The Influence of Post-Treatment on Micropore Evolution and Mechanical Performance in AlSi10Mg Alloy Manufactured by Laser Powder Bed Fusion.

Gas-induced porosity is almost inevitable in additively manufactured aluminum alloys due to the evaporation of low-melting point elements (e.g., Al, Mg, and Zn) and the encapsulation of gases (e.g., hydrogen) during the multiple-phase reaction in the melt pool. These micropores are highly unstable during post-heat treatment at elevated temperatures and greatly affect mechanical properties and service reliability. In this study, the AlSi10Mg samples prepared by LPBF were subjected to solution heat treatment at 560 °C for 0.5 and 2 h, followed by artificial aging at 160 °C, 180 °C and 200 °C, respectively. The defect tolerance of gas porosity and associated damage mechanisms in the as-built and heat treated AlSi10Mg alloy were elucidated using optical, scanning electron microscopic analysis, X-ray micro computed tomography (XCT) and room temperature tensile testing. The results showed the defect tolerance of AlSi10Mg alloy prepared by LPBF was significantly reduced by the artificial aging treatment due to the precipitation of Mg-Si phases. Fracture analysis showed that the cooperation of fine precipitates and coarsened micropores assists nucleation and propagation of microcracks sites due to stress concentration upon tensile deformation and reduces the tensile elongation at break.

Synergistic powering of DNA walker movement by endogenous dual enzymes for constructing dual-mode biosensors.

To achieve highly sensitive and reliable detection of apurinic/apyrimidinic endonuclease 1 (APE1), a critical cancer diagnostic biomarker, we designed a DNA walker-based dual-mode biosensor, utilizing cellular endogenous dual enzymes (APE 1 and Flap endonuclease 1 (FEN 1)) to collaborate in activating and propelling DNA walker motion on DNA-functionalized Au nanoparticles. Incorporating both fluorescence and electrochemical detection modes, this system leverages signal amplification from DNA walker movement and cascade amplification through tandem hybridization chain reactions (HCR), achieving highly sensitive detection of APE 1. In the fluorescence mode, continuous DNA walker movement, initiated by APE1 and driven by FEN1, generates a robust signal response within a concentration range of 0.01-500 U mL-1, presenting a good linearity in the concentration range of 0.01-10 U mL-1, with a detection limit of 0.01 U mL-1. In the electrochemical detection module, the cascade upstream DNA walker and downstream HCR dual signal amplification strategy further enhances the sensitivity of APE1 detection, extending the linear range to 0.01-50 U mL-1 and reducing the detection limit to 0.002 U mL-1. Rigorous validation demonstrates the biosensor's specificity and anti-interference capability against multiple enzymes. Moreover, it effectively distinguishes cancer cells from normal cell lysates, exhibiting excellent stability and consistency in the dual-modes. Overall, our findings underscore the efficacy of the developed dual-mode biosensor for detecting APE1 in serum and cell lysates samples, indicating its potential for clinical applications in disease diagnosis.

Pretreatment mortality risk prediction model in patients with polymyositis/dermatomyositis-associated interstitial lung disease.

OBJECTIVES: Risk prediction for patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) is challenging due to heterogeneity in the disease course. We aimed to develop a mortality risk prediction model for PM/DM-ILD. METHODS: This prognostic study analysed patients with PM/DM-ILD admitted to Nanjing Drum Hospital from 2016 to 2021. The primary outcome was mortality within 1 year. We used a least absolute shrinkage and selection operator (LASSO) logistic regression model to identify predictive laboratory indicators. These indicators were used to create a laboratory risk score, and we developed a mortality risk prediction model by incorporating clinical factors. The evaluation of model performance encompassed discrimination, calibration, clinical utility and practical application for risk prediction and prognosis. RESULTS: Overall, 418 patients with PM/DM-ILD were enrolled and randomly divided into development (n=282) and validation (n=136) cohorts. LASSO logistic regression identified four optimal features in the development cohort, forming a laboratory risk score: C reactive protein, lactate dehydrogenase, CD3+CD4+ T cell counts and PO2/FiO2. The final prediction model integrated age, arthralgia, anti-melanoma differentiation-associated gene 5 antibody status, high-resolution CT pattern and the laboratory risk score. The prediction model exhibited robust discrimination (area under the receiver operating characteristic: 0.869, 95% CI 0.811 to 0.910), excellent calibration and valuable clinical utility. Patients were categorised into three risk groups with distinct mortality rates. The internal validation, sensitivity analyses and comparative assessments against previous models further confirmed the robustness of the prediction model. CONCLUSIONS: We developed and validated an evidence-based mortality risk prediction model with simple, readily accessible clinical variables in patients with PM/DM-ILD, which may inform clinical decision-making.

