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Background. Esophageal cancer is one of the leading causes of cancer-related death worldwide. Despite the significant progress in the overall treatment of esophageal cancer in recent years, the prognosis for patients who require surgery remains poor. Methods. The present study investigated the clinicopathological features of 503 patients who underwent radical esophagectomy at Huashan Hospital of Fudan University between January 2005 and January 2015. Nomograms that predicted the esophageal squamous cell carcinoma (ESCC) survival rates were established using the Cox proportional hazard regression model. Discrimination and calibration, which were calculated after bootstrapping, were used as a measure of accuracy. Results. Multivariate analyses were used to select five independent prognostic variables and build the nomogram. These variables were pathological T stage, pathological N factor, rate of positive LNs, history of chronic obstructive pulmonary disease (COPD) and postoperative sepsis. The nomogram was built to predict the rates for overall survival (OS) and disease-free survival (DFS). The concordance index for the nomogram prediction for OS and DFS was 0.720 and 0.707, respectively. Compared to the conventional TNM staging system, the nomogram had better predictive accuracy for survival (OS 0.720 vs. 0.672, P

The presence of anti-citrullinated protein antibodies (ACPAs) in the serum is one of the immunological features of rheumatoid arthritis (RA). Anti-cyclic citrullinated peptide (CCP) assay has been widely used in clinic for the diagnosis of RA. However, up to 40% of RA patients are anti-CCP negative and the diagnostic sensitivity in this population needs to be improved for better clinical management. In this study, peptides with Multiple Citrulline Similar Motif (MCSM) were synthesized and a new ELISA system, which we called RA_CP, was developed to detect citrullinated antigens with MCSM present in the serum. 106 RA,48 other arthritis patients and 41 sex- and age-matched healthy controls (HCs) were included in this study. Patients with RA have a significantly higher amount of citrullinated antigens with MCSM than other arthritis patients and HCs. RA patients with positive anti-CCP are also MCSM positive, whereas 75% anti-CCP negative patients are positive for MCSM. The diagnostic sensitivity for anti-CCP and MCSM was 81.1% and 95.3%, while the specificity was 100% and 94.4%, respectively. ROC curve analyses showed that the area under the curve (AUC) values were 0.906 (95% CI: 0.860-0.951) for anti-CCP and 0.948 (95% CI: 0.912-0.985) for MCSM while the combination of MCSM and anti-CCP test has the highest AUC (0.971, 95% CI: 0.946–0.996). Our results suggest that detection of citrullinated antigens with MCSM has improved sensitivity compared with anti-CCP assay and could serve as a biomarker in diagnosis of RA patients.

SARS-CoV-2 is the cause of the current global pandemic of COVID-19; this virus infects multiple organs, such as the lungs and gastrointestinal tract. The microbiome in these organs, including the bacteriome and virome, responds to infection and might also influence disease progression and treatment outcome. In a cohort of 13 COVID-19 patients in Beijing, China, we observed that the gut virome and bacteriome in the COVID-19 patients were notably different from those of five healthy controls. We identified a bacterial dysbiosis signature by observing reduced diversity and viral shifts in patients, and among the patients, the bacterial/viral compositions were different between patients of different severities, although these differences are not entirely distinguishable from the effect of antibiotics. Severe cases of COVID-19 exhibited a greater abundance of opportunistic pathogens but were depleted for butyrate-producing groups of bacteria compared with mild to moderate cases. We replicated our findings in a mouse COVID-19 model, confirmed virome differences and bacteriome dysbiosis due to SARS-CoV-2 infection, and observed that immune/infection-related genes were differentially expressed in gut epithelial cells during infection, possibly explaining the virome and bacteriome dynamics. Our results suggest that the components of the microbiome, including the bacteriome and virome, are affected by SARS-CoV-2 infections, while their compositional signatures could reflect or even contribute to disease severity and recovery processes.

