Search

Objective: This study aimed to analyze the effects of ward night noise management in the context of enhanced recovery after surgery (ERAS) on postoperative sleep quality and anxiety of thoracic surgery patients with lung cancer. Methods: This retrospective analysis included 118 patients with lung cancer who underwent thoracic surgery (from January 2020 to December 2021). The patients were categorized into the control and observation groups, which comprised 63 and 55 cases, respectively, on the basis of perioperative management plans. The two groups were compared in terms of their score in Athens Insomnia Scale (AIS), the State-Trait Anxiety Inventory (STAI) and Self-Rating Depression Scale (SDS), salivary cortisol (SC), thyroid hormone (TSH), and angiotensin II (Ang II) levels, and noise measurements at various timepoints. Results: The observation group exhibited a significantly lower noise level than the control group (P < 0.001). No statistically significant difference was found in the AIS, STAI, and SDS scores and Ang II, TSH and SC levels between the two groups before their surgery (P > 0.05). Compared with the control group, the observation group achieved significantly lower AIS scores at 1, 3 and 7 days after surgery (P < 0.05) and significantly lower STAI scores at 1 and 3 days postsurgery (P < 0.05). Significantly lower Ang II, TSH and SC indices were observed in the observation group after management than the control group (P < 0.05). Conclusion: Night noise management in the context of ERAS can improve sleep quality and adverse moods of patients who underwent thoracic surgery for lung cancer, which helps in the promotion of prognosis.

Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratification and efficient screening of high-risk patients, thereby facilitating clinical decision-making. Herein, we performed a comprehensive, robust DNA methylation analysis based on genome-wide DNA methylation profiling. We constructed a diagnostic signature with five DNA methylation markers, which precisely distinguished HCC patients from normal controls. Cox regression and LASSO analysis were applied to construct a prognostic signature with four DNA methylation markers. A one-to-one correlation analysis was carried out between genes of the whole genome and our prognostic signature. Exploration of the biological function and the role of the underlying significantly correlated genes was conducted. A mixed dataset of 463 HCC patients and 253 normal controls, derived from six independent datasets, was used to valid the diagnostic signature. Results showed a specificity of 96.84% and sensitivity of 96.77%. Class scores for the diagnostic signature were significantly different between normal controls, individuals with liver diseases, and HCC patients. The present signature has the potential to serve as a biomarker to monitor health in normal controls. Additionally, HCC patients were successfully separated into low-risk and high-risk groups by the prognostic signature, with a better prognosis for patients in the low-risk group. Kaplan-Meier and ROC analysis confirmed that the prognostic signature performed well. We found eight of the top ten genes to positively correlate with risk scores of the prognostic signature, and to be involved in cell cycle regulation. This eight-gene panel also served as a prognostic signature. The robust evidence presented in this study therefore demonstrates the effectiveness of the prognostic signature. In summary, we constructed diagnostic and prognostic signatures, which have potential for use in diagnosis, surveillance, and prognostic prediction for HCC patients. Eight genes that were significantly and positively correlated with the prognostic signature were strongly associated with cell cycle processes. Therefore, the prognostic signature can be used as a guide by which to measure responsiveness to cell-cycle-targeting agents.

Abstract Current single-cell RNA-seq approaches are hindered by preamplification bias, loss of strand of origin information, and the inability to observe small-RNA and mRNA dual transcriptomes. Here, we introduce a single-cell holo-transcriptome sequencing (Holo-Seq) that overcomes all three hurdles. Holo-Seq has the same quantitative accuracy and uniform coverage with a complete strand of origin information as bulk RNA-seq. Most importantly, Holo-Seq can simultaneously observe small RNAs and mRNAs in a single cell. Furthermore, we acquire small RNA and mRNA dual transcriptomes of 32 human hepatocellular carcinoma single cells, which display the genome-wide super-enhancer activity and hepatic neoplasm kinetics of these cells.

