality and the traceability of metering devices are essential when integrating energy metering systems for energy efficiency. This management requires an understanding of electrical current events such as pulse and transient currents. Current transducers are widely used to measure these electrical current events up to a few megahertz. Their use makes it possible to measure not only the main current flowing through the transducer, but also the bypass current that affects electrical equipment. Calibration of these sensors up to a few megahertz then becomes an essential step. Currently, most calibration methods are limited to 100 kHz frequency for a current of 10 A. This paper presents an improvement of a traceable calibration methodology for current transducers up to 10 A and 1 MHz, thus increasing, by 10 times, the current level for such high frequency applications. This calibration methodology is based on a metrological traceability chain (uninterrupted link to the International System of Units) with respect to a calculable current shunt and is currently the only traceable method for calibrating current transducers at 10 A and up to 1 MHz. The uncertainty obtained for the transimpedance ratio is less than 0.2%, which is considerably reduced with respect to the existing capabilities.

Multi-model exploration of groundwater quality and potential health risk assessment in Jajpur district, Eastern India.

The presence of fluoride and nitrate is a serious groundwater quality issue in India impacting human health. In the present study, 14 different hydrochemical parameters for 76 groundwater samples collected from the Jajpur district of Odisha, India, were evaluated. Entropy-weighted water quality index (EWQI), fixed-weight groundwater quality index (GWQI), principal component analysis (PCA), and rotated factor loading-based water quality index (PCWQI) were employed to assess groundwater quality. About 65.79 ± 4.68%, 33.55 ± 3.95%, and 0.66 ± 0.76% of the samples were rated as "excellent," "good," or "medium" quality, respectively, across the four different water quality indices, with a nominal rating discrepancy of 13.15%. Though 86% of samples consistently received excellent or good ratings across all WQI frameworks, concentrations of F- and NO3- in 36.8% and 11.84% of the samples exceeded the WHO permissible limit. In health risk assessment, about 38.15% of samples surpassed the F- hazard quotient (HQ > 1) posing non-carcinogenic health risks for children. The non-carcinogenic health risks due to NO3- were evident in 55.26% and 11.84% of samples for children and adults, respectively. The higher concentration of NO3- in some of the water samples, together with its positive correlation with HCO3-, may worsen groundwater pollution. The moderate correlation between Ca2+ and HCO3- (r = 0.410) and the insignificant correlation between Mg2+ and HCO3- (r = 0.234) suggests calcite dissolution is far more common than dolomite.

Eucalyptus Oils Phytochemical Composition in Correlation with Their Newly Explored Anti-SARS-CoV-2 Potential: in Vitro and in Silico Approaches.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the latest arisen contagious respiratory pathogen related to the global outbreak of atypical pneumonia pandemic (COVID-19). The essential oils (EOs) of Eucalyptus camaldulensis, E. ficifolia F. Muell., E. citriodora Hook, E. globulus Labill, E. sideroxylon Cunn. ex Woolls, and E. torquata Luehm. were investigated for its antiviral activity against SARS-CoV-2. The EOs phytochemical composition was determined using GC/MS analysis. Correlation with the explored antiviral activity was also studied using multi-variate data analysis and Pearson's correlation. The antiviral MTT and cytopathic effect inhibition assays revealed very potent and promising anti SARS-CoV-2 potential for E. citriodora EO (IC50 = 0.00019 µg/mL and SI = 26.27). The multivariate analysis revealed α-pinene, α-terpinyl acetate, globulol, γ -terpinene, and pinocarvone were the main biomarkers for E. citriodora oil. Pearson's correlation revealed that globulol is the top positively correlated compound in E. citriodora oil to its newly explored potent anti SARS-CoV-2 potential. A molecular simulation was performed on globulol via docking in the main active sites of both SARS-CoV-2 viral main protease (Mpro) and spike protein (S). In silico predictive ADMET study was also developed to investigate the pharmacokinetic profile and predict globulol toxicity. The obtained in silico, in vitro and Pearson's correlation results were aligned showing promising SARS-CoV-2 inhibitory activity of E. citriodora and globulol. This study is a first record for E. citriodora EO as a novel lead exhibiting potent in vitro, and in silico anti SARS-CoV-2 potential and suggesting its component globulol as a promising candidate for further extensive in silico, in vitro and in vivo anti-COVID studies.

Evolution and health risk of indicator microorganisms in landscape water replenished by reclaimed water.

As an important means to solve water shortage, reclaimed water has been widely used for landscape water supply. However, with the emergence of large-scale epidemic diseases such as SARS, avian influenza and COVID-19 in recent years, people are increasingly concerned about the public health safety of reclaimed water discharged into landscape water, especially the pathogenic microorganisms in it. In this study, the water quality and microorganisms of the Old Summer Palace, a landscape water body with reclaimed water as the only replenishment water source, were tracked through long-term dynamic monitoring. And the health risks of indicator microorganisms were analyzed using Quantitative Microbial Risk Assessment (QMRA). It was found that the concentration of indicator microorganisms Enterococcus (ENT), Escherichia coli (EC) and Fecal coliform (FC) generally showed an upward trend along the direction of water flow and increased by more than 0.6 log at the end of the flow. The concentrations of indicator microorganisms were higher in summer and autumn than those in spring. And there was a positive correlation between the concentration of indicator microorganisms and COD. Further research suggested that increased concentration of indicator microorganisms also led to increased health risks, which were more than 30% higher in other areas of the park than the water inlet area and required special attention. In addition, (water) surface operation exposure pathway had much higher health risks than other pathways and people in related occupations were advised to take precautions to reduce the risks.