Chiral cholesteric molecular tweezer 7d was synthesized and its influences on changes in the ultraviolet (UV) and fluorescence spectra of various anions were investigated. The results displayed that molecular tweezer 7d selectively recognized F− ions in dimethyl sulfoxide with a detection limit of 5.14 μmol/L, while other anions had little interference. On this basis, a method for the rapid detection of F− ions by host molecular tweezer 7d was established, and the naked-eye detection of F− was realized through the unique yellow color of the complex solution. According to the determination of F− ions in real food samples, it was proved that the established method had good application prospects in F− ion detection.

(1) Background: Patients with acute myocardial infarction (AMI) still experience many major adverse cardiovascular events (MACEs), including myocardial infarction, heart failure, kidney failure, coronary events, cerebrovascular events, and death. This retrospective study aims to assess the prognostic value of machine learning (ML) for the prediction of MACEs. (2) Methods: Five-hundred patients diagnosed with AMI and who had undergone successful percutaneous coronary intervention were included in the study. Logistic regression (LR) analysis was used to assess the relevance of MACEs and 24 selected clinical variables. Six ML models were developed with five-fold cross-validation in the training dataset and their ability to predict MACEs was compared to LR with the testing dataset. (3) Results: The MACE rate was calculated as 30.6% after a mean follow-up of 1.42 years. Killip classification (Killip IV vs. I class, odds ratio 4.386, 95% confidence interval 1.943–9.904), drug compliance (irregular vs. regular compliance, 3.06, 1.721–5.438), age (per year, 1.025, 1.006–1.044), and creatinine (1 µmol/L, 1.007, 1.002–1.012) and cholesterol levels (1 mmol/L, 0.708, 0.556–0.903) were independent predictors of MACEs. In the training dataset, the best performing model was the random forest (RDF) model with an area under the curve of (0.749, 0.644–0.853) and accuracy of (0.734, 0.647–0.820). In the testing dataset, the RDF showed the most significant survival difference (log-rank p = 0.017) in distinguishing patients with and without MACEs. (4) Conclusions: The RDF model has been identified as superior to other models for MACE prediction in this study. ML methods can be promising for improving optimal predictor selection and clinical outcomes in patients with AMI.

Trapiche-like quartz, which is found in Huanggangliang area, Chifeng City, Inner Mongolia, China, has a short columnar euhedral shape. Arms of trapiche-like phenomena are formed by six radial dark bands located along the a-axis of crystals, and their cores are formed by color zones. Various methods were used to investigate the conventional gemological characteristics, trapiche pattern features, chemical compositions, and spectral characteristics of the trapiche-like quartz. CL images and EPMA results reveal they were formed at high temperature conditions and originated from pegmatite. The hexagonal darker zones with high FeO and very little TiO2 contents indicate the trapiche-like patterns are due to spatial distribution of color-inducing elements. According to the position and interpenetration relationship between inclusions, fibrous and spherical inclusions are identified as protogenetic inclusions, which were respectively identified to be ferro-actinolite and iron oxide by EPMA and Raman spectra.

Morphine is one of the most severely abused drugs in the world. Previous research on morphine addiction has focused on the central nervous system (CNS). Studies have shown that a two-way regulation of the brain and gut microbiota (GM), suggesting a link between GM and CNS disease. However, the functional mechanism underlying the relationship between intestinal flora and morphine dependence is unclear. In this study, the effect of sinomenine on morphine addiction was evaluated based on the microbiota-gut-brain axis (MGBA). The results show that the GM plays an important role in morphine dependence. Morphine treatment induced zebrafish conditional position preference (CPP), and significantly changed zebrafish GM characteristics and the expression of MGBA-related genes in the zebrafish brain and intestine. Importantly, sinomenine, an alkaloid with a similar structure to morphine, can reverse these morphine-induced changes. Subsequently, morphine-dependent CPP training was performed after antibiotic administration. After antibiotic treatment, zebrafish CPP behavior, the composition and proportions of the zebrafish GM, and the expression of MGBA-related genes in zebrafish were changed. More interestingly, sinomenine was no longer effective in treating morphine dependence, indicating that antibiotic-driven intestinal flora imbalance alters the efficacy of sinomenine on morphine-dependent zebrafish. This study confirms that the MGBA is bidirectionally regulated, highlighting the key role of the GM in the formation and treatment of morphine dependence, and may provide new treatment strategies for using traditional Chinese medicine to treat drug addiction.