Simulation-Guided Rational Design of DNA Walker-Based Theranostic Platform.

Biomolecule-functionalized nanoparticles represent a type of promising biomaterials in biomedical applications owing to their excellent biocompatibility and versatility. DNA-based reactions on nanoparticles have enabled emerging applications including intelligent biosensors, drug delivery, and biomimetic devices. Among the reactions, strand hybridization is the critical step to control the sensitivity and specificity of biosensing, and the efficiency of drug delivery. However, a comprehensive understanding of DNA hybridization on nanoparticles is still lacking, which may differ from the process in homogeneous solutions. To address this limitation, coarse-grained model-based molecular dynamic simulation is harnessed to disclose the critical factors involved in intermolecular hybridization. Based on simulation guidance, DNA walker-based smart theranostic platform (DWTP) based on "on-particle" hybridization is developed, showing excellent consistency with simulation. DWTP is successfully applied for highly sensitive miRNA 21 detection and tumor-specific miRNA 21 imaging, driven by tumor-endogenous APE 1 enzyme. It enables the precise release of antisense oligonucleotide triggered by tumor-endogenous dual-switch miRNA 21 and APE 1, facilitating effective gene silencing therapy with high biosafety. The simulation of "on-particle" DNA hybridization has improved the corresponding biosensing performance and the release efficiency of therapeutic agents, representing a conceptually new approach for DNA-based device design.

Development of a regenerable dual-trigger tripedal DNA walker electrochemical biosensor for sensitive detection of microRNA-155.

Since microRNAs (miRNAs) are valuable biomarkers for disease diagnosis and prognosis, the pursuit of enhanced detection sensitivity through signal amplification strategies has emerged as a prominent focus in low-abundance miRNA detection research. DNA walkers, as dynamic DNA nanodevice, have gained significant attention for their applications as signal amplification strategies. To overcome the limitations of unipedal DNA walkers with a restricted signal amplification efficiency, there is a great need for multi-pedal DNA walkers that offer improved walking and signal amplification capabilities. Here, we employed a combination of catalytic hairpin assembly (CHA) and APE1 enzymatic cleavage reactions to construct a tripedal DNA walker, driving its movement to establish a cascade signal amplification system for the electrochemical detection of miRNA-155. The biosensor utilizes tumor cell-endogenous microRNA-155 and APE1 as dual-trigger for DNA walker formation and walking movement, leading to highly efficient and controllable signal amplification. The biosensor exhibited high sensitivity, with a low detection limit of 10 pM for microRNA-155, and successfully differentiated and selectively detected microRNA-155 from other interfering RNAs. Successful detection in 20 % serum samples indicates its potential clinical application. In addition, we harnessed strand displacement reactions to create a gentle yet efficient electrode regeneration strategy, to addresses the time-consuming challenges during electrode modification processes. We have successfully demonstrated the stability of current signals even after multiple cycles of electrode regeneration. This study showcased the high-efficiency amplification potential of multi-pedal DNA walkers and the effectiveness and versatility of strand displacement in biosensing applications. It opens a promising path for developing regenerable electrochemical biosensors. This regenerable strategy for electrochemical biosensors is both label-free and cost-effective, and holds promise for detecting various disease-related RNA targets beyond its current application.

A cascade signal-amplified fluorescent biosensor combining APE1 enzyme cleavage-assisted target cycling with rolling circle amplification.

A cascade signal-amplified fluorescent biosensor was developed for miRNA-21 detection by combining APE1 enzyme-assisted target recycling and rolling circle amplification strategy. A key feature of this biosensor is its dual-trigger mechanism, utilizing both tumor-endogenous miRNA-21 and the APE1 enzyme in the initial amplification step, followed by a second rolling circle amplification reaction. This dual signal amplification cascade significantly enhanced sensitivity, achieving a detection limit of 3.33 pM. Furthermore, this biosensor exhibited excellent specificity and resistance to interference, allowing it to effectively distinguish and detect the target miRNA-21 in the presence of multiple interfering miRNAs. Moreover, the biosensor maintained its robust detection capabilities in a 10% serum environment, demonstrating its potential for clinical disease diagnosis applications.

