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Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression of tens of thousands of single cells simultaneously. We present DeepImpute, a deep neural network-based imputation algorithm that uses dropout layers and loss functions to learn patterns in the data, allowing for accurate imputation. Overall, DeepImpute yields better accuracy than other six publicly available scRNA-seq imputation methods on experimental data, as measured by the mean squared error or Pearson’s correlation coefficient. DeepImpute is an accurate, fast, and scalable imputation tool that is suited to handle the ever-increasing volume of scRNA-seq data, and is freely available at https://github.com/lanagarmire/DeepImpute .

Although radiotherapy can promote antitumour immunity, the mechanisms underlying this phenomenon remain unclear. Here, we demonstrate that the expression of the E3 ubiquitin ligase, tumour cell-intrinsic tripartite motif-containing 21 (TRIM21) in tumours, is inversely associated with the response to radiation and CD8 + T cell-mediated antitumour immunity in nasopharyngeal carcinoma (NPC). Knockout of TRIM21 modulates the cGAS/STING cytosolic DNA sensing pathway, potentiates the antigen-presenting capacity of NPC cells, and activates cytotoxic T cell-mediated antitumour immunity in response to radiation. Mechanistically, TRIM21 promotes the degradation of the mitochondrial voltage-dependent anion-selective channel protein 2 (VDAC2) via K48-linked ubiquitination, which inhibits pore formation by VDAC2 oligomers for mitochondrial DNA (mtDNA) release, thereby inhibiting type-I interferon responses following radiation exposure. In patients with NPC, high TRIM21 expression was associated with poor prognosis and early tumour relapse after radiotherapy. Our findings reveal a critical role of TRIM21 in radiation-induced antitumour immunity, providing potential targets for improving the efficacy of radiotherapy in patients with NPC. The molecular mechanisms determining the response to radiotherapy remain incompletely understood. Here, the authors demonstrate that the E3 ubiquitin ligase and intracellular Fc receptor, TRIM21, impairs CD8 + T cell responses in nasopharyngeal carcinoma tumour models following ionizing radiation.

The open and formative teaching approach within the framework of cross campus learning for English majors in universities reflects an open and inclusive spirit of teaching and problem-solving, a sustainable learning method and process, and an attitude towards cooperative teaching and learning. The English major, with its characteristics as a liberal arts major, is particularly suitable for open and nurturing teaching models within the framework of cross school studies. Students majoring in English in universities should cultivate the habit of lifelong learning in an open teaching and learning environment, and effectively utilize the learning community under the cross campus learning framework and actively adapt to the diverse scoring mechanism under the cross campus learning framework.

To conduct a systematic review of the efficacy and safety of Shenyankangfu tablets in combination with losartan potassium in the treatment of chronic glomerulonephritis. We searched PubMed, Embase, Cochrane Library, CNKI, WanFang Data, and WeiPu for comparative studies on Shenyankangfu tablets in combination with losartan potassium in the treatment of chronic glomerulonephritis. The search period runs from the establishment of the database until September 2021. Data extraction and quality evaluation were carried out on the documents that met the inclusion criteria, and a meta-analysis of the included literature was conducted using the RevMan5.3 software. A total of 17 randomized controlled trials that met the inclusion criteria were included, with a total sample size of 1680 patients (841 patients in the study group and 839 in the control group). The effective rate was significantly higher in the study group than in the control group [RR = 1.22, 95% CI (1.16, 1.27), P < 0.00001]. In addition, 24-hour urine protein levels [SMD = -1.11, 95% CI (-1.40, -0.83), P < 0.00001], urine NAG enzyme [SMD = -0.99, 95% CI (-1.27, -0.72), P < 0.00001], leukotactin-1 [SMD = -2.43, 95% CI (-3.50, -1.35), P < 0.00001], and the incidence of adverse reactions [RR = 0.43, 95% CI (0.28, 0.66), P < 0.00001] were lower in the study group when compared to the control group. It is safer to treat chronic glomerulonephritis with Shyenyankangfu tablets in combination with losartan potassium. At the same time, it alleviates disease-related symptoms, reduces the influence of cytokine levels, and has fewer adverse reactions, making it more conducive to disease recovery. However, additional multi-center, randomized, control trials with large sample sizes must be conducted to confirm the findings.