Background: Mild cognitive impairment (MCI) is common among elderly people. So far, effective treatment that can stabilize or reverse the cognitive decline associated with MCI is lacking. Recent studies suggest that playing mahjong may improve attention and memory in elderly people. However, its effect on executive function remains unknown.Methods: 56 elderly people (74.3 ± 4.3 years of age) with MCI from the First Social Welfare the First Nursing Home of Nanchong were randomized into mahjong and control groups (N = 28, each group). Subjects in the mahjong group played mahjong three times a week for 12 weeks, while people in the control group assumed normal daily activity. Executive function was evaluated using the Montreal Cognitive Assessment—Beijing (MoCA-B), the Shape Trail Test (STT), and the Functional Activities Questionnaire (FAQ) before the study and then at 6 and 12 weeks after mahjong administration.Results: There were no baseline differences in MoCA-B, STT, and FAQ scoring between the two groups. The MoCA-B, STT, and FAQ scores, however, improved significantly in the mahjong group but not in the control group after the 12-week mahjong administration. Significant correlations were also found between STT and FAQ scores.Conclusions: Playing Mahjong for 12 weeks improved the executive function of elderly people with MCI. Because Mahjong is a simple, low-cost entertainment activity, it could be widely applied to slow down or reverse the progression of cognitive decline in people with MCI, including those with traumatic brain injury.

Aproper choice of neutrophil-macrophage progenitor cell fate is essential for the generation of adequate myeloid subpopulations during embryonic development and in adulthood. The network governing neutrophil-macrophage progenitor cell fate has several key determinants, such as myeloid master regulators CCAAT enhancer binding protein alpha (C/EBPα) and spleen focus forming virus proviral integration oncogene (PU.1). Nevertheless, more regulators remain to be identified and characterized. To ensure balanced commitment of neutrophil-macrophage progenitors toward each lineage, the interplay among these determinants is not only synergistic, but also antagonistic. Depletion of interferon regulatory factor 2 binding protein 2b (Irf2bp2b), a well-known negative transcription regulator, results in a bias in neutrophil-macrophage progenitor cell fate in favor of macrophages at the expense of neutrophils during the stage of definitive myelopoiesis in zebrafish embryos. Mechanistic studies indicate that Irf2bp2b acts as a downstream target of C/EBPα, repressing PU.1 expression, and that SUMOylation confers the repressive function of Irf2bp2b. Thus, Irf2bp2b is a novel determinant in the choice of fate of neutrophil-macrophage progenitor cells.

BackgroundSince December 2019, coronavirus disease 2019 (COVID-19) emerged in Wuhan and spread across the globe. The objective of this study is to build and validate a practical nomogram for estimating the risk of severe COVID-19.MethodsA cohort of 366 patients with laboratory-confirmed COVID-19 was used to develop a prediction model using data collected from 47 locations in Sichuan province from January 2020 to February 2020. The primary outcome was the development of severe COVID-19 during hospitalization. The least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data size and select relevant features. Multivariable logistic regression analysis was applied to build a prediction model incorporating the selected features. The performance of the nomogram regarding the C-index, calibration, discrimination, and clinical usefulness was assessed. Internal validation was assessed by bootstrapping.ResultsThe median age of the cohort was 43 years. Severe patients were older than mild patients by a median of 6 years. Fever, cough, and dyspnea were more common in severe patients. The individualized prediction nomogram included seven predictors: body temperature at admission, cough, dyspnea, hypertension, cardiovascular disease, chronic liver disease, and chronic kidney disease. The model had good discrimination with an area under the curve of 0.862, C-index of 0.863 (95% confidence interval, 0.801-0.925), and good calibration. A high C-index value of 0.839 was reached in the interval validation. Decision curve analysis showed that the prediction nomogram was clinically useful.ConclusionWe established an early warning model incorporating clinical characteristics that could be quickly obtained on admission. This model can be used to help predict severe COVID-19 and identify patients at risk of developing severe disease.