Graph-Based Multicentroid Nonnegative Matrix Factorization.

Nonnegative matrix factorization (NMF) is a widely recognized approach for data representation. When it comes to clustering, NMF fails to handle data points located in complex geometries, as each sample cluster is represented by a centroid. In this article, a novel multicentroid-based clustering method called graph-based multicentroid NMF (MCNMF) is proposed. Because the method constructs the neighborhood connection graph between data points and centroids, each data point is represented by adjacent centroids, which preserves the local geometric structure. Second, because the method constructs an undirected connected graph with centroids as nodes, in which the centroids are divided into different centroid clusters, a novel data clustering method based on MCNMF is proposed. In addition, the membership index matrix is reconstructed based on the obtained centroid clusters, which solves the problem of membership identification of the final sample. Extensive experiments conducted on synthetic datasets and real benchmark datasets illustrate the effectiveness of the proposed MCNMF method. Compared with single-centroid-based methods, the MCNMF can obtain the best experimental results.

HDAC3 aberration-incurred GPX4 suppression drives renal ferroptosis and AKI-CKD progression.

Acute kidney injury (AKI) progression to chronic kidney disease (CKD) represents a unique renal disease setting characterized by early renal cellular injury and regulated cell death, and later renal fibrosis, of which the critical role and nature of ferroptosis are only partially understood. Here, we report that renal tubular epithelial ferroptosis caused by HDAC3 (histone deacetylase 3) aberration and the resultant GPX4 suppression drives AKI-CKD progression. In mouse models of AKI-CKD transition induced by nephrotoxic aristolochic acid (AA) and folic acid (FA), renal tubular epithelial ferroptosis occurred early that coincided with preferential HDAC3 elevation and marked suppression of a core anti-ferroptosis enzyme GPX4 (glutathione peroxidase 4). Intriguingly, genetic Hdac3 knockout or administration of a HDAC3-selective inhibitor RGFP966 effectively mitigated the GPX4 suppression, ferroptosis and the fibrosis-associated renal functional loss. In cultured tubular epithelial cells, HDAC3 over-expression or inhibition inversely affected GPX4 abundances. Further analysis revealed that Gpx4 promoter contains a typical binding motif of transcription factor KLF5 (Kruppel-like factor 5). HDAC3 and KLF5 inducibly associated and bound to Gpx4 promoter upon AA treatment, leading to local histone hypoacetylation and GPX4 transactivation inhibition, which was blocked by RGFP966 and a KLF5 inhibitor ML264, respectively, suggesting that KLF5 co-regulated the HDAC3-incurred Gpx4 transcription inhibition. More importantly, in AKI-CKD mice receiving a GPX4 inactivator RSL3, the anti-ferroptosis and renoprotective effects of RGFP966 were largely abrogated, indicating that GPX4 is an essential downstream mediator of the HDAC3 aberration and renal ferroptosis during AKI-CKD transition. Together, our study identified a critical epigenetic pathway of ferroptosis during AKI-CKD transition and suggested that the strategies preserving GPX4 by HDAC3 inhibition are potentially effective to reduce renal ferroptosis and slow AKI-CKD progression.

Federated Data Quality Assessment Approach: Robust Learning With Mixed Label Noise.

Federated learning (FL) has been an effective way to train a machine learning model distributedly, holding local data without exchanging them. However, due to the inaccessibility of local data, FL with label noise would be more challenging. Most existing methods assume only open-set or closed-set noise and correspondingly propose filtering or correction solutions, ignoring that label noise can be mixed in real-world scenarios. In this article, we propose a novel FL method to discriminate the type of noise and make the FL mixed noise-robust, named FedMIN. FedMIN employs a composite framework that captures local-global differences in multiparticipant distributions to model generalized noise patterns. By determining adaptive thresholds for identifying mixed label noise in each client and assigning appropriate weights during model aggregation, FedMIN enhances the performance of the global model. Furthermore, FedMIN incorporates a loss alignment mechanism using local and global Gaussian mixture models (GMMs) to mitigate the risk of revealing samplewise loss. Extensive experiments are conducted on several public datasets, which include the simulated FL testbeds, i.e., CIFAR-10, CIFAR-100, and SVHN, and the real-world ones, i.e., Camelyon17 and multiorgan nuclei challenge (MoNuSAC). Compared to FL benchmarks, FedMIN improves model accuracy by up to 9.9% due to its superior noise estimation capabilities.

