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BackgroundHashimoto's thyroiditis (HT) frequently occurs among autoimmune diseases and may simultaneously appear with thyroid cancer. However, it is difficult to diagnose HT at an early stage just by clinical symptoms. Thus, it is urgent to integrate multiple clinical and laboratory factors for the early diagnosis and risk prediction of HT.MethodsWe recruited 1,303 participants, including 866 non-HT controls and 437 diagnosed HT patients. 44 HT patients also had thyroid cancer. Firstly, we compared the difference in thyroid goiter degrees between controls and patients. Secondly, we collected 15 factors and analyzed their significant differences between controls and HT patients, including age, body mass index, gender, history of diabetes, degrees of thyroid goiter, UIC, 25-(OH)D, FT3, FT4, TSH, TAG, TC, FPG, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol. Thirdly, logistic regression analysis demonstrated the risk factors for HT. For machine learning modeling of HT and thyroid cancer, we conducted the establishment and evaluation of six models in training and test sets.ResultsThe degrees of thyroid goiter were significantly different among controls, HT patients without cancer (HT-C), and HT patients with thyroid cancer (HT+C). Most factors had significant differences between controls and patients. Logistic regression analysis confirmed diabetes, UIC, FT3, and TSH as important risk factors for HT. The AUC scores of XGBoost, LR, SVM, and MLP models indicated appropriate predictive power for HT. The features were arranged by their importance, among which, 25-(OH)D, FT4, and TSH were the top three high-ranking factors.ConclusionsWe firstly analyzed comprehensive factors of HT patients. The proposed machine learning modeling, combined with multiple factors, are efficient for thyroid diagnosis. These discoveries will extensively promote precise diagnosis, personalized therapies, and reduce unnecessary cost for thyroid diseases.

Rheumatoid arthritis (RA) is an immune-mediated disease affecting diarthrodial joints that remains an unmet medical need despite improved therapy. This limitation likely reflects the diversity of pathogenic pathways in RA, with individual patients demonstrating variable responses to targeted therapies. Better understanding of RA pathogenesis would be aided by a more complete characterization of the disease. To tackle this challenge, we develop and apply a systems biology approach to identify important transcription factors (TFs) in individual RA fibroblast-like synoviocyte (FLS) cell lines by integrating transcriptomic and epigenomic information. Based on the relative importance of the identified TFs, we stratify the RA FLS cell lines into two subtypes with distinct phenotypes and predicted active pathways. We biologically validate these predictions for the top subtype-specific TF RARα and demonstrate differential regulation of TGFβ signaling in the two subtypes. This study characterizes clusters of RA cell lines with distinctive TF biology by integrating transcriptomic and epigenomic data, which could pave the way towards a greater understanding of disease heterogeneity.

Current pooled CRISPR screens for cis-regulatory elements (CREs), based on transcriptional output changes, are typically limited to characterizing CREs of only one gene. Here, we describe CRISPRpath, a scalable screening strategy for parallelly characterizing CREs of genes linked to the same biological pathway and converging phenotypes. We demonstrate the ability of CRISPRpath for simultaneously identifying functional enhancers of six genes in the 6-thioguanine–induced DNA mismatch repair pathway using both CRISPR interference (CRISPRi) and CRISPR nuclease (CRISPRn) approaches. Sixty percent of the identified enhancers are known promoters with distinct epigenomic features compared to other active promoters, including increased chromatin accessibility and interactivity. Furthermore, by imposing different levels of selection pressure, CRISPRpath can distinguish enhancers exerting strong impact on gene expression from those exerting weak impact. Our results offer a nuanced view of cis-regulation and demonstrate that CRISPRpath can be leveraged for understanding the complex gene regulatory program beyond transcriptional output at scale.

Acute liver injury is a common and serious syndrome caused by multiple factors and unclear pathogenesis. If the injury persists, liver injury can lead to cirrhosis and liver failure and ultimately results in the development of liver cancer. Emerging evidence has indicated that long noncoding RNAs (lncRNAs) play an important role in the development of liver injury. However, the role of antisense Igf2r RNA (Airn) in acute liver injury and its underlying mechanism remain largely unclear. In this study, we show that Airn is upregulated in liver tissue and primary hepatocytes from an acute liver injury mouse model. Consistently, Airn is also overexpressed in serum samples of patients with acute-on-chronic liver failure and is negatively correlated with the Model for End-Stage Liver Disease (MELD) score. Moreover, gene knockout and rescue assays reveal that Airn alleviates CCl 4-induced liver injury by inhibiting hepatocyte apoptosis and oxidative stress in vivo. Further investigation reveals that Airn decreases H 2O 2-induced hepatocyte apoptosis in vitro. Mechanistically, we reveal that Airn represses CCl 4- and H 2O 2-induced enhancement of phosphorylation of p65 and IκBα, suggesting that Airn inhibits hepatocyte apoptosis by inactivating the NF-κB pathway. In conclusion, our results demonstrate that Airn can alleviate acute liver injury by inhibiting hepatocyte apoptosis via inactivating the NF-κB signaling pathway, and Airn could be a potential biomarker for acute liver injury.

