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Abstract Objective This study aims to assess the performance of various scoring systems in predicting the 28-day mortality of patients with aortic aneurysms (AA) admitted to the intensive care unit (ICU). Methods We utilized data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) to perform a comparative analysis of various predictive systems, including the Glasgow Aneurysm Score (GAS), Simplified Acute Physiology Score (SAPS) III, SAPS II, Logical Organ Dysfunction System (LODS), Sequential Organ Failure Assessment (SOFA), Systemic Inflammatory Response Syndrome (SIRS), and The Oxford Acute Illness Severity Score (OASIS). The discrimination abilities of these systems were compared using the area under the receiver operating characteristic curve (AUROC). Additionally, a 4-knotted restricted cubic spline regression was employed to evaluate the association between the different scoring systems and the risk of 28-day mortality. Finally, we conducted a subgroup analysis focusing on patients with abdominal aortic aneurysms (AAA). Results This study enrolled 586 patients with AA (68.39% male). Among them, 26 patients (4.4%) died within 28 days. Comparative analysis revealed higher SAPS II, SAPS III, SOFA, LODS, OASIS, and SIRS scores in the deceased group, while no statistically significant difference was observed in GAS scores between the survivor and deceased groups (P = 0.148). The SAPS III system exhibited superior predictive value for the 28-day mortality rate (AUROC 0.805) compared to the LODS system (AUROC 0.771), SOFA (AUROC 0.757), SAPS II (AUROC 0.759), OASIS (AUROC 0.742), SIRS (AUROC 0.638), and GAS (AUROC 0.586) systems. The results of the univariate and multivariate logistic analyses showed that SAPS III was statistically significant for both 28-day and 1-year mortality. Subgroup analyses yielded results consistent with the overall findings. No nonlinear relationship was identified between these scoring systems and 28-day all-cause mortality (P for nonlinear > 0.05). Conclusion The SAPS III system demonstrated superior discriminatory ability for both 28-day and 1-year mortality compared to the GAS, SAPS II SIRS, SOFA, and OASIS systems among patients with AA.

Ferroptosis is an emerging form of regulated cell death in an oxidative stress- and iron-dependent manner, primarily induced by the over-production of reactive oxygen species (ROS). Manipulation of ferroptosis has been considered a promising therapeutic approach to inhibit liver tumor growth. Nevertheless, the development of resistance to ferroptosis in liver cancer poses a significant challenge in cancer treatment. Post-translational modifications (PTMs) are crucial enzymatic catalytic reactions that covalently regulate protein conformation, stability and cellular activities. Additionally, PTMs play pivotal roles in various biological processes and divergent programmed cell death, including ferroptosis. Importantly, key PTMs regulators involved in ferroptosis have been identified as potential targets for cancer therapy. PTMs function of two proteins, SLC7A11, GPX4 involved in ferroptosis resistance have been extensively investigated in recent years. This review will summarize the roles of PTMs in ferroptosis-related proteins in hepatocellular carcinoma (HCC) treatment.

Abstract Faithful inheritance of parental histones is essential to maintain epigenetic information and cellular identity during cell division. Parental histones are evenly deposited onto the replicating DNA of sister chromatids in a process dependent on the MCM2 subunit of DNA helicase. However, the impact of aberrant parental histone partition on human disease such as cancer is largely unknown. In this study, we construct a model of impaired histone inheritance by introducing MCM2-2A mutation (defective in parental histone binding) in MCF-7 breast cancer cells. The resulting impaired histone inheritance reprograms the histone modification landscapes of progeny cells, especially the repressive histone mark H3K27me3. Lower H3K27me3 levels derepress the expression of genes associated with development, cell proliferation, and epithelial to mesenchymal transition. These epigenetic changes confer fitness advantages to some newly emerged subclones and consequently promote tumor growth and metastasis after orthotopic implantation. In summary, our results indicate that impaired inheritance of parental histones can drive tumor progression.