Iterative Self-Training Based Domain Adaptation for Cross-User sEMG Gesture Recognition.

Surface electromyography (sEMG) based gesture recognition has received broad attention and application in rehabilitation areas for its direct and fine-grained sensing ability. sEMG signals exhibit strong user dependence properties among users with different physiology, causing the inapplicability of the recognition model on new users. Domain adaptation is the most representative method to reduce the user gap with feature decoupling to acquire motion-related features. However, the existing domain adaptation method shows awful decoupling results when handling complex time-series physiological signals. Therefore, this paper proposes an Iterative Self-Training based Domain Adaptation method (STDA) to supervise the feature decoupling process with the pseudo-label generated by self-training and to explore cross-user sEMG gesture recognition. STDA mainly consists of two parts, discrepancy-based domain adaptation (DDA) and pseudo-label iterative update (PIU). DDA aligns existing users' data and new users' unlabeled data with a Gaussian kernel-based distance constraint. PIU Iteratively continuously updates pseudo-labels to generate more accurate labelled data on new users with category balance. Detailed experiments are performed on publicly available benchmark datasets, including the NinaPro dataset (DB-1 and DB-5) and the CapgMyo dataset (DB-a, DB-b, and DB-c). Experimental results show that the proposed method achieves significant performance improvement compared with existing sEMG gesture recognition and domain adaption methods.

Synthesis and Properties of Polyamide 6 Random Copolymers Containing an Aromatic Imide Structure.

In order to adjust the properties of polyamide 6 (PA6) and expand its application, a new strategy of introducing an aromatic imide structure into the PA6 chain through the random copolymerization method is reported. The diimide diacid monomer was first synthesized by the dehydration and cyclization of pyromellitic dianhydride and 6-aminocaproic acid before it reacted with 1,6-hexamethylene diamine to form poly(amide imide) (PAI) salt, and finally synthesized PA6/PAI random copolymers containing an aromatic imide structure by the random copolymerization of ε-caprolactam and PAI salt. The introduction of an aromatic imide structural unit into the PA6 chain could have a great influence on its properties. As the content of PAI increases, the crystallinity (Xc) and melting temperature (Tm) of the PA6/PAI random copolymer gradually decrease, but its glass transition temperature (Tg) increases obviously. When the PAI content is 20 wt%, the copolymer PA6/PAI-20 has the best comprehensive performance and not only has high thermal stabilities but also excellent mechanical properties (high strength, high modulus, and good toughness) and dielectric properties (low dielectric constant and dielectric loss). Moreover, these properties are significantly superior to those of PA6. Such high-performance PA6 random copolymers can provide great promise for the wider applications of PA6 materials.

Correction: Metabolomics study reveals the alteration of fatty acid oxidation in the hearts of diabetic mice by empagliflozin.

Correction for 'Metabolomics study reveals the alteration of fatty acid oxidation in the hearts of diabetic mice by empagliflozin' by Yingwei Zhang et al., Mol. Omics, 2022, 18, 643-651, https://doi.org/10.1039/D2MO00036A.

Recurrence after percutaneous radiofrequency ablation of hepatocellular carcinoma: Analysis of the pattern and risk factors.

Background: Hepatocellular carcinoma (HCC) frequently relapses after minimally invasive treatment. This study aimed to observe the influencing factors of different recurrence patterns after radiofrequency ablation (RFA) for the treatment of recurrence. Methods: The medical records of HCC patients who underwent RFA between January 2010 and January 2019 were retrospectively reviewed. HCC recurrence is classified into three types: local tumour progression (LTP), intrahepatic distant metastasis, and extrahepatic metastasis. Risk factors, overall survival (OS), and disease-free survival (DFS) were assessed for each modality. Among the risk factors are age, gender, liver function tests, blood tests, and tumour size. The OS and DFS curves were measured by the Kaplan-Meier method. Results: 406 patients who had undergone RFA were included in the study. The median survival for OS and DFS were 120 and 43.6 months. During follow-up, 39, 312, and 55 patients developed LTP, intrahepatic distant metastasis, and extrahepatic metastatic recurrence, respectively. The independent risk factors for each type were as follows: WBC > 5.55*109/L was an independent risk factor for local recurrence. Multiple tumours, extrahepatic metastases, and AFP > 200 ng/ml were used for intrahepatic metastases. Age (P = 0.030), recurrence pattern (P < 0.001) and Child-Pugh class B (P = 0.015) were independent predictors of OS. Conclusions: According to our classification, each pattern of recurrence has different risk factors for recurrence, OS, and DFS.

