Association of adverse childhood experiences with poor health condition among middle-aged and elderly adults in the United States: A nationally retrospective cohort study.

BACKGROUND: The specific effects of adverse childhood experiences (ACEs) in adulthood and senectitude were less known. We aim to examine the relationship between early ACEs and overall health condition as well as specific dimensions in the middle-aged and elderly population. METHODS: In the 2019-2021 Behavioral Risk Factor Surveillance System Study, robust Poisson regression models were used to estimate the relationship between ACE exposure and current health status among adults aged 45 ≥ years. RESULTS: Of the 195,472 participants, 53.8 % were female and the mean age was 65.0 years. Compared to populations without ACE, ACE exposures were more significantly associated with depression (PR: 2.03, 95 %CI: 1.94-2.21), frequent mental health (PR: 1.85, 95 %CI: 1.74-1.97) and subject cognitive decline (PR: 1.99, 95 %CI:1.85-2.14) than with physical health (PR: 1.37, 95 %CI: 1.32-1.44), with dose-response patterns. The association with mental disorder was especially significant among the elderly population. CONCLUSION: Early ACEs are associated with adverse health outcomes that persist into later life, particularly mental disorders and cognitive decline. Poor mental health may indirectly influence associations with ACEs and cognitive decline as well as physical health. Our findings emphasize the importance of lifelong psychological screening and support for the ACE-exposed middle-aged and elderly population.

Fine hippocampal morphology analysis with a multi-dataset cross-sectional study on 2911 subjects.

CA1 subfield and subiculum of the hippocampus contain a series of dentate bulges, which are also called hippocampus dentation (HD). There have been several studies demonstrating an association between HD and brain disorders. Such as the number of hippocampal dentation correlates with temporal lobe epilepsy. And epileptic hippocampus have a lower number of dentation compared to contralateral hippocampus. However, most studies rely on subjective assessment by manual searching and counting in HD areas, which is time-consuming and labor-intensive to process large amounts of samples. And to date, only one objective method for quantifying HD has been proposed. Therefore, to fill this gap, we developed an automated and objective method to quantify HD and explore its relationship with neurodegenerative diseases. In this work, we performed a fine-scale morphological characterization of HD in 2911 subjects from four different cohorts of ADNI, PPMI, HCP, and IXI to quantify and explore differences between them in MR T1w images. The results showed that the degree of right hippocampal dentation are lower in patients with Alzheimer's disease than samples in mild cognitive impairment or cognitively normal, whereas this change is not significant in Parkinson's disease progression. The innovation of this paper that we propose a quantitative, robust, and fully automated method. These methodological innovation and corresponding results delineated above constitute the significance and novelty of our study. What's more, the proposed method breaks through the limitations of manual labeling and is the first to quantitatively measure and compare HD in four different brain populations including thousands of subjects. These findings revealed new morphological patterns in the hippocampal dentation, which can help with subsequent fine-scale hippocampal morphology research.

High-yield porphyrin production through metabolic engineering and biocatalysis.

Porphyrins and their derivatives find extensive applications in medicine, food, energy and materials. In this study, we produced porphyrin compounds by combining Rhodobacter sphaeroides as an efficient cell factory with enzymatic catalysis. Genome-wide CRISPRi-based screening in R. sphaeroides identifies hemN as a target for improved coproporphyrin III (CPIII) production, and exploiting phosphorylation of PrrA further improves the production of bioactive CPIII to 16.5 g L-1 by fed-batch fermentation. Subsequent screening and engineering high-activity metal chelatases and coproheme decarboxylase results in the synthesis of various metalloporphyrins, including heme and the anti-tumor agent zincphyrin. After pilot-scale fermentation (200 L) and setting up the purification process for CPIII (purity >95%), we scaled up the production of heme and zincphyrin through enzymatic catalysis in a 5-L bioreactor, with CPIII achieving respective enzyme conversion rates of 63% and 98% and yielding 10.8 g L-1 and 21.3 g L-1, respectively. Our strategy offers a solution for high-yield bioproduction of heme and other valuable porphyrins with substantial industrial and medical applications.