Abstract Generation of hematopoietic stem/progenitor cells (HSPCs) via cell expansion or cell reprogramming has been widely achieved by overexpression of transcription factors. Herein, it is reported that without introducing exogenous genes, mouse fibroblasts can be reprogrammed into hemogenic cells based on lineage tracing analysis, which further develop into hematopoietic cells, by treatment of cocktails of chemical compounds. The chemical cocktails also reprogram differentiated hematopoietic cells back into HSPC‐like cells. Most importantly, the chemical cocktails enabling hematopoietic reprogramming robustly promote HSPC proliferation ex vivo. The expanded HSPCs acquire enhanced capacity of hematopoietic reconstruction in vivo. Single‐cell sequencing analysis verifies the expansion of HSPCs and the cell reprogramming toward potential generation of HSPCs at the same time by the chemical cocktail treatment. Thus, the proof‐of‐concept findings not only demonstrate that hematopoietic reprogramming can be achieved by chemical compounds but also provide a promising strategy for acquisition of HSPCs by chemical cocktail‐enabled double effects.

Promyelocytic leukemia protein (PML) is a scaffolding protein that organizes PML nuclear bodies. Here the authors present the tetrameric crystal structure of the PML RING domain and show that RING tetramerization is functionally important for nuclear body formation and PML sumoylation.

[Background]: In recent years, aging has become a global social problem. Intelligent health management technology (IHMT) provides solutions for the elderly to deal with various health risks. However, the elderly are facing many difficulties in using IHMT. Studying the application types of IHMT and the influencing factors of the elderly’s acceptance of it will help to improve the use behavior of the elderly. [Methods]: This paper summarizes the application types of IHMT, identifies the influencing factors of the elderly’s adaption of IHMT, and makes a systematic comment on the influencing factors. [Results]: We divide the different functions of IHMT for the elderly into four types: self-monitoring, medical care, remote monitoring, and health education. The influencing factors are divided into three types: individual, social, and technology. [Conclusions]: This study finds that IHMT’s application covers all aspects of the health services of the elderly. Among these applications, self-monitoring is the most used. We divided the influencing factors of the elderly’s acceptance of IHMT into three categories and nine subcategories, having 25 variables.

Chest X-rays (CXR) and computed tomography (CT) are the main medical imaging modalities used against the increased worldwide spread of the 2019 coronavirus disease (COVID-19) epidemic. Machine learning (ML) and artificial intelligence (AI) technology, based on medical imaging fully extracting and utilizing the hidden information in massive medical imaging data, have been used in COVID-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction. This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance in terms of application direction, image collection, and algorithm improvement, from the perspective of radiologists. The limitations and challenges faced by these systems and technologies, such as generalization and robustness, are discussed to indicate future research directions.

Abstract Aptamers are short non-coding, single-stranded oligonucleotides (RNA or DNA) developed through Systematic Evolution of Ligands by Exponential enrichment (SELEX) in vitro. Similar to antibodies, aptamers can bind to specific targets with high affinity, and are considered promising therapeutic agents as they have several advantages over antibodies, including high specificity, stability, and non-immunogenicity. Furthermore, aptamers can be produced at a low cost and easily modified, and are, therefore, called “chemical antibodies”. In the past years, a variety of aptamers specifically bound to both breast cancer biomarkers and cells had been selected. Besides, taking advantage of nanomaterials, there were a number of aptamer-nanomaterial conjugates been developed and widely investigated for diagnostics and targeted therapy of breast cancer. In this short review, we first present a systematical review of various aptamer selection methods. Then, various aptamer-based diagnostic and therapeutic strategies of breast cancer were provided. Finally, the current problems, challenges, and future perspectives in the field were thoroughly discussed.