AP2/ERF transcription factor family plays an important role in plant development and stress responses. Previous studies have shed light on the evolutionary trajectory of the AP2 and DREB subfamilies. However, knowledge about the evolutionary history of the ERF subfamily in angiosperms still remains limited. In this study, we performed a comprehensive analysis of the ERF subfamily from 107 representative angiosperm species by combining phylogenomic and synteny network approaches. We observed that the expansion of the ERF subfamily was driven not only by whole-genome duplication (WGD) but also by tandem duplication (TD) and transposition duplication events. We also found multiple transposition events in Poaceae, Brassicaceae, Poales, Brassicales, and Commelinids. These events may have had notable impacts on copy number variation and subsequent functional divergence of the ERF subfamily. Moreover, we observed a number of ancient tandem duplications occurred in the ERF subfamily across angiosperms, e.g., in Subgroup IX, IXb originated from ancient tandem duplication events within IXa. These findings together provide novel insights into the evolution of this important transcription factor family.

MRIs obtained before and after long-duration spaceflight showed an upward shift of the brain, narrowing of the central sulcus, and narrowing of the cerebrospinal fluid spaces at the vertex. These effects were seen infrequently after short-duration flights.

Biomedical named entity recognition (BioNER) is an essential task in biomedical information analysis. Recently, deep neural approaches have become widely utilized for BioNER. Biomedical dictionaries, implemented through a masked manner, are frequently employed in these methods to enhance entity recognition. However, their performance remains limited. In this work, we propose a dictionary-based matching graph network for BioNER. This approach utilizes the matching graph method to project all possible dictionary-based entity combinations in the text onto a directional graph. The network is implemented coherently with a bi-directional graph convolutional network (BiGCN) that incorporates the matching graph information. Our proposed approach fully leverages the dictionary-based matching graph instead of a simple masked manner. We have conducted numerous experiments on five typical Bio-NER datasets. The proposed model shows significant improvements in F1 score compared to the state-of-the-art (SOTA) models: 2.8% on BC2GM, 1.3% on BC4CHEMD, 1.1% on BC5CDR, 1.6% on NCBI-disease, and 0.5% on JNLPBA. The results show that our model, which is superior to other models, can effectively recognize natural biomedical named entities.

The tranquil environment of high-density urban residential areas had an important impact on the quality of life of residents, but low sound pressure level didn’t necessarily lead to a tranquil experience. The purpose of this study was to explore the constituted and affected factors of tranquility in high-density urban residential areas. Nine high-density urban residential areas were selected, and 216 questionnaires of evaluations on tranquility, the sound sources and environmental indicators of residential areas were collected. Principal component analysis, correlation analysis and multiple linear regression were used to analyze the data. The results showed that perception of restorativeness (72.61%) and pleasantness (27.39%) constituted the evaluation of residential tranquility. Natural sound sources of wind, leaves, and birds promoted restorativeness and pleasantness of tranquility, while selling loudspeakers, mechanics, and traffic reduced restorativeness and pleasantness of residents. Meanwhile, many environmental factors, such as public infrastructure, landscape greening, and security affected the tranquility, except public spaces or cleanliness. Moreover, richness of plant configuration was not a factor which affected restorativeness of tranquility evaluation either in this study. This study constructed the evaluation system of residential tranquility, clarified the mechanism of sound source and environmental factors, and provided theoretical basis and practical guidance for soundscape optimization and environmental design of high-density urban residential areas. It is suggested to integrate natural soundscape, add noise reduction facilities, optimize greening configuration and improve environmental quality in residential area planning, so as to enhance residents’ restorativeness and pleasantness, and promote sustainable development of community.

Telomeres are crucial in the maintenance of chromosome integrity and genomic stability. A series of epidemiological studies have examined the association between telomere length and the risk of cancers, but the findings remain conflicting. We performed literature review and meta-analysis to demonstrate the relationship between telomere length and cancer risk. A total of 23,379 cases and 68,792 controls from 51 publications with 62 population studies were included in this meta-analysis to assess the association between overall cancer or cancer-specific risk and telomere length. General association and dose-response relationship were evaluated based on two and three groups, respectively. The estimates of association were evaluated with odds ratios and 95% confidence intervals by the random-effects or fixed-effects model based on heterogeneity test. We observed a non-significant association between short telomeres and overall risk of cancer. Convincing evidence was observed for the association of short telomeres with an increased risk of gastrointestinal tumor and head and neck cancer. Significant dose-response associations were also observed for gastrointestinal tumor and head and neck cancer. Our findings indicate that telomeres may play diverse roles in different cancers and short telomeres may be risk factors for the tumors of digestive system.