Applications of machine learning in urodynamics: A narrative review.

BACKGROUND: Machine learning algorithms as a research tool, including traditional machine learning and deep learning, are increasingly applied to the field of urodynamics. However, no studies have evaluated how to select appropriate algorithm models for different urodynamic research tasks. METHODS: We undertook a narrative review evaluating how the published literature reports the applications of machine learning in urodynamics. We searched PubMed up to December 2023, limited to the English language. We selected the following search terms: artificial intelligence, machine learning, deep learning, urodynamics, and lower urinary tract symptoms. We identified three domains for assessment in advance of commencing the review. These were the applications of urodynamic studies examination, applications of diagnoses of dysfunction related to urodynamics, and applications of prognosis prediction. RESULTS: The machine learning algorithm applied in the field of urodynamics can be mainly divided into three aspects, which are urodynamic examination, diagnosis of urinary tract dysfunction and prediction of the efficacy of various treatment methods. Most of these studies were single-center retrospective studies, lacking external validation, requiring further validation of model generalization ability, and insufficient sample size. The relevant research in this field is still in the preliminary exploration stage; there are few high-quality multi-center clinical studies, and the performance of various models still needs to be further optimized, and there is still a distance from clinical application. CONCLUSIONS: At present, there is no research to summarize and analyze the machine learning algorithms applied in the field of urodynamics. The purpose of this review is to summarize and classify the machine learning algorithms applied in this field and to guide researchers to select the appropriate algorithm model for different task requirements to achieve the best results.

Diachronic evolvement from tetra-icosahedral to quasi-hexagonal close-packed bimetal clusters.

Here we report a diachronic evolvement from tetra-icosahedral Au30Ag12(C[triple bond, length as m-dash]CR)24 to quasi-hcp (hexagonal close-packed) Au47Ag19(C[triple bond, length as m-dash]CR)32 via a one-step reduction, in which the size/structure conversion of the two clusters is not a typical Oswald growth process, but involves interface shrinking followed by core rearrangement and surface polymerization. Au30Ag12(C[triple bond, length as m-dash]CR)24 has an aesthetic Au18Ag8 kernel that is composed of four interpenetrating Au10Ag3 icosahedra, while Au47Ag19(C[triple bond, length as m-dash]CR)32 has a twisted Au19 core capped by a Au12Ag19 shell that are stacked in a layer-by-layer manner with a quasi-hcp pattern. The discovery of the two clusters not only provides further evidence for icosahedral clusters with longer excited-state lifetime compared to hcp-like clusters, but also discloses a double increase in catalytic reactivity for electrocatalytic oxidation of ethanol over quasi-hcp clusters in comparison with icosahedral clusters. This work provides the rationale for reversing the bottom-up growth process to remake bimetal clusters.

Efficacy and Safety of Anti-Programmed Cell Death Protein 1/Programmed Death-Ligand 1 Antibodies Plus Chemotherapy as First-Line Treatment for NSCLC in the People's Republic of China: a Systematic Review and Meta-Analysis.

Introduction: The available approved anticancer drugs for Chinese patients are relatively limited because of China's low participation rate in international clinical trials. Therefore, a focus on approved anti-programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) drugs in China is needed. This study aims to assess the heterogeneity of anti-PD-1/PD-L1 antibodies manufactured in China (domestic PD-1/PD-L1) and overseas (imported PD-1/PD-L1) when combined with chemotherapy as the first-line treatment of NSCLC. Methods: A systematic search was performed using PubMed, EMBASE, and Cochrane Library of publications up to July 13, 2023. Meta-analysis was applied to compare the efficacy and safety profile between anti-PD-1/PD-L1 antibodies plus chemotherapy (PD-1/PD-L1+Chemo) and chemotherapy alone using STATA software. Pooled hazard ratios for progression-free survival and overall survival, odds ratios for objective response rate, and incidence rate of grade greater than or equal to three treatment-related adverse events with 95% confidence intervals were calculated in the domestic group and imported group by a random-effects model, and the heterogeneity between the two estimates was assessed. Results: There were 14 eligible clinical studies with a total of 3951 patients involved in this analysis, including eight studies of domestic PD-1/PD-L1+Chemo and six studies of imported PD-1/PD-L1+Chemo. The study revealed that there was no significant difference between domestic and imported PD-1/PD-L1+Chemo in overall survival (p = 0.80), progression-free survival (p = 0.53), and incidence rate of grade greater than or equal to three treatment-related adverse events (p = 0.10). Nevertheless, the objective response rate of imported PD-1/PD-L1+Chemo was significantly higher than that of domestic PD-1/PD-L1+Chemo (p = 0.03). Conclusions: Domestic anti-PD-1/PD-L1 antibodies plus chemotherapy were found to have comparable efficacy and safety to those combined with imported anti-PD-1/PD-L1 antibodies based on current evidence.

