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Background: This study aims to construct a model predicting the probability of RF in AECOPD patients upon hospital admission. Methods: This study retrospectively extracted data from MIMIC-IV database, ultimately including 3776 AECOPD patients. The patients were randomly divided into a training set (n = 2643) and a validation set (n = 1133) in a 7:3 ratio. First, LASSO regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Subsequently, a multifactorial Cox regression analysis was employed to establish a predictive model. Thirdly, the model was validated using ROC curves, Harrell's C-index, calibration plots, DCA, and K-M curve. Result: Eight predictive indicators were selected, including blood urea nitrogen, prothrombin time, white blood cell count, heart rate, the presence of comorbid interstitial lung disease, heart failure, and the use of antibiotics and bronchodilators. The model constructed with these 8 predictors demonstrated good predictive capabilities, with ROC curve areas under the curve (AUC) of 0.858 (0.836–0.881), 0.773 (0.746–0.799), 0.736 (0.701–0.771) within 3, 7, and 14 days in the training set, respectively and the C-index was 0.743 (0.723–0.763). Additionally, calibration plots indicated strong consistency between predicted and observed values. DCA analysis demonstrated favorable clinical utility. The K-M curve indicated the model's good reliability, revealed a significantly higher RF occurrence probability in the high-risk group than that in the low-risk group (P < 0.0001). Conclusion: The nomogram can provide valuable guidance for clinical practitioners to early predict the probability of RF occurrence in AECOPD patients, take relevant measures, prevent RF, and improve patient outcomes. [ABSTRACT FROM AUTHOR]

In the realm of flexible optoelectronic devices, intrinsic flexible fully π‐conjugated polymers (FπCPs) assume a pivotal role owing to their concurrent intrinsic viscoelasticity and robust optoelectronic properties. As flexible devices are destined to encounter diverse stress environments, the selection of functional materials based on mechanical requirements becomes imperative. Here, VPERD assessment system is introduced to scrutinize the mechanical properties of side‐chain plasticizing FπCPs. The acronym VPERD encapsulates five key aspects of mechanical characteristics, namely viscidity (V), plasticity (P), elasticity (E), rigidity (R), and ductility (D). The mechanical characteristics of FπCPs are tuned through the control of flexible chain density (FCD). Enhancing FCD induces superior chain softness, favorable solubility, and heightened viscoplasticity. Through precise regulation of FCD and thoughtful structural design, freestanding FπCPs nano‐films exhibit a remarkable maximum fracture strain of ≈50%. Deep‐blue flexible polymer light‐emitting diodes (PLEDs) reveal that maintaining FCD at ≈50% achieves a balance between mechanical and optoelectronic properties. The stretched films after strain fatigue both show that mild strain is conducive to enhancing the efficiency of FπCPs films and devices. According to VPERD assessment system, the prerequisite for achieving intrinsically flexible FπCPs lies in controlling the degree of side‐chain internal plasticization through the tuning of FCD. [ABSTRACT FROM AUTHOR]

Conjugated polymers with p‐orbital overlap show intramolecular‐conformation‐dependent photophysical and electrical properties. Compared to the non‐planar segments, the planar conformation segments have a relatively long effective conjugated length and rigid backbone structure, which are beneficial for the enhancement of optoelectronic properties. Herein, the effect of film thickness on the formation capacity of planar (β) conformations in polyfluorene (poly[4‐(octyloxy)‐9,9‐diphenylfluorene‐2,7‐diyl]‐co‐[5‐(octyloxy)‐9,9‐diphenylfluorene‐2,7‐diyl], PODPF) for the fabrication of stable deep‐blue polymer light‐emitting diodes (PLEDs) is explored. Thickness‐tunable films with thicknesses ranging from 15 to 270 nm by controlling the concentration of precursor solution are prepared. The main observations are as follows. The PODPF chains in thin films are less likely to adopt the β conformations associated with the loose interchain packing in nano‐aggregates than those in thick films. Red‐shifted and well‐resolved emission spectra are observed for the annealed film with a high thickness, indicating the greater presence of β‐conformation segments. More interestingly, interchain aggregation is a necessary but not sufficient condition for the formation of β conformations. Finally, PLEDs based on β‐conformation segments have outstanding brightness, low turn‐on voltage, and stable deep‐blue electroluminescent behavior, confirming the unique advantage of planar conformation for optoelectronic applications. [ABSTRACT FROM AUTHOR]