Increased serum levels of sCD40L were associated with rapidly progressive interstitial lung disease in idiopathic inflammatory myopathies.

OBJECTIVES: Whether coagulopathy exists in development of idiopathic inflammatory myopathies associated rapidly progressive interstitial lung disease (IIMs-RPILD) is unclear. In this study, we aimed to investigate soluble CD40 ligand and D-dimer levels in RPILD patients. METHODS: Patients with IIMs-ILD were enrolled and classified as RPILD and stable-ILD group. Clinical data, laboratory examinations including coagulation-associated parameters and the myositis antibodies status, chest high-resolution computed tomography (HRCT) findings and treatment regimens were collected and serum levels of sCD40L were detected by ELISA. Univariable and adjusted multivariable cox regression were performed to identify risk factors for 6-month mortality, and further to select predictors for establishing predictive model for RPILD. RESULTS: Eighty patients with IIMs-ILD were enrolled and 34 of them were diagnosed as RPILD while 46 as stable-ILD. Multivariable cox regression showed that albumin<32.4 g/L and sCD40L<1658.55 pg/ml were independent risk factors of short-term mortality in RPILD. A SMAD model consisting of serum sCD40L>1054 pg/ml, anti-MDA5 positivity, albumin<32.4 g/L and D-dimer>0.865 mg/L were generated. The odds for RPILD with SMAD score of 0, 1, 2, 3 and 4 were 0, 26.9%, 66.7%, 91.7% and 100%. The 6-month survival stratified by mild (SMAD score 0), moderate (SMAD score 1 and 2) and severe group (SMAD score 3 and 4) were 100%, 79.5% and 20%, respectively. CONCLUSIONS: We established a predictive model for IIMs-RPILD, which provided a clue that coagulopathy might exist in IIMs-RPILD and could help to better treat patients with RPILD. This model awaits further validations.

An observational study of clinical recurrence in patients with interstitial lung disease related to the antisynthetase syndrome.

OBJECTIVE: To describe the clinical characteristics and risk factors of clinical recurrence in interstitial lung disease related to antisynthetase syndrome (ARS-ILD). METHODS: Patients diagnosed as ARS-ILD in Nanjing Drum Tower Hospital between January 2015 and November 2020 were retrospectively analyzed. Clinical information and treatment course were reviewed. The primary endpoint was the disease recurrence, and the secondary point was mortality. Univariate and multivariable Cox regression analyses were performed to identify risk factors for recurrence. RESULTS: Totally, 132 patients with ARS-ILD received immunomodulation treatment from diagnosis. During follow-ups, sixty-nine patients showed recurrence, with a recurrency rate yielding 52.3%. The median duration from treatment initiation to recurrence was 11 (5-18) months. The median tapering course in the recurrence group was 8 (3-12.5) months, which was significantly shorter than the 16 (10-32) months in the no-recurrence group (p < 0.001). Fifty-eight patients experienced recurrence when the glucocorticoids (GC) dose dropped to 10 (9.375-15) mg/day. Twelve patients discontinued GC with a median treatment course of 11.5 (8-16.75) months, and 11 patients developed recurrence after discontinuing GC for 3 (1-4) months. Twelve patients died, with a mortality rate of 9.1%, and recurrence was not associated with increased mortality. The adjusted multivariate analysis showed that age, increased serum lactate dehydrogenase (LDH) level, relatively shorter tapering duration, and inappropriate GC discontinuation were associated with recurrence. CONCLUSION: Recurrence of ARS-ILD was common during medication intensity reduction. Age, LDH, medication tapering duration, and discontinuation were risk factors for recurrence. Further efforts to reduce recurrence should take into consideration of these factors. Key Points • Recurrence is observed commonly with a recurrency rate 52.3% in patients with interstitial lung disease related to antisynthetase syndrome (ARS-ILD) when glucocorticoids (GC) tapering or discontinuation. • Age, increased serum lactate dehydrogenase (LDH) level, medication tapering duration, and GC discontinuation were identified to be significantly associated with the recurrence of ARS-ILD.