Colorimetric array sensor based on bimetallic nitrogen-doped carbon-based nanozyme material to detect multiple antioxidants.

Copper-cobalt bimetallic nitrogen-doped carbon-based nanoenzymatic materials (CuCo@NC) were synthesized using a one-step pyrolysis process. A three-channel colorimetric sensor array was constructed for the detection of seven antioxidants, including cysteine (Cys), uric acid (UA), tea polyphenols (TP), lysine (Lys), ascorbic acid (AA), glutathione (GSH), and dopamine (DA). CuCo@NC with peroxidase activity was used to catalyze the oxidation of TMB by H2O2 at three different ratios of metal sites. The ability of various antioxidants to reduce the oxidation products of TMB (ox TMB) varied, leading to distinct absorbance changes. Linear discriminant analysis (LDA) results showed that the sensor array was capable of detecting seven antioxidants in buffer and serum samples. It could successfully discriminate antioxidants with a minimum concentration of 10 nM. Thus, multifunctional sensor arrays based on CuCo@NC bimetallic nanoenzymes not only offer a promising strategy for identifying various antioxidants but also expand their applications in medical diagnostics and environmental analysis of food.

Assessing the effectiveness of inhalation therapy in patients with chronic airway diseases: A new digital measurement.

BACKGROUND: This study aimed to evaluate the effectiveness of inhalation therapy in patients with chronic airway diseases via the use of a new multiparametric inhalation assessment device. METHODS: A multiparametric inhalation evaluation device (PF810, UBREATH, Zhejiang, China) that could simulate common inhalation devices with 6 different levels (0-V) of resistance was used in this study. The device was considered suitable if the three parameters of peak inspiratory flow rate (PIFR), effective inspiratory time (EIT), and breath-hold time (BHT) after inspiration met the minimum requirements. RESULTS: A total of 4,559 tests were performed. The qualification rates of 0-V resistance gear from low to high were 3.38 % (I), 8.42 % (0), 15.31 % (II), 16.71 % (III), 20.27 % (IV), and 46.91 % (V). The COPD patients in the 3 experimental groups had the lowest percentages of isolates classified as resistant 0, III, and V, which were 5.65 %, 11.93 %, and 40.43 %, respectively. The lowest percentage was 39.67 % (V) for insufficient EIT and 18.40 % (V) for BHT less than 5 s after inspiration. The results of 149 subjects who had used the inhalation device showed that the VIE and EIT at 0 levels were significantly greater than those before training (Z= -5.651, -5.646, P < 0.001). The VIE and EIT at I-III and V significantly increased after training (all P < 0.05). CONCLUSIONS: Patients using portable inhaler devices do not always inhale with adequate flow patterns. The multiparametric inhalation assessment device may be useful in outpatient settings.

Fluoride impairs vascular smooth muscle A7R5 cell lines via disrupting amino acids metabolism.