Chemodynamic therapy (CDT) generating hydroxyl radicals (•OH) by utilizing metal ions reacting with hydrogen peroxide (H2O2) is a highly encouraging strategy for cancer treatment. However, highly expressed GSH in tumor cells severely limits the efficacy of CDT, and CDT alone is also not sufficient to produce excellent antitumor efficiency. Herein, a dual GSH depletion nanosystem (MnO2@PDA@PEG@DOX) was designed and synthesized to achieve synergistic cancer treatment under ultrasound (US) irritation. To achieve an acidic response, dopamine (DA) was loaded onto manganese dioxide, and the water solubility and stability were greatly improved after PEG modification; finally, the loading of doxorubicin (DOX) achieved the combinational therapy. When the nanoparticles arrived at the tumor site, the acidic and high expression of GSH in the tumor microenvironment prompted the degrading of the nanosystem, followed by the release of MnO2 and DOX. The released MnO2 can react with intracellular GSH to produce Mn2+, which realizes chemodynamic therapy by catalyzing H2O2 to generate highly toxic hydroxyl radicals (•OH) at the tumor site; also, the depletion of GSH will significantly promote the level of •OH, improving the efficiency of CDT simultaneously. Moreover, the release of DOX could be boosted by US irradiation, thus enhancing the effect of chemotherapy on DOX and achieving sonodynamic therapy (SDT). Therefore, strategies to enhance CDT efficiency by dual GSH depletion and combining chemotherapy and sonodynamic therapy modalities can provide more ideas and approaches for combination therapy in cancer treatment. [ABSTRACT FROM AUTHOR]

The effect of colloidal nanoparticles on the phase changes of the amphiphilic AB linear diblock, A1A2B, and A2B heteroarm star copolymers confined between two polymer brush substrates was investigated by using a real-space self-consistent field theory. By changing the concentrations of nanoparticles and polymer brushes, the phase structure of the amphiphilic AB copolymer transforms from lamellar to core-shell hexagonal phase to cylinder phase. The pattern of A2B heteroarm star copolymer changes from core-shell hexagonal phases to lamellar phases and the layer decreases when increasing the density of the polymer brushes. The results showed that the phase behavior of the system is strongly influenced by the polymer brush architecture and the colloidal nanoparticle numbers. The colloidal nanoparticles and the soft confined surface of polymer brushes make amphiphilic AB copolymers easier to form ordered structures. The dispersion of the nanoparticles was also investigated in detail. The soft surfaces of polymer brushes and the conformation of the block copolymers work together to force the nanoparticles to disperse evenly. It will give helpful guidance for making some new functional materials by nano etching technology, nano photoresist, and nanoprinting. [ABSTRACT FROM AUTHOR]

To evaluate the value of nanopore targeted sequencing in diagnosing pneumonia pathogens. This large-scale multicentre prospective study performed in 8 hospitals across China from April to October 2022. Hospitalised patients with a diagnosis of pneumonia at admission were included. Complete clinical data were collected, and bronchoalveolar lavage fluid were obtained from each patient. These samples underwent simultaneous testing using conventional microbial testing, metagenomic next-generation sequencing, and nanopore targeted sequencing. A total of 218 patients were included. Among the 168 cases of pulmonary infection, 246 strains of pathogens were confirmed. Nanopore targeted sequencing outperformed conventional microbial testing, identifying more pathogens with a sensitivity increase of 47.9% (77.2% vs. 29.3%). Metagenomic next-generation sequencing had a sensitivity of 82.9%. Total of 70.1% patients had consistent results in both metagenomic next-generation sequencing and nanopore targeted sequencing. Nanopore targeted sequencing exhibited significantly higher sensitivity in detecting Pneumocystis jiroveci, cytomegalovirus, Mycobacterium tuberculosis, Nontuberculous mycobacteria, Streptococcus pneumoniae, and Mycoplasma pneumoniae compared to conventional microbial testing. However, metagenomic next-generation sequencing demonstrated higher sensitivity than nanopore targeted sequencing for Aspergillus (88.5% vs. 53.8%). Regarding the detection of co-infections, nanopore targeted sequencing displayed significantly higher sensitivity than conventional microbial testing (76.7% vs. 28.7%) and was on par with metagenomic next-generation sequencing (76.7% vs. 82.9%). Nanopore targeted sequencing performs equally well as metagenomic next-generation sequencing in bronchoalveolar lavage fluid for pathogen diagnosis in pneumonia, both methods showing higher sensitivity than conventional microbial testing. Nanopore targeted sequencing can be considered a reliable method for diagnosing pathogens in pneumonia. [ABSTRACT FROM AUTHOR]