Prediction model for the pretreatment evaluation of mortality risk in anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease.

Background: Anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease (anti-MDA5 DM-ILD) is a disease with high mortality. We sought to develop an effective and convenient prediction tool to estimate mortality risk in patients with anti-MDA5 DM-ILD and inform clinical decision-making early. Methods: This prognostic study included Asian patients with anti-MDA5 DM-ILD hospitalized at the Nanjing Drum Hospital from December 2016 to December 2020. Candidate laboratory indicators were retrospectively collected. Patients hospitalized from 2016 to 2018 were used as the discovery cohort and applied to identify the optimal predictive features using a least absolute shrinkage and selection operator (LASSO) logistic regression model. A risk score was determined based on these features and used to construct the mortality risk prediction model in combination with clinical characteristics. Results were verified in a temporal validation comprising patients treated between 2019 and 2020. The primary outcome was mortality risk within one year. The secondary outcome was overall survival. The prediction model's performance was assessed in terms of discrimination, calibration, and clinical usefulness. Results: This study included 127 patients, (72 men [56.7%]; median age, 54 years [interquartile range, 48-63 years], split into discovery (n = 87, 70%) and temporal validation (n=37, 30%) cohorts. Five optimal features were selected by LASSO logistic regression in the discovery cohort (n = 87) and used to construct a risk score, including lymphocyte counts, CD3+CD4+ T-cell counts, cytokeratin 19 fragment (CYFRA21-1), oxygenation index, and anti-Ro52 antibody. The retained predictive variables in the final prediction model were age, Heliotrope, fever, and risk score, and the most predictive factor was the risk score. The prediction model showed good discrimination (AUC: 0.915, 95% CI: 0.846-0.957), good calibration (Hosmer-Lemeshow test, P = 0.506; Brier score, 0.12), and fair clinical usefulness in the discovery cohort. The results were verified among patients in the temporal validation cohort (n = 38). We successfully divided patients into three risk groups with very different mortality rates according to the predictive score in both the discovery and validation cohorts (Cochran-Armitage test for trend, P < 0.001). Conclusions: We developed and validated a mortality risk prediction tool with good discrimination and calibration for Asian patients with anti-MDA5 DM-ILD. This tool can offer individualized mortality risk estimation and inform clinical decision-making.

Papel Diagnóstico do NT-proBNP em Pacientes com Comprometimento por Amiloidose Cardíaca: Uma Metanálise / Diagnostic Role of NT-proBNP in Patients with Cardiac Amyloidosis Involvement: A Meta-Analysis

Resumo Fundamento A amiloidose é definida como um distúrbio caracterizado pela deposição de material proteico amiloide extracelular nos tecidos. Objetivos O N-terminal pró-peptídeo natriurético tipo-B (NT-proBNP) é usado para prever a amiloidose cardíaca (AC), mas seu efeito diagnóstico no comprometimento por AC ainda não é claro, especialmente em termos de especificidade e sensibilidade. Métodos Foi feita uma busca de literatura nos bancos de dados Pubmed, Embase e a biblioteca Cochrane, e o QUADAS 2 foi utilizado para avaliação da qualidade. O comando Midas no Stata 12.0 foi usado para analisar os indicadores dos sujeitos. O teste Q de Cochran e o I2 foram usados como testes de heterogeneidade, e a heterogeneidade significativa foi definida como p <0,05 e/ou I2 >50%. A análise de correlação de Spearman foi usada para avaliar o efeito de limiar, e o viés da publicação foi avaliado pelo teste de assimetria. A significância estatística foi definida em p <0,05. Resultados Como resultados, 10 conjuntos de dados de 7 estudos foram incluídos para análise, apresentando alta qualidade metodológica e pequenos vieses de confusão. A sensibilidade e a especificidade do NT-proBNP no diagnóstico do comprometimento cardíaco para pacientes com amiloidose foram 0,93 e 0,84, respectivamente. As curvas ROC também sugeriram uma validade diagnóstica alta do NT-proBNP com AUC de 0,95. Um nomograma de Fagan demonstrou que as probabilidades de NT-proBNP positivo e negativo no avanço do comprometimento por AC eram de 90% e 8%, respectivamente. O gráfico de funil de Deek não sugeriu viés significativo de publicação entre os estudos incluídos, e os resultados foram estáveis e confiáveis. Conclusões O NT-proBNP desempenha um papel positivo no diagnóstico precoce do comprometimento por AC, com alta sensibilidade e especificidade.