Given the insidious and high-fatality nature of cardiovascular diseases (CVDs), the emergence of fluoride as a newly identified risk factor demands serious consideration alongside traditional risk factors. While vascular smooth muscle cells (VSMCs) play a pivotal role in the progression of CVDs, the toxicological impact of fluoride on VSMCs remains largely uncharted. In this study, we constructed fluorosis model in SD rats and A7R5 aortic smooth muscle cell lines to confirm fluoride impaired VSMCs. Fluoride aggravated the pathological damage of rat aorta in vivo. Then A7R5 were exposed to fluoride with concentration ranging from 0 to 1200 µmol/L over a 24-h period, revealing a dose-dependent inhibition of cell proliferation and migration. The further metabolomic analysis showed alterations in metabolite profiles induced by fluoride exposure, notably decreasing organic acids and lipid molecules level. Additionally, gene network analysis underscored the frequency of fluoride's interference with amino acids metabolism, potentially impacting the tricarboxylic acid (TCA) cycle. Our results also highlighted the ATP-binding cassette (ABC) transporters pathway as a central element in VSMC impairment. Moreover, we observed a dose-dependent increase in osteopontin (OPN) and α-smooth muscle actin (α-SMA) mRNA level and a dose-dependent decrease in ABC subfamily C member 1 (ABCC1) and bestrophin 1 (BEST1) mRNA level. These findings advance our understanding of fluoride as a CVD risk factor and its influence on VSMCs and metabolic pathways, warranting further investigation into this emerging risk factor.

Spatially confined CuFe2O4 nanosphere in N/O-codoped porous carbon mimetics for triple-mode sensing of antibiotics and visual detection of neurotransmitters in biofluids.

BACKGROUND: Carbon-based nanozymes have recently received enormous concern, however, there is still a huge challenge for inexpensive and large-scale synthesis of magnetic carbon-based "Two-in-One" mimics with both peroxidase (POD)-like and laccase-like activities, especially their potential applications in multi-mode sensing of antibiotics and neurotransmitters in biofluids. Although some progresses have been made in this field, the feasibility of biomass-derived carbon materials with both POD-like and laccase-like activities by polyatomic doping strategy is still unclear. In addition, multi-mode sensing platform can provide a more reliable result because of the self-validation, self-correction and mutual agreement. Nevertheless, the use of magnetic carbon-based nanozyme sensors for the multi-mode detection of antibiotics and neurotransmitters have not been investigated. RESULTS: We herein report a shrimp shell-derived N, O-codoped porous carbon confined magnetic CuFe2O4 nanosphere with outstanding laccase-like and POD-like activities for triple-mode sensing of antibiotic d-penicillamine (D-PA) and chloramphenicol (CPL), as well as colorimetric detection of neurotransmitters in biofluids. The magnetic CuFe2O4/N, O-codoped porous carbon (MCNPC) armored mimetics was successfully fabricated using a combined in-situ coordination and high-temperature crystallization method. The synthesized MCNPC composite with superior POD-like activity can be used for colorimetric/temperature/smartphone-based triple-mode detection of D-PA and CPL in goat serum. Importantly, the MCNPC nanozyme can also be used for colorimetric analysis of dopamine and epinephrine in human urine. SIGNIFICANCE: This work not only offered a novel strategy to large-scale, cheap synthesize magnetic carbon-based "Two-in-One" armored mimetics, but also established the highly sensitive and selective platforms for triple-mode monitoring D-PA and CPL, as well as colorimetric analysis of neurotransmitters in biofluids without any tanglesome sample pretreatment.

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System.

OBJECTIVES: Freehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference. METHODS: To address the above issues, we integrated a binocular camera and an inertial measurement unit (IMU) on a US probe. Subsequently, we built a tight coupling model utilizing the unscented Kalman algorithm based on Lie groups (UKF-LG), combining vision and inertial information to infer the probe's movement, through which the position and orientation of the US image frame are calculated. Finally, the volume data was reconstructed with the voxel-based hole-filling method. RESULTS: The experiments including calibration experiments, tracking performance evaluation, phantom scans, and real scenarios scans have been conducted. The results show that the proposed system achieved the accumulated frame position error of 3.78 mm and the orientation error of 0.36° and reconstructed 3D US images with high quality in both phantom and real scenarios. CONCLUSIONS: The proposed method has been demonstrated to enhance the robustness and effectiveness of freehand 3D US. Follow-up research will focus on improving the accuracy and stability of multi-sensor fusion to make the system more practical in clinical environments.

Identification of Key Genes of Fruit Shape Variation in Jujube with Integrating Elliptic Fourier Descriptors and Transcriptome.