Predicting Click-Through Rate (CTR) is crucial in product and content recommendation, as it involves estimating the likelihood of a user engaging with a specific advertisement or content link. This task encompasses understanding the complex cognitive processes behind human interactions with recommended content. Learning varied feature embeddings that reflect different cognitive responses in various circumstances is significantly important. However, traditional methods typically learn fixed feature representations, leading to suboptimal performance. Some recent approaches attempt to address this issue by learning bit-wise weights or augmented embeddings for feature representations, but suffer from uninformative or redundant features in the context. To tackle this problem, inspired by the Global Workspace Theory in conscious processing, which posits that only a specific subset of the product features are pertinent while the rest can be noisy and even detrimental to human-click behaviors, we propose a CTR model that enables Dynamic Embedding Learning with Truncated Conscious Attention for CTR prediction, termed DELTA. DELTA contains two key components:(I) conscious truncation module (CTM), which utilizes curriculum learning to apply adaptive truncation on attention weights to select the most critical feature in the context;(II) explicit embedding optimization (EEO), which applies an auxiliary task during training that directly and independently propagates the gradient from the loss layer to the embedding layer, thereby optimizing the embedding explicitly via linear feature crossing. Extensive experiments on five challenging CTR datasets demonstrate that DELTA achieves new state-of-the-art performance among current CTR methods.

Cancer is still a major disease that threatens human life. Although traditional cancer treatment methods are widely used, they still have many disadvantages. Aptamers, owing to their small size, low toxicity, good specificity, and excellent biocompatibility, have been widely applied in biomedical areas. Therefore, the combination of nanomaterials with aptamers offers a new method for cancer treatment. First, we briefly introduce the situation of cancer treatment and aptamers. Then, we discuss the application of aptamers in breast cancer treatment, lung cancer treatment, and other cancer treatment methods. Finally, perspectives on challenges and future applications of aptamers in cancer therapy are discussed.

Dental fluorosis (DF) is an endemic disease caused by excessive fluoride exposure during childhood. Previous studies mainly focused on the acid resistance of fluorotic enamel and failed to reach a consensus on the topic of the caries susceptibility of DF patients. In this review, we discuss the role of DF classification in assessing this susceptibility and follow the “four factors theory” in weighing the pros and cons of DF classification in terms of host factor (dental enamel and saliva), food factor, bacteria factor, and DF treatment factor. From our analysis, we find that susceptibility is possibly determined by various factors such as the extent of structural and chemical changes in fluorotic enamel, eating habits, fluoride levels in diets and in the oral cavity, changes in quantity and quality of saliva, and/or oral hygiene. Thus, a universal conclusion regarding caries susceptibility might not exist, instead depending on each individual’s situation.

Abstract Background With the development of emergency and intensive medical technologies, the survival rate of traumatic brain injury has greatly increased. More and more patients have been converted from severe coma to alleviated state of consciousness, which can be subsequently classified within the framework of disorders of consciousness (DOC). We investigated the clinical application and characteristics of imaging indicators of diffusion tensor imaging (DTI) for the DOC patients. Methods DTI was performed on a total of 75 cases with a clinical diagnosis of DOC from January 2014 to December 2015 in Beijing Tiantan Hospital and PLA Army General Hospital (including 66 cases of unresponsive wakefulness state (UWS) patients and 9 cases of minimally conscious state (MCS) patients). The data for the imaging indicators, such as fractional anisotropy (FA) and mean diffusivity (MD), were separately collected from three relevant regions of interest (ROIs): brainstem, thalamus, and subcortex. The indicators of two groups with different conscious states were statistically analyzed, and correlation analyses were conducted for the mean values of FA and MD in the ROIs evaluated through clinical Coma Recovery Scale-Revised (CRS-R) scores. Results The FA value of the UWS group was evidentially lower than that of the MCS group (P