The volume of natural rubber vulcanizates varied slightly during stretching. Hydrostatic weighing method was adopted in this study to study the volume change. By measuring the volume change of natural rubber compounds filled with different grades and different loadings of carbon black during extension, the corresponding volume variation-elongation ([DELTA]V/V-[epsilon]) curves were created, and the differences of [DELTA]V/V-[epsilon] curves among different carbon black compounds were discussed. The stress differences between different samples were normalized and the [DELTA]V/(V[sigma])-[epsilon] curves were plotted. Scanning electron microscope was utilized to observe the emergence and variation process of cavities in various stretched states. X-ray diffraction was used to explore the change of crystallinity of the rubber after stretching to a certain elongation. Based on the experimental results, the damage at the filler-rubber matrix interface and within the fillers agglomerates would be discussed. KEYWORDS breakdown of agglomerates, cavity, polymer-filler interaction, strain-induced crystallization, volume change, 1 | INTRODUCTION Studies on volume change of vulcanizate during stretching began as early as the 1880s. [1] Schippel [1] reported in 1920 that the density of vulcanizates changed during [...]

Background: Sepsis‐associated encephalopathy (SAE) is a neuronal injury with poor prognosis. Mitochondrial dysfunction is critical in SAE development, and hydrogen gas (H2) has a protective effect on septic mice. This study aimed to investigate the effect of high concentration (67%) of H2 on SAE and whether it is related to mitochondrial biogenesis and mitochondrial dynamics. Methods: A mouse sepsis model was induced by cecal ligation and puncture. The mice inhalated 67% H2 for 1 h at 1 and 6 h post‐surgery, respectively. The 7‐day survival rate was recorded. Cognitive function was assessed using the Y‐maze test and Morris water maze test. Serum inflammatory factors, antioxidant enzymes, as well as mitochondrial function indexes including mitochondrial membrane potential (MMP) and ATP in the hippocampal tissue were evaluated 24 h after surgery. Mitochondrial dynamic proteins (DRP1 and MFN2) and biosynthetic proteins (PGC‐1α, NRF2, and TFAM) in the hippocampal tissue were detected. Moreover, the morphology of mitochondria was observed by transmission electron microscopy. Results: Inhalation of 67% H2 improved the 7‐day survival rates and recognition memory function of septic mice, alleviated brain antioxidant enzyme activity (SOD and CAT), and reduced serum proinflammatory cytokine levels. H2 inhalation also enhanced the expression of MFN2 and mitochondrial biogenesis‐related factors (PGC‐1α, NRF2, and TFAM) and decreased the expression of fission protein (DRP1), leading to improvement in mitochondrial function, as evidenced by MMP and ATP levels. Conclusions: Inhalation of high concentration (67%) of H2 in septic mice improved the survival rate and reduced neuronal injury. Its mechanism might be mediated by enhancing mitochondrial biogenesis and mitochondrial dynamics. [ABSTRACT FROM AUTHOR]

The fracture mechanism and macro-properties of SVSAC were studied using a novel test system combined with numerical simulations, which included three-point bending beam tests, the digital image correlation (DIC) technique, scanning electron microscopy (SEM), and ABAQUS analyses. In total, 9 groups and 36 specimens were fabricated by considering two critical parameters: initial notch-to-depth ratios (a0/h) and concrete mix components (seawater and volcanic scoria coarse aggregate (VSCA)). Changes in fracture parameters, such as the load-crack mouth opening displacement curve (P-CMOD), load-crack tip opening displacement curve (P-CTOD), and fracture energy (Gf), were obtained. The typical double-K fracture parameters (i.e., initial fracture toughness ( K IC ini ) and unstable fracture toughness ( K IC un )) and tension-softening (σ-CTOD) curve were analyzed. The test results showed that the initial cracking load (Pini), Gf, and characteristic length (Lch) of the SVSAC increased with decreasing a0/h. Compared with the ordinary concrete (OC) specimen, the P-CMOD and P-CTOD curves of the specimen changed after using seawater and VSCA. The evolution of the crack propagation length was obtained through the DIC technique, indicating cracks appeared earlier and the fracture properties of specimen decreased after using VSCA. Generally, the K IC un and K IC ini of SVSAC were 36.17% and 8.55% lower than those of the OC specimen, respectively, whereas the effects of a0/h were negligible. The reductions in Pini, Gf, and Lch of the specimen using VSCA were 10.94%, 32.66%, and 60.39%, respectively; however, seawater efficiently decreased the negative effect of VSCA on the fracture before the cracking width approached 0.1 mm. Furthermore, the effects of specimen characteristics on the fracture mechanism were also studied through numerical simulations, indicating the size of the beam changed the fracture toughness. Finally, theoretical models of the double-K fracture toughness and the σ-CTOD relations were proposed, which could prompt their application in marine structures. [ABSTRACT FROM AUTHOR]