GeCoNet-Tool: a software package for gene co-expression network construction and analysis.

BACKGROUND: Network analysis is a powerful tool for studying gene regulation and identifying biological processes associated with gene function. However, constructing gene co-expression networks can be a challenging task, particularly when dealing with a large number of missing values. RESULTS: We introduce GeCoNet-Tool, an integrated gene co-expression network construction and analysis tool. The tool comprises two main parts: network construction and network analysis. In the network construction part, GeCoNet-Tool offers users various options for processing gene co-expression data derived from diverse technologies. The output of the tool is an edge list with the option of weights associated with each link. In network analysis part, the user can produce a table that includes several network properties such as communities, cores, and centrality measures. With GeCoNet-Tool, users can explore and gain insights into the complex interactions between genes.

Integrated metabolomics and transcriptomics analyses reveal the key genes regulating differential metabolites of longissimus dorsi muscle in castrated South Sichuan black goats (Capra hircus).

The main aim of the current work was to explore the differential metabolites and differentially expressed genes of longissimus dorsi muscle (LDM) between castrated and uncastrated fattening male South Sichuan black goats (Capra hircus). Then, the key genes regulating important differential metabolites (DMs) in castrated male goats were observed by integrated metabolomics and transcriptomics analyses. In addition, we evaluated the effects of castration on blood constituents, dressing percentage, and water holding capacity of LDM in male black goats. The results showed that the concentrations of alkaline phosphatase (ALP), total cholesterol (TC), triglyceride (TG), and low-density lipoprotein cholesterol (LDL-C) were significantly increased and testosterone was significantly decreased in castrated male goats compared with the uncastrated male goats, while dressing percentage of black goats and water holding capacity of longissimus dorsi muscle were not significant differences. Through metabolomics and transcriptomics analyses, 23 important KEGG pathways, 13 important DMs, 32 important differentially expressed genes (DEGs), and 13 key genes related to the "Metabolism" and "Organismal systems" pathways were screened. Lipid accumulation may be elevated in the blood of fattening South Sichuan black goats after castration. Castration might play a positive role in energy provision, intercellular signaling, muscle function, softening of meat, disease reduction, and anti-oxidation of LDM. P4HA2, AKR1B1, GPT2, L2HGDH, ENSCHIG00000021660, ENSCHIG00000023861, DGAT2, ULK1, SLC38A3, PLA2G4A, SLC6A1, ENSCHIG00000026624, and ND2 might be the key genes regulating important DMs in the KEGG pathways related to "Metabolism" and "Organismal systems" of castrated male goats compared with the uncastrated male goats.

Neurochemical correlations in short echo time proton magnetic resonance spectroscopy.

Neurochemical concentrations determined by magnetic resonance spectroscopy (MRS) have been treated as statistically independent measurements in various clinical MRS studies. However, spectral overlap, independent of any biological effects, could lead to significant correlations between neurochemical concentrations extracted from spectral fitting of MRS data, confounding determination of correlations of biological origin. Short echo time (TE) proton MRS spectra are very crowded because of the comparatively narrow chemical shift dispersion of proton nuclear spins. In this study, the complex neurochemical correlations of spectral origin in short-TE MRS spectra were quantified. The effects of macromolecules and the background spectral baseline on metabolite-metabolite correlations were also analyzed. Our results demonstrate the importance of factoring in spectral correlations when correlating overlapping metabolite signals in short-TE spectra with clinical parameters.

A robust and fast two-sample test of equal correlations with an application to differential co-expression.

A robust and fast two-sample test for equal Pearson correlation coefficients (PCCs) is important in solving many biological problems, including, for example, analysis of differential co-expression. However, few existing methods for this test can achieve robustness against deviation from normal distributions, accuracy under small sample sizes, and computational efficiency simultaneously. Here, we propose a new method for testing differential correlation using a saddlepoint approximation of the residual bootstrap (DICOSAR). To achieve robustness, accuracy, and efficiency, DICOSAR combines the ideas underlying the pooled residual bootstrap, the signed root of a likelihood ratio statistic, and a multivariate saddlepoint approximation. Through a comprehensive simulation study and a real data analysis of gene co-expression, we demonstrate that DICOSAR is accurate and robust in controlling the type I error rate for detecting differential correlation and provides a faster alternative to the bootstrap and permutation methods. We further show that DICOSAR can also be used for testing differential correlation matrices. These results suggest that DICOSAR provides an analytical approach to facilitate rapid testing for the equality of PCCs in large-scale analysis.