Cross-sea cable-stayed bridges encounter challenges associated with cable corrosion and cable-force relaxation during their service life, which significantly affects their structural performance and seismic response. This study focuses on a cross-sea cable-stayed bridge located in Hainan Province. Utilizing an LSTM deep learning model, this study aims to fill in the gaps in short-term cable-monitoring data from the past year using the available cable-force-monitoring data from the same period. The authors of this study interpolated the cable-force data in the absence of sensors and employed a SARIMA machine learning time-series-prediction model to predict the future trends of all cable forces. A finite-element model was constructed, and a dynamic time-history analysis of the seismic response of the cross-sea cable-stayed bridge was conducted, considering the influence of cable-force relaxation and cable corrosion in the future. The findings indicate that the LSTM-SARIMA model predicted an average decrease of 11.81% in the cable force of the cable-stayed bridge after 20 years. During the lifecycle of the cables, cable corrosion exerts a significant impact on the variation in cable stress within the bridge structure during earthquakes, while cable-force relaxation has a more pronounced effect on the vertical displacement of the main beam of the bridge structure during seismic events. Compared to when using the traditional model that only considers cable corrosion, the maximum negative vertical displacement of the main beam increases by 29.7% when using the proposed model if the earthquake intensity is 0.35 g after 20 years, which indicates that the proposed machine learning model can exactly determine the seismic behavior of the lifecycle cross-sea cable-stayed bridge, considering the impacts of both cable-force relaxation and cable corrosion.

Abstract Manufacturing abrasion‐resistant superhydrophobic matters is challenging due to the fragile feature of the introduced micro‐/nanoscale surface roughness. Besides the long‐term durability, large scale at meter level, and 3D complex structures are of great importance for the superhydrophobic objects used across diverse industries. Here it is shown that abrasion‐resistant, half‐a‐meter scaled superhydrophobic objects can be one‐step realized by the selective laser sintering (SLS) 3D printing technology using hydrophobic‐fumed‐silica (HFS)/polymer composite grains. The HFS grains serve as the hydrophobic guests while the sintered polymeric network provides the mechanical strength, leading to low‐adhesion, intrinsic superhydrophobic objects with desired 3D structures. It is found that as‐printed structures remained anti‐wetting capabilities even after undergoing different abrasion tests, including knife cutting test, rude file grinding test, 1000 cycles of sandpaper friction test, tape test and quicksand impacting test, illustrating their abrasion‐resistant superhydrophobic stability. This strategy is applied to manufacture a shell of the unmanned aerial vehicle and an abrasion‐resistant superhydrophobic shoe, showing the industrial customization of large‐scale superhydrophobic objects. The findings thus provide insight for designing intrinsic superhydrophobic objects via the SLS 3D printing strategy that might find use in drag‐reduce, anti‐fouling, or other industrial fields in harsh operating environments.

E3 ubiquitin ligases (E3s), the second most common cancer-related functional protein family, play vital roles in multiple tumors. However, their importance in prognosis and immunotherapy of lung adenocarcinoma (LUAD) is not clear. First, utilizing the data from The Cancer Genome Atlas (TCGA), we comprehensively assessed the expression profile and immunological association of 13 E3s in LUAD patients. Consequently, MARCH1 was considered a candidate for further study. Second, several algorithms were applied to assess the correlation between MARCH1 and immunological characteristics in the LUAD tumor microenvironment. Third, an immune risk score (IRS) was developed to predict the prognosis. Finally, the immunological relationship of MARCH1 in pan-cancer was also estimated. We found that E3s were disordered in LUAD. Among them, MARCH1 was positively correlated with most immunological characteristics, indicating that MARCH1 designed an inflamed TME in LUAD. Coincidently, LUAD with low MARCH1 expression had a poor prognosis and was not sensitive to immune checkpoint blockers. In addition, the IRS could accurately predict the prognosis. In pan-cancer, MARCH1 was also positively correlated with most immunological characteristics. In conclusion, MARCH1 could be a novel and promising biomarker for immune status and effectiveness of immunotherapy for LUAD patients.

Objective: Dysfunction in fibroblast growth factor receptor (FGFR) signaling has been reported in diverse cancer types, including non-small cell lung cancer (NSCLC). The frequency of FGFR aberrations in Chinese NSCLC patients is therefore of great clinical significance. Methods: A total of 10,966 NSCLC patients whose tumor specimen and/or circulating cell-free DNA (cfDNA) underwent hybridization capture-based next-generation sequencing were reviewed. Patients’ clinical characteristics and treatment histories were also evaluated. Results: FGFR aberrations, including mutations, fusions, and gene amplifications, were detected in 1.9% (210/10,966) of the population. FGFR abnormalities were more frequently observed in lung squamous cell carcinomas (6.8%, 65/954) than lung adenocarcinomas (1.3%, 128/9,596). FGFR oncogenic mutations were identified in 19 patients (∼0.17%), of which, 68% were male lung squamous cell carcinoma patients. Eleven out of the 19 patients (58%) had concurrent altered PI3K signaling, thus highlighting a potential combination therapeutic strategy of dual-targeting FGFR and PI3K signaling in such patients. Furthermore, FGFR fusions retaining the intact kinase domain were identified in 12 patients (0.11%), including 9 FGFR3-TACC3, 1 FGFR2-INA, 1 novel FGFR4-RAPGEFL1, and 1 novel fusion between the FGFR1 and SLC20A2 5′-untranslated regions, which may have caused FGFR1 overexpressions. Concomitant EGFR mutations or amplifications were observed in 6 patients, and 4 patients received anti-EGFR inhibitors, in whom FGFR fusions may have mediated resistance to anti-EGFR therapies. FGFR amplification was detected in 24 patients, with the majority being FGFR1 amplifications. Importantly, FGFR oncogenic mutations, fusions, and gene amplifications were almost always mutually exclusive events. Conclusions: We report the prevalence of FGFR anomalies in a large NSCLC population, including mutations, gene amplifications, and novel FGFR fusions.