Abstract Background Highly polymorphic human leukocyte antigen (HLA) genes are responsible for fine-tuning the adaptive immune system. High-resolution HLA typing is important for the treatment of autoimmune and infectious diseases. Additionally, it is routinely performed for identifying matched donors in transplantation medicine. Although many HLA typing approaches have been developed, the complexity, low-efficiency and high-cost of current HLA-typing assays limit their application in population-based high-throughput HLA typing for donors, which is required for creating large-scale databases for transplantation and precision medicine. Results Here, we present a cost-efficient Saturated Tiling Capture Sequencing (STC-Seq) approach to capturing 14 HLA class I and II genes. The highly efficient capture (an approximately 23,000-fold enrichment) of these genes allows for simplified allele calling. Tests on five genes (HLA-A/B/C/DRB1/DQB1) from 31 human samples and 351 datasets using STC-Seq showed results that were 98% consistent with the known two sets of digitals (field1 and field2) genotypes. Additionally, STC can capture genomic DNA fragments longer than 3 kb from HLA loci, making the library compatible with the third-generation sequencing. Conclusions STC-Seq is a highly accurate and cost-efficient method for HLA typing which can be used to facilitate the establishment of population-based HLA databases for the precision and transplantation medicine.

The activation of TGF-β signaling has been implicated in cancer metastasis. Here, the authors show that OTUD1 suppresses metastasis by antagonizing the TGF-β pathway via the deubiquitination of SMAD7, and its loss correlates with poor prognosis in breast cancer.

Macrophage metabolism controls differentiation and subsequent adaptive immune responses. Here the authors show that mitochondrial membrane protein Fam73b regulates TLR-mediated mitochondrial switching of fusion to fission to induce IL-12 production via accumulation of Parkin and stabilization of IRF1 in macrophages, resulting in control of anti-tumor immunity in mice.

Aberrant activation of TGF-β signalling promotes cancer metastasis but the initial steps of this activation are unclear. Here Xieet al. show that FAF1 regulates the surface levels of TGF-β type II receptor thus influencing the persistence of the signalling and breast cancer metastasis.

Understanding how chromatin modification regulates development and disease can be limited by available material. Despite recent progress, balancing high-quality and reliable mapping using chromatin-immunoprecipitation-based deep sequencing (ChIP-seq) remains a challenge. We report two techniques, recovery via protection (RP)-ChIP-seq and favored amplification RP-ChIP-seq (FARP-ChIP-seq), that provide reproducible mapping in as few as 500 cells. RP-ChIP-seq allows detection of age-associated epigenetic changes in a single mouse lens, whereas FARP-ChIP-seq accurately maps histone H3 lysine 4 trimethylation (H3K4me3) and H3K27me3 in long-term hematopoietic stem cells (LT-HSCs), short-term HSCs (ST-HSCs), and multi-potent progenitors (MPPs) from one mouse. These datasets not only highlight genes that may be involved in lens aging but also indicate a lack of H3K4me3/H3K27me3 bivalency on hematopoietic genes in HSCs.

[This corrects the article DOI: 10.1371/journal.pone.0206844.].