Jujube (Ziziphus jujuba) exhibits a rich diversity in fruit shape, with natural occurrences of gourd-like, flattened, and other special shapes. Despite the ongoing research into fruit shape, studies integrating elliptical Fourier descriptors (EFDs) with both Short Time-series Expression Miner (STEM) and weighted gene co-expression network analysis (WGCNA) for gene discovery remain scarce. In this study, six cultivars of jujube fruits with distinct shapes were selected, and samples were collected from the fruit set period to the white mature stage across five time points for shape analysis and transcriptome studies. By combining EFDs with WGCNA and STEM, the study aimed to identify the critical periods and key genes involved in the formation of jujube fruit shape. The findings indicated that the D25 (25 days after flowering) is crucial for the development of jujube fruit shape. Moreover, ZjAGL80, ZjABI3, and eight other genes have been implicated to regulate the shape development of jujubes at different periods of fruit development, through seed development and fruit development pathway. In this research, EFDs were employed to precisely delineate the shape of jujube fruits. This approach, in conjunction with transcriptome, enhanced the precision of gene identification, and offered an innovative methodology for fruit shape analysis. This integration facilitates the advancement of research into the morphological characteristics of plant fruits, underpinning the development of a refined framework for the genetic underpinnings of fruit shape variation.

Axillary lymph node metastasis in pure mucinous carcinoma of breast: clinicopathologic and ultrasonographic features.

BACKGROUND: The purpose of this research is to study the sonographic and clinicopathologic characteristics that associate with axillary lymph node metastasis (ALNM) for pure mucinous carcinoma of breast (PMBC). METHODS: A total of 176 patients diagnosed as PMBC after surgery were included. According to the status of axillary lymph nodes, all patients were classified into ALNM group (n = 15) and non-ALNM group (n = 161). The clinical factors (patient age, tumor size, location), molecular biomarkers (ER, PR, HER2 and Ki-67) and sonographic features (shape, orientation, margin, echo pattern, posterior acoustic pattern and vascularity) between two groups were analyzed to unclose the clinicopathologic and ultrasonographic characteristics in PMBC with ALNM. RESULTS: The incidence of axillary lymph node metastasis was 8.5% in this study. Tumors located in the outer side of the breast (upper outer quadrant and lower outer quadrant) were more likely to have lymphatic metastasis, and the difference between the two group was significantly (86.7% vs. 60.3%, P = 0.043). ALNM not associated with age (P = 0.437). Although tumor size not associated with ALNM(P = 0.418), the tumor size in ALNM group (32.3 ± 32.7 mm) was bigger than non-ALNM group (25.2 ± 12.8 mm). All the tumors expressed progesterone receptor (PR) positively, and 90% of all expressed estrogen receptor (ER) positively, human epidermal growth factor receptor 2 (HER2) were positive in two cases of non-ALNM group. Ki-67 high expression was observed in 36 tumors in our study (20.5%), and it was higher in ALNM group than non-ALNM group (33.3% vs. 19.3%), but the difference wasn't significantly (P = 0.338). CONCLUSIONS: Tumor location is a significant factor for ALNM in PMBC. Outer side location is more easily for ALNM. With the bigger size and/or Ki-67 higher expression status, the lymphatic metastasis seems more likely to present.

Exploring the stable structures of cerium oxide nanoclusters using high-dimensional neural network potential.

Cerium clusters have been extensively applied in industry owing to their extraordinary properties for oxygen storage and redox catalytic activities. However, their atomically precise structures have not been studied because of the lack of a reliable method to efficiently sample their complex structures. Herein, we combined a neural network algorithm with density functional theory calculations to establish a high-dimensional potential to search for the global minimums of cerium oxide clusters. Using Ce14O28 as well as its reduced state Ce14O27 and oxidized state Ce14O29 with ultra-small dimensions of ∼1.0 nm as examples, we found that these three clusters adopt pyramid-like structures with the lowest energies, which was obtained by exploring 100 000 configurations in large feasible spaces. Further the neural network potential-enhanced molecular dynamics calculations indicated that these cluster structures are stable at high temperature. The electronic structure analysis suggested that these clusters are highly active and easily lose oxygen. This work demonstrated that neural network potentials can be useful for exploring the stable structures of metal oxide nanoclusters in practical applications.