Abstract Background DNMT3A mutations are frequently discovered in acute myeloid leukemia (AML), associated with poor outcome. Recently, a relapse case report of AML extramedullary disease has showed that AML cells harboring DNMT3A variation were detected in the cerebral spinal fluid. However, whether a causal relationship exists between DNMT3A mutation (D3Amut) and extramedullary infiltration (EMI) is unclear. Methods We took advantage of DNMT3A (R882C) mutation-carrying AML cell strain, that is, OCI-AML3, assessing its migration ability in vitro and in vivo. By RNA interfering technology and a xenograft mouse model, we evaluated the effect of DNMT3A mutation on cell mobility and explored the possible mechanism. Results OCI-AML3 displayed extraordinary migration ability in vitro and infiltrated into meninges of NOD/SCID mice after intravenous transfusion. We found that this leukemic migration or infiltration capacity was significantly compromised by the knockdown of DNMT3A mutant. Notably, TWIST1, a critical inducer of epithelial–mesenchymal transition, which underlies the metastasis of carcinomas, was highly expressed in association with R882 mutations. Abrogation of TWIST1 in DNMT3A mutated cells considerably weakened their mobility or infiltration. Conclusions Our results demonstrate that D3Amut in OCI-AML3 strain enhances leukemic aggressiveness by promoting EMI process, which is partially through upregulating TWIST1.

Lung cancer is the world’s highest morbidity and mortality of malignant tumors, with lung adenocarcinoma (LUAD) as a major subtype. The competitive endogenous RNA (ceRNA) regulative network provides opportunities to understand the relationships among different molecules, as well as the regulative mechanisms among them in order to investigate the whole transcriptome landscape in cancer pathology. We designed this work to explore the role of a key oncogene, MYC, in the pathogenesis of LUAD, and this study aims to identify important long noncoding RNA (lncRNA)-microRNA (miRNA)- transcription factor (TF) interactions in non-small cell lung cancer (NSCLC) using a bioinformatics analysis. The Cancer Genome Atlas (TCGA) database, containing mRNA expression data of NSCLC, was used to determine the deferentially expressed genes (DEGs), and the ceRNA network was composed of WT1-AS, miR-206, and nicotinamide phosphoribosyltransferase (NAMPT) bashing on the MYC expression level. The Kaplan–Meier univariate survival analysis showed that these components may be closely related prognostic biomarkers and will become new ideas for NSCLC treatment. Moreover, the high expression of WT1-AS and NAMPT and low expression of miR-206 were associated with a shortened survival in NSCLC patients, which provided a survival advantage. In summary, the current study constructing a ceRNA-based WT1-AS/miR-206/NAMPT axis might be a novel important prognostic factor associated with the diagnosis and prognosis of LUAD.

In this study, three kinds of CeO2 were synthesized, and supported PdOx (x = 0,1) catalysts were prepared for benzene catalytic combustion. The samples were characterized by XRD, N2 adsorption/desorption, HRTEM, XPS and H2-TPR. The results show that three kinds of CeO2 with different structures can be formed by different preparation methods. This is mainly reflected in the differences in pore structure, particle size and crystal plane. CeO2-DC obtained from directly calcined Ce(NO3)3·6H2O had the largest pore volume and pore diameter and smallest particle size. CeO2-DC was mainly exposed to the (200) plane. Combined with the results of the ability test, it could be concluded that when Pd2+ and Pd0 exist at the same time, the activity increases with an increase in the proportion of Pd2+. Meanwhile, the structure of CeO2 affects the formation of oxygen vacancies, thereby affecting the adsorption and degradation of benzene. This article reveals that the particle size, crystal planes, oxygen vacancies and proportion of Pd2+ have a great impact on the catalytic combustion of benzene and allow a more comprehensive understanding of the structure–activity relationship, which can guide us to design high-efficiency catalysts targeted to obtain suitable CeO2-based catalysts for the catalytic combustion of benzene.