BACKGROUND:Key regulators of developmental processes can be prioritized through integrated analysis of ChIP-Seq data of master transcriptional factors (TFs) such as Nanog and Oct4, active histone modifications (HMs) such as H3K4me3 and H3K27ac, and repressive HMs such as H3K27me3. Recent studies show that broad enrichment signals such as super-enhancers and broad H3K4me3 enrichment signals play more dominant roles than short enrichment signals of the master TFs and H3K4me3 in epigenetic regulatory mechanism. Besides the broad enrichment signals, up to ten thousands of short enrichment signals of these TFs and HMs exist in genome. Prioritization of these broad enrichment signals from ChIP-Seq data is a prerequisite for such integrated analysis. RESULTS:Here, we present a method named Clustering-Local-Unique-Enriched-Signals (CLUES), which uses an adaptive-size-windows strategy to identify enriched regions (ERs) and cluster them into broad enrichment signals. Tested on 62 ENCODE ChIP-Seq datasets of Ctcf and Nrsf, CLUES performs equally well as MACS2 regarding prioritization of ERs with the TF's motif. Tested on 165 ENCODE ChIP-Seq datasets of H3K4me3, H3K27me3, and H3K36me3, CLUES performs better than existing algorithms on prioritizing broad enrichment signals implicating cell functions influenced by epigenetic regulatory mechanism in cells. Most importantly, CLUES helps to confirm several novel regulators of mouse ES cell self-renewal and pluripotency through integrated analysis of prioritized broad enrichment signals of H3K4me3, H3K27me3, Nanog and Oct4 with the support of a CRISPR/Cas9 negative selection genetic screen. CONCLUSIONS:CLUES holds promise for prioritizing broad enrichment signals from ChIP-Seq data. The download site for CLUES is https://github.com/Wuchao1984/CLUESv1.

Starvation induces sustained increase in locomotion, which facilitates food localization and acquisition and hence composes an important aspect of food-seeking behavior. We investigated how nutritional states modulated starvation-induced hyperactivity in adult Drosophila. The receptor of the adipokinetic hormone (AKHR), the insect analog of glucagon, was required for starvation-induced hyperactivity. AKHR was expressed in a small group of octopaminergic neurons in the brain. Silencing AKHR+ neurons and blocking octopamine signaling in these neurons eliminated starvation-induced hyperactivity, whereas activation of these neurons accelerated the onset of hyperactivity upon starvation. Neither AKHR nor AKHR+ neurons were involved in increased food consumption upon starvation, suggesting that starvation-induced hyperactivity and food consumption are independently regulated. Single cell analysis of AKHR+ neurons identified the co-expression of Drosophila insulin-like receptor (dInR), which imposed suppressive effect on starvation-induced hyperactivity. Therefore, insulin and glucagon signaling exert opposite effects on starvation-induced hyperactivity via a common neural target in Drosophila.

Abstract Objective To investigate the effects of Lathyrol on the expression of androgen receptor (AR) and sphingosine kinase 2 (SPHK2) in renal cell carcinoma (RCC) mice and to further explore the mechanism by which Lathyrol inhibits the invasion and incidence of epithelial-mesenchymal transition (EMT). Methods An RCC xenograft mouse model was constructed, and the mice were randomly divided into a model group, an experiment group and a negative control group. The experiment group was intragastrically gavaged with Lathyrol solution (20 mg/kg), the model group was intragastrically gavaged with 0.9% NaCl (same volume as that used in the experiment group), and the negative control group was injected intraperitoneally with 2 mg/kg cisplatin aqueous solution. Changes in the body weight and tumor volume of the mice were recorded. Western blot (WB) was used to assess the protein expression levels of AR, p-AR, CYP17A1, PARP1, E-cadherin, N-cadherin, vimentin, α-SMA, β-catenin, and ZO-1. Protein expression levels of SPHK2, metal matrix protease 2 (MMP2), MMP9 and urokinase-type plasminogen activator (uPA) in tumor tissues were assessed by immunohistochemistry (IHC). AR expression in tumor tissues was assessed after immunofluorescence (IF) staining. Results After 14 days of drug administration, compared with that in the model group, the tumor volumes in the negative control and experiment groups were lower; the difference in tumor volume among the model, control and experiment groups was statistically significant (P 0.05). In the model group, the protein expression levels of AR, p-AR, CYP17A1, SPHK2, and PARP1 were relatively increased, the protein expression levels of E-cadherin and ZO-1 were relatively reduced (P

This paper proposes an improved analysis method based on the theory of structural vulnerability, which incorporates structural redundancy and comprehensively analyzes structural vulnerability and robustness by considering the changes in structural stiffness and redundancy after damage to structural members under conventional loading. The improved method takes into account the changes in the strain energy of the structure after the damage of the structural members, which can be more in line with the actual situation of continuity collapse, and solves the complex process of traditional structural vulnerability theory that requires clustering and unclustering, greatly reducing the workload as well as solving the problem of not being able to find the critical members of the structure. The improved method is used to analyze the vulnerability of a 5-story dropped-story steel frame structure, to find the critical members of the structure based on the test data simulated by ABAQUS, to evaluate the robustness, and to propose improvement measures. The results show that the improved vulnerability assessment method is more reasonable and effective and can be applied to different steel frame structures.