Abstract Background Amyloidosis is defined as a disorder characterized by the deposition of extracellular protein material of amyloid in tissues. Objectives N-terminal pro-B-type natriuretic peptide (NT-proBNP) is used to predict the cardiac amyloidosis (CA), but its diagnostic effect on CA involvement remains unclear, especially in terms of specificity and sensitivity. Methods A search for literature was conducted in the Pubmed, Embase, and Cochrane library databases, and QUADAS 2 was used for quality assessment. Midas command in Stata 12.0 was used to analyze the subject indicators. Cochran's Q and I2were to test for heterogeneity, and the significant heterogeneity was set at p < 0.05 and/or I2> 50%. Spearman correlation analysis was used to evaluate the threshold effect, and the publication bias was assessed using the asymmetry test. The statistical significance was set at p < 0.05. Results As results, 10 sets of data from 7 studies were included for analysis, showing high methodological quality and minimal confounding bias. The sensitivity and specificity of NT-proBNP in the diagnosis of cardiac involvement for patients with amyloidosis were 0.93 and 0.84, respectively. ROC curves also suggested a high diagnostic validity of NT-proBNP with an AUC of 0.95. A Fagan's nomogram plot showed probabilities for NT-proBNP positive and negative in developing CA involvement were 90% and 8%, respectively. The Deek's funnel plot suggested no significant publication bias across included studies, and the results were stable and reliable. Conclusions NT-proBNP plays the positive role in the early diagnosis of CA involvement with high sensitivity and specificity.

Development and Validation of Nomogram for Predicting Survival of Primary Liver Cancers Using Machine Learning.

Background and Aims: Primary liver cancer (PLC) is a common malignancy with poor survival and requires long-term follow-up. Hence, nomograms need to be established to predict overall survival (OS) and cancer-specific survival (CSS) from different databases for patients with PLC. Methods: Data of PLC patients were downloaded from Surveillance, Epidemiology, and End Results (SEER) and the Cancer Genome Atlas (TCGA) databases. The Kaplan Meier method and log-rank test were used to compare differences in OS and CSS. Independent prognostic factors for patients with PLC were determined by univariate and multivariate Cox regression analyses. Two nomograms were developed based on the result of the multivariable analysis and evaluated by calibration curves and receiver operating characteristic curves. Results: OS and CSS nomograms were based on age, race, TNM stage, primary diagnosis, and pathologic stage. The area under the curve (AUC) was 0.777, 0.769, and 0.772 for 1-, 3- and 5-year OS. The AUC was 0.739, 0.729 and 0.780 for 1-, 3- and 5-year CSS. The performance of the two new models was then evaluated using calibration curves. Conclusions: We systematically reviewed the prognosis of PLC and developed two nomograms. Both nomograms facilitate clinical application and may benefit clinical decision-making.

Design of Uracil-Modified DNA Nanotubes for Targeted Drug Release via DNA-Modifying Enzyme Reactions.

DNA nanostructure-based responsive drug delivery has become an increasingly potent method in cancer therapy. However, a variety of important cancer biomarkers have not been explored in searching of new and efficient targeted delivery systems. Uracil degradation glycosylase and human apurinic/apyrimidinic endonuclease are significantly more active in cancer cells. Here, we developed uracil-modified DNA nanotubes that can deliver drugs to tumor cells through an enzyme-induced disassembly process. Although the reaction of these enzymes on their natural DNA substrates has been established, their reactivity on self-assembled nanostructures of nucleic acids is not well understood. We leveraged molecular dynamic simulation based on coarse-grained model to forecast the enzyme reactivity on different DNA designs. The experimental data are highly consistent with the simulation results. It is the first example of molecule simulation being used to guide the design of enzyme-responsive DNA nano-delivery systems. Importantly, we found that the efficiency of drug release from the nanotubes can be regulated by tuning the positions of uracil modification. The DNA nanotubes equipped with cancer-specific aptamer AS1411 are used to deliver doxorubicin to tumor-bearing mice not only effectively inhibiting tumor growth but also protecting major organs from drug-caused damage. We believe that this work provides new knowledge on and insights into future design of enzyme-responsive DNA-based nanocarriers for drug delivery.