With the increasing complexity and frequency of interactions among a large number of heterogeneous nodes within a combat system of systems (SoS), evaluating the capability of the SoS to withstand external attacks and interferences has become an increasingly challenging and urgent issue. However, the complexity of a combat SoS often brings about difficulties in quantitative analysis. This paper proposes a method to assess the resilience of a combat SoS. Firstly, a network model of a combat SoS is constructed, taking into account multi-functional composite nodes. Secondly, the combat capability model of the combat SoS is built based on the capabilities of the kill chains and kill networks. Lastly, an approach is proposed to calculate the combat capability of the system based on the network's two-terminal connectivity. Moreover, based on the SoS's combat capability, the resilience is analyzed from the dimensions of anti-destruction, survival, and recovery. The simulation experiments show that, compared to other methods, the method in this paper for calculating the combat capability of the combat SoS does not depend on the number of kill chains and aligns with the combat processes and actual patterns. Additionally, the resilience measurement method can effectively analyze its capability to cope with external interferences. [ABSTRACT FROM AUTHOR]

Despite a few attempts to automatically crawl Ewe text from online news portals and magazines, the African Ewe language remains underdeveloped despite its rich morphology and complex "unique" structure. This is due to the poor quality, unbalanced, and religious-based nature of the crawled Ewe texts, thus making it challenging to preprocess and perform any NLP task with current transformer-based language models. In this study, we present a well-preprocessed Ewe dataset for low-resource text classification to the research community. Additionally, we have developed an Ewe-based word embedding to leverage the low-resource semantic representation. Finally, we have fine-tuned seven transformer-based models, namely BERT-based (cased and uncased), DistilBERT-based (cased and uncased), RoBERTa, DistilRoBERTa, and DeBERTa, using the preprocessed Ewe dataset that we have proposed. Extensive experiments indicate that the fine-tuned BERT-base-cased model outperforms all baseline models with an accuracy of 0.972, precision of 0.969, recall of 0.970, loss score of 0.021, and an F1-score of 0.970. This performance demonstrates the model's ability to comprehend the low-resourced Ewe semantic representation compared to all other models, thus setting the fine-tuned BERT-based model as the benchmark for the proposed Ewe dataset. [ABSTRACT FROM AUTHOR]

This study investigated the inhibitory effects of lncRNA HLA Complex Group 11 (HCG11) on non-small cell lung cancer (NSCLC) and the molecular mechanisms. Bioinformatics analysis was conducted to determine the downstream targeted gene miR-17-5p/p21 and predict their binding sites. qRT-PCR and Western blot were used to detect expression levels, and dual luciferase and RIP assays were adopted to verify binding relationship. The lncRNA HCG11/miR-17-5p/p21 axis was found to regulate drug resistance, proliferation, apoptosis, and cell cycle of A549 and A549-Gemcitabine (GEM) cells. HCG11 acted as a ceRNA binding to miR-17-5p, which repressed p21 expression in turn. In vivo experiments demonstrated that HCG11 hindered tumor growth. Therefore, lncRNA HCG11, by targeting the miR-17-5p/p21 axis, suppressed GEM resistance and malignant progression of NSCLC cells. This study provides a reference for investigating the potential value of lncRNA HCG11 in the diagnosis of NSCLC and finding potential targets against clinical chemotherapeutic resistance in NSCLC. [ABSTRACT FROM AUTHOR]

Existing Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods are mostly suitable for simple systems with fewer factors, and lack effective integration of expert knowledge and experience from large-scale group populations, resulting in a potential compromise of the quality of the initial direct relation (IDR) matrix. To make DEMATEL better suited for the identification of critical factors in complex systems, this paper proposes a hierarchical DEMATEL method for large-scale group decision-making. Considering the limitations of expert knowledge and experience, a method based on expert consistency network for constructing the expert weight matrix is designed. The expert consistency network is constructed for different elements, and the weights of experts in different elements are determined using the clustering coefficient. Following the principles of the classic DEMATEL method, the steps for identifying key elements in complex systems using the large-scale group-hierarchical DEMATEL method are summarized. To objectively test the effectiveness and superiority of the decision algorithm, the robustness of the algorithm is analyzed in an interference environment. Finally, the superiority of the proposed method and algorithm is verified through a case study, which demonstrating that the proposed decision-making method is suitable for group decision-making in complex systems, with high algorithm stability and low algorithm deviation. [ABSTRACT FROM AUTHOR]