NR2C2 of macrophages promotes inflammation via NF-κB in LPS-induced orchitis in mice.

In Brief: Bacterial infection can induce testicular inflammation and damage male fertility. This paper reveals the role of nuclear receptor subfamily 2 group C member 2 (NR2C2) in macrophage cells in orchitis caused by bacterial endotoxin lipopolysaccharide (LPS) infection.

Abstract: Bacterial infection and induced inflammation are important causes of male infertility.

Pancancer survival prediction using a deep learning architecture with multimodal representation and integration.

Motivation: Use of multi-omics data carrying comprehensive signals about the disease is strongly desirable for understanding and predicting disease progression, cancer particularly as a serious disease with a high mortality rate. However, recent methods currently fail to effectively utilize the multi-omics data for cancer survival prediction and thus significantly limiting the accuracy of survival prediction using omics data.

Results: In this work, we constructed a deep learning model with multimodal representation and integration to predict the survival of patients using multi-omics data.

Chromodomain helicase DNA-binding domain 2 maintains spermatogonial self-renewal by promoting chromatin accessibility and mRNA stability.

Chromodomain helicase DNA-binding domain 2 (CHD2) is a chromatin remodeling factor involved in many developmental processes. However, its role in male germ cell development has not been elucidated. Here, we confirm that CHD2 expression is enriched in the male germline.

microRNA-196a-5p inhibits testicular germ cell tumor progression via NR6A1/E-cadherin axis.

Testicular germ cell tumors (TGCTs) are a diverse group of neoplasms that are derived from dysfunctional fetal germ cells and can also present in extragonadal sites. The genetic drivers underlying malignant transformation of TGCTs have not been fully elucidated so far. The aim of the present study is to clarify the functional role and regulatory mechanism of miR-196a-5p in TGCTs.

MetFID: artificial neural network-based compound fingerprint prediction for metabolite annotation.

Introduction: Metabolite annotation is a critical and challenging step in mass spectrometry-based metabolomic profiling. In a typical untargeted MS/MS-based metabolomic study, experimental MS/MS spectra are matched against those in spectral libraries for metabolite annotation. Yet, existing spectral libraries comprise merely a marginal percentage of known compounds.

MOTA: Network-Based Multi-Omic Data Integration for Biomarker Discovery.

The recent advancement of omic technologies provides researchers with the possibility to search for disease-associated biomarkers at the system level. The integrative analysis of data from a large number of molecules involved at various layers of the biological system offers a great opportunity to rank disease biomarker candidates. In this paper, we propose MOTA, a network-based method that uses data acquired at multiple layers to rank candidate disease biomarkers.

MOTA: Multi-omic integrative analysis for biomarker discovery.

Recent advancement of omic technologies provides researchers with opportunities to search for disease biomarkers at the systems level. However, selection of biomarker candidates from a large number of molecules involved at various layers of the biological system is challenging. In this paper, we propose multi-omic integrative analysis (MOTA), a network-based method that uses information from multi-omic data to identify candidate disease biomarkers.

Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) causes more than half a million annual deaths worldwide. Understanding the mechanisms contributing to HCC development is highly desirable for improved surveillance, diagnosis, and treatment. Liver tissue metabolomics has the potential to reflect the physiological changes behind HCC development.

H NMR plasma metabolomic profiling of ovarian quiescence in energy balanced postpartum dairy cows.

Background: As the milk production of dairy cows increases, the reproductive capacity gradually declines. Ovarian quiescence has become one of the concerns of the dairy industry.

Objective: To explore the different plasma metabolite levels between estrus and anestrus in energy balanced (EB) dairy cows.

Protein profiling of plasma proteins in dairy cows with subclinical hypocalcaemia.

Subclinical hypocalcaemia (SH) is an important metabolic disease in dairy cows that has a serious impact on production performance. The objective of this study was to investigate novel aspects of pathogenesis using proteomics technology to identify proteins that are differentially expressed in diseased and healthy animals. Dairy cows were divided into an SH group (T,  = 10) and a control group (C,  = 10) based on plasma calcium concentration.

Differentially expressed serum proteins associated with calcium regulation and hypocalcemia in dairy cows.

Objective: Hypocalcemia is an important metabolic disease of dairy cows during the transition period, although the effect of hypocalcemia on biological function in dairy cows remains unknown.

Methods: In this study, proteomic, mass spectrum, bioinformatics and western blotting were employed to identify differentially expressed proteins related to serum Ca concentration. Serum samples from dairy cows were collected at three time points: 3rd days before calving (day -3), the day of calving (day 0), and 3rd days after calving (day +3).

Metabolic profiles using (1)H-nuclear magnetic resonance spectroscopy in postpartum dairy cows with ovarian inactivity.

To understand the differences in metabolic changes between cows with ovarian inactivity and estrus cows, we selected cows at 60-90 days postpartum from an intensive dairy farm. According to clinical manifestations, B-ultrasound scan, rectal examination, 10 cows were assigned to the estrus group (A) and 10 to the ovarian inactivity group (B). All plasma samples were analyzed by (1)H-nuclear magnetic resonance spectroscopy to compare plasma metabolomic profiles between the groups.

Relative Biological Effectiveness of Energetic Heavy Ions for Intestinal Tumorigenesis Shows Male Preponderance and Radiation Type and Energy Dependence in APC(1638N/+) Mice.

Purpose: There are uncertainties associated with the prediction of colorectal cancer (CRC) risk from highly energetic heavy ion (HZE) radiation. We undertook a comprehensive assessment of intestinal and colonic tumorigenesis induced after exposure to high linear energy transfer (high-LET) HZE radiation spanning a range of doses and LET in a CRC mouse model and compared the results with the effects of low-LET γ radiation.

Methods And Materials: Male and female APC(1638N/+) mice (n=20 mice per group) were whole-body exposed to sham-radiation, γ rays, (12)C, (28)Si, or (56)Fe radiation.