Diagnostic Role of NT-proBNP in Patients with Cardiac Amyloidosis Involvement: A Meta-Analysis. / Papel Diagnóstico do NT-proBNP em Pacientes com Comprometimento por Amiloidose Cardíaca: Uma Metanálise.

BACKGROUND: Amyloidosis is defined as a disorder characterized by the deposition of extracellular protein material of amyloid in tissues. OBJECTIVES: N-terminal pro-B-type natriuretic peptide (NT-proBNP) is used to predict the cardiac amyloidosis (CA), but its diagnostic effect on CA involvement remains unclear, especially in terms of specificity and sensitivity. METHODS: A search for literature was conducted in the Pubmed, Embase, and Cochrane library databases, and QUADAS 2 was used for quality assessment. Midas command in Stata 12.0 was used to analyze the subject indicators. Cochran's Q and I2were to test for heterogeneity, and the significant heterogeneity was set at p < 0.05 and/or I2> 50%. Spearman correlation analysis was used to evaluate the threshold effect, and the publication bias was assessed using the asymmetry test. The statistical significance was set at p < 0.05. RESULTS: As results, 10 sets of data from 7 studies were included for analysis, showing high methodological quality and minimal confounding bias. The sensitivity and specificity of NT-proBNP in the diagnosis of cardiac involvement for patients with amyloidosis were 0.93 and 0.84, respectively. ROC curves also suggested a high diagnostic validity of NT-proBNP with an AUC of 0.95. A Fagan's nomogram plot showed probabilities for NT-proBNP positive and negative in developing CA involvement were 90% and 8%, respectively. The Deek's funnel plot suggested no significant publication bias across included studies, and the results were stable and reliable. CONCLUSIONS: NT-proBNP plays the positive role in the early diagnosis of CA involvement with high sensitivity and specificity.

FUNDAMENTO: A amiloidose é definida como um distúrbio caracterizado pela deposição de material proteico amiloide extracelular nos tecidos. OBJETIVOS: O N-terminal pró-peptídeo natriurético tipo-B (NT-proBNP) é usado para prever a amiloidose cardíaca (AC), mas seu efeito diagnóstico no comprometimento por AC ainda não é claro, especialmente em termos de especificidade e sensibilidade. MÉTODOS: Foi feita uma busca de literatura nos bancos de dados Pubmed, Embase e a biblioteca Cochrane, e o QUADAS 2 foi utilizado para avaliação da qualidade. O comando Midas no Stata 12.0 foi usado para analisar os indicadores dos sujeitos. O teste Q de Cochran e o I2 foram usados como testes de heterogeneidade, e a heterogeneidade significativa foi definida como p <0,05 e/ou I2 >50%. A análise de correlação de Spearman foi usada para avaliar o efeito de limiar, e o viés da publicação foi avaliado pelo teste de assimetria. A significância estatística foi definida em p <0,05. RESULTADOS: Como resultados, 10 conjuntos de dados de 7 estudos foram incluídos para análise, apresentando alta qualidade metodológica e pequenos vieses de confusão. A sensibilidade e a especificidade do NT-proBNP no diagnóstico do comprometimento cardíaco para pacientes com amiloidose foram 0,93 e 0,84, respectivamente. As curvas ROC também sugeriram uma validade diagnóstica alta do NT-proBNP com AUC de 0,95. Um nomograma de Fagan demonstrou que as probabilidades de NT-proBNP positivo e negativo no avanço do comprometimento por AC eram de 90% e 8%, respectivamente. O gráfico de funil de Deek não sugeriu viés significativo de publicação entre os estudos incluídos, e os resultados foram estáveis e confiáveis. CONCLUSÕES: O NT-proBNP desempenha um papel positivo no diagnóstico precoce do comprometimento por AC, com alta sensibilidade e especificidade.