Indoor positioning technology is vital for various location-aware applications while visible light positioning (VLP) is especially promising due to its ubiquitous and energy-efficient features. VLP has been widely investigated under the assumption of line of sight (LoS), yet, VLP signal blockage can happen frequently in a practical indoor environment and brings about outage problems to indoor localization/tracking services. However, this problem is usually overlooked or sidestepped in the existing works. Our work, for the first time, investigates the outage problem in a received signal strength (RSS)-based VLP system. Efficient algorithms for outage bridging and trajectory recovery are proposed by smartly fusing with insufficient RSS information. Specifically, a partial-RSS-assisted inertial navigation system (PRAINS) inspired by extended Kalman filter (EKF) is developed to bridge sporadic outage, while a bi-directional structured PRAINS (Bid-PRAINS) is developed to use both pre- and post- outage information to recover the lost trajectory information. To further deal with a more general situation when the system noise features are not pre-known and hard to be measured/estimated, a semi-parameterized RNN based learnable Kalman filter (SPR-LKF) is proposed in place of the EKF to learn the observation/transition noise features and optimize the estimation simultaneously through a recurrent neural network (RNN). Extensive tests show that the PRAINS/ Bid-PRAINS has at least 62% accuracy improvement over the conventional inertial navigation system (INS)-only algorithm, while the proposed SPR-LKF/ Bid-SPR-LKF can offer an even better accuracy gain of 70% even without pre-knowing the system noise feature.

The type-I interferon (IFN-I) signaling pathway plays pivot roles in defending against pathogen invasion. Exogenous ssRNA and dsRNA could be immunogenic. RNA-mediated IFN signaling is extensively studied in the field. The incorrect functioning of this pathway leads to either autoimmune diseases or suffering from microorganism invasion. From the discrimination of “self” and “non-self” molecules by receptors to the fine-tune modulations in downstream cascades, all steps are under the surveillance featured by complex feedbacks and regulators. Studies in recent years highlighted the emerging roles of long noncoding RNAs (lncRNAs) as a reservoir for signaling regulation. LncRNAs bind to targets through the structure and sequence, and thus the mechanisms of action can be complex and specific. Here, we summarized lncRNAs modulating the RNA-activated IFN-I signaling pathway according to the event order during the signaling. We hope this review help understand how lncRNAs are participating in the regulation of IFN-I signaling.

Four types of flowerlike manganese dioxide in nano scale was synthesized via a liquid phase method in KMnO4-H2SO4 solution and Cu particles, wherein the effect of Cu particles was investigated in detail. The obtained manganese dioxide powder was characterized by XRD, SEM and TEM, and the supercapacity properties of MnO2 electrode materials were measured. The results showed that doping carbon black can benefit to better dispersion of copper particles, resulting in generated smaller size of Cu particles, and the morphology of MnO2 nanoparticles was dominated by that of Cu particles. The study of MnO2 synthesis by different sources of Cu particles showed that the size of MnO2 particles decreased significantly with freshly prepared fine copper powder compared with using commercial Cu powder, and the size of MnO2 particles can be further reduced to 120 nm by prepared Cu particles with smaller size. Therefore, it was suggested that the copper particles served as not only the reductant and but also the nuclei centre for the growth of MnO2 particles in synthesis process MnO2, and that is the reason how copper particles worked on the growth of flower-like MnO2 and electrochemical property. In the part of investigation for electrochemical property, the calculated results of b values indicated that the electrode materials have pseudo capacitance property, and the highest specific capacitance of 197.2 F g-1 at 2 mV s-1 and 148 F/g at 1 A/g were obtained for MCE electrode materials (MnO2 was synthesized with freshly prepared copper particles, where carbon black was used and dispersed in ethanol before preparation of Cu particles). The values of charge transfer resistance in all types of MnO2 materials electrodes were smaller than 0.08 Ω. The cycling retention of MCE material electrode is still kept as 93.8% after 1000 cycles.