The steel frame structure plays an important role in strategic deployments and is widely used in heavy machinery, metallurgy, military, and other important industries. To study the impact of explosive loads on the anti-progressive collapse performance of steel structures, this paper proposes to establish the vulnerability characteristics of steel frame structures and provides a method for calculating vulnerability characterization indicators. A finite element model is used to analyze the dynamic response of steel frame structures under the action of close-range explosive loads, and factors influencing the anti-progressive collapse of steel frame structures are proposed, including the number of stories and diagonal bracing. A comparison is made between the various column types of steel structures under explosive loads, such as corner columns, long-edge middle columns, short-edge middle columns, inner columns, also in various coupling conditions. The results show that the progressive collapse of steel frame structures is greatly influenced by the position of the explosion and less affected by the amount of explosive material. The simultaneous failure of corner columns and long-edge middle columns is more likely to cause overall structural failure. The addition of diagonal bracing significantly improves the anti-progressive collapse ability and prevents the lateral displacement of steel frame structures; increasing the number of stories provides more alternative load transfer paths for steel frame structures, thereby preventing their collapse.

In order to study the effect of the support mode of a staggered truss system on the continuous collapse resistance performance of a steel structure, four finite element models were established based on the bracing arrangement of a five-story steel frame structure. The situations of different columns on the first floor removed were classified into eight scenarios, and five models of each scenario were analyzed with nonlinear dynamic analyses. Finally, a computational metric based on energy robustness was proposed to evaluate the robustness of the structure. The results of nonlinear dynamic analyses indicated that the staggered truss system significantly improved the resistance to progressive collapse of steel frame structures and effectively increased the redundancy of steel frame structures. All four bracing methods effectively reduced the vertical displacement at the point of failure, with the peak displacement at the point of failure reduced by a maximum of 84 percent and a minimum of 41 percent compared to a pure frame structure. Moreover, the staggered truss system can reduce some axial force peaks in the adjacent columns adjacent to the failed columns. The structural robustness coefficients of Model A, Scheme 1, Scheme 2, Scheme 3, and Scheme 4 are 1.144, 1.339, 1.306, 1.584, and 1.176, respectively, according to the proposed robustness calculation method, which shows that the braced steel frame structure has improved robustness over the original structure. The staggered truss system improves the robustness of the steel frame structure so that the steel frame structure has better resistance to progressive collapse.

We aimed to investigate the extent to which the initial state generated by unexpected loads, such as explosions and impacts on the remaining structure, affects the dynamic response of the structure. The study used the orthogonal test method to obtain orthogonal table L25 (53) by combining five levels of each of the three factors of column removal time and initial velocity, and the initial displacement of the remaining structure under three failure scenarios of the corner, side, and internal columns at the ground floor of the reinforced concrete frame structure. The degree of influence of different factors on the structural dynamic response, and the result of the unifactorial impact of initial velocity and initial displacement of the remaining structure on the structural dynamic response in the case of failure of the bottom side columns, were obtained by the polar difference method. The results show that the analysis using the orthogonal test polar difference method revealed that the initial displacement has a more significant influence on the dynamic response of the structure, forming the main influencing factor. At the same time, the failure time and initial velocity have a smaller influence on the dynamic response of the structure as secondary influencing factors. In the case of unifactorial influence, the initial upward displacement and initial upward velocity are detrimental to the structure, leading to progressive collapse. In contrast, the initial downward velocity and initial downward displacement are favorable.