There is great attention to develop hardware accelerator with better energy efficiency, as well as throughput, than GPUs for convolutional neural network (CNN). The existing solutions have relatively limited parallelism as well as large power consumption (including leakage power). In this paper, we present a resistive random access memory (ReRAM)-accelerated CNN that can achieve significantly higher throughput and energy efficiency when the CNN is trained with binary constraints on both weights and activations, and is further mapped on a digital ReRAM-crossbar. We propose an optimized accelerator architecture tailored for bitwise convolution that features massive parallelism with high energy efficiency. Numerical experiment results show that the binary CNN accelerator on a digital ReRAM-crossbar achieves a peak throughput of 792 GOPS at the power consumption of 4.5 mW, which is 1.61 times faster and 296 times more energy-efficient than a high-end GPU.

Orientation is one of the important elements of objects that can influence visual processing. In this study, we examined whether changes in orientation could be detected automatically under unattended condition. Visual mismatch negativity (vMMN) was used to analyze this processing. In addition, we investigated the underlying neural oscillatory activity. Non-phase-locked spectral power was used to explore the specific frequency related to unexpected changes in orientation. The experiment consisted of standard (0° arrows) and deviant (90°/270° arrows) stimuli. Compared with standard stimuli, deviant stimuli elicited a larger N170 component (negative wave approximately 170 ms after the stimuli started) and a smaller P2 component (positive wave approximately 200 ms after the stimuli started). Furthermore, vMMN was obtained by subtracting the event-related potential (ERP) waveforms in response to standard stimuli from those elicited in response to deviant stimuli. According to the time–frequency analysis, deviant stimuli elicited enhanced band power compared with standard stimuli in the delta and theta bands. Compared with previous studies, we concluded that theta activity plays an important role in the generation of the vMMN induced by changes in orientation.

In eukaryotes, the interphase nucleus is organized in morphologically and/or functionally distinct nuclear "compartments". Numerous studies highlight functional relationships between the spatial organization of the nucleus and gene regulation. This raises the question of whether nuclear organization principles exist and, if so, whether they are identical in the animal and plant kingdoms. We addressed this issue through the investigation of the three-dimensional distribution of the centromeres and chromocenters. We investigated five very diverse populations of interphase nuclei at different differentiation stages in their physiological environment, belonging to rabbit embryos at the 8-cell and blastocyst stages, differentiated rabbit mammary epithelial cells during lactation, and differentiated cells of Arabidopsis thaliana plantlets. We developed new tools based on the processing of confocal images and a new statistical approach based on G- and F- distance functions used in spatial statistics. Our original computational scheme takes into account both size and shape variability by comparing, for each nucleus, the observed distribution against a reference distribution estimated by Monte-Carlo sampling over the same nucleus. This implicit normalization allowed similar data processing and extraction of rules in the five differentiated nuclei populations of the three studied biological systems, despite differences in chromosome number, genome organization and heterochromatin content. We showed that centromeres/chromocenters form significantly more regularly spaced patterns than expected under a completely random situation, suggesting that repulsive constraints or spatial inhomogeneities underlay the spatial organization of heterochromatic compartments. The proposed technique should be useful for identifying further spatial features in a wide range of cell types.

E3 ubiquitin ligases (E3s), the second most common cancer-related functional protein family, play vital roles in multiple tumors. However, their importance in prognosis and immunotherapy of lung adenocarcinoma (LUAD) is not clear. First, utilizing the data from The Cancer Genome Atlas (TCGA), we comprehensively assessed the expression profile and immunological association of 13 E3s in LUAD patients. Consequently, MARCH1 was considered a candidate for further study. Second, several algorithms were applied to assess the correlation between MARCH1 and immunological characteristics in the LUAD tumor microenvironment. Third, an immune risk score (IRS) was developed to predict the prognosis. Finally, the immunological relationship of MARCH1 in pan-cancer was also estimated. We found that E3s were disordered in LUAD. Among them, MARCH1 was positively correlated with most immunological characteristics, indicating that MARCH1 designed an inflamed TME in LUAD. Coincidently, LUAD with low MARCH1 expression had a poor prognosis and was not sensitive to immune checkpoint blockers. In addition, the IRS could accurately predict the prognosis. In pan-cancer, MARCH1 was also positively correlated with most immunological characteristics. In conclusion, MARCH1 could be a novel and promising biomarker for immune status and effectiveness of immunotherapy for LUAD patients. [ABSTRACT FROM AUTHOR]