Prevalence, Medicaid use and mortality risk of low FEV1 in adults aged 20-35 years old in the USA: evidence from a population-based retrospective cohort study.

BACKGROUND: The prevalence, Medicaid use and mortality risk associated with low forced expiratory volume in 1 s (FEV1) among young adults aged 20-35 years are not well understood, despite its potential implications for the development of chronic pulmonary disease and overall prognosis. METHODS: A retrospective cohort study was conducted among young adults aged 20-35 years old, using data from the National Health and Nutrition Examination Survey, National Death Index and Centers for Medicare & Medicaid Services. Participants were categorised into a low FEV1 group (pre-bronchodilator FEV1%pred <80%) and a normal FEV1 group (FEV1%pred ≥80%). Weighted logistic regression analysis was employed to identify the risk factors associated with low FEV1, while Cox proportional hazard models were used to calculate the hazard ratio (HR) for Medicaid use and the all-cause mortality between the two groups. RESULTS: A total of 5346 participants aged 20-35 were included in the study, with 329 in the low FEV1 group and 5017 in the normal group. The weighted prevalence of low FEV1 among young adults was 7.1% (95% CI 6.0 to 8.2). Low body mass index (OR=3.06, 95% CI 1.79 to 5.24), doctor-diagnosed asthma (OR=2.25, 1.28 to 3.93), and wheezing or whistling (OR=1.57, 1.06 to 2.33) were identified as independent risk factors for low FEV1. Over a 15-year follow-up, individuals in the low FEV1 group exhibited a higher likelihood of Medicaid use compared with those in the normal group (HR=1.73, 1.07 to 2.79). However, there was no statistically significant increase in the risk of all-cause mortality over a 30-year follow-up period (HR=1.48, 1.00 to 2.19). CONCLUSIONS: A considerable portion of young adults demonstrated low FEV1 levels, a characteristic that was associated with a higher risk of Medicaid use over a long-term follow-up, yet not linked to an augmented risk of all-cause mortality.

Understanding Care Needs of Older Adults with Disabilities: A Scoping Review.

Purpose: To conducted a scoping review of care needs of older adults with disabilities at home and in the community and provide a comprehensive understanding of the essential needs of older adults with disabilities. Methods: Eight databases were searched for relevant Chinese and English studies (supplemented by retrospective references of the included studies) from the establishment of the database to February 13, 2023. An thematic synthesis approach was used to qualitatively integrate the retrieved studies and identify need-related themes. Results: A total of 6239 studies were retrieved, 2557 were de-weighted and excluded, and 56 were obtained after the double screening. Studies were from 11 countries. Thirty-three studies used a self-prepared survey instrument to investigate needs, and the other research tools commonly used were secondary databases and the Long-Term Care Needs of the Disabled Scale. A total of 78 specific need items were identified and summarized into three need themes based on the ICF framework: physical functioning needs, activity and participation needs, and environment needs. Conclusion: The complex physical and mental health conditions faced by older adults with disabilities result in multifaceted, integrated needs that are difficult to identify and meet. Current research on older adults with disabilities is limited to common care. Future research should focus on the specificities of the older disabled population and understand the diverse care needs of people with disabilities in order to better target care services for this group. Policymakers should formulate more operational and strategic measures based on the actual needs of older adults with disabilities to expand the coverage of services and to pinpoint care services.

Research progress of KL-6 in respiratory system diseases.

This article comprehensively elucidates the discovery of Krebs von den Lungen-6 (KL-6), its structural features, functional mechanisms, and the current research status in various respiratory system diseases. Discovered in 1985, KL-6 was initially considered a tumor marker, but its elevated levels in interstitial lung disease (ILD) led to its recognition as a relevant serum marker for ILD. KL-6 is primarily produced by type 2 alveolar epithelial cell regeneration. Over the past 30 years since the discovery of KL-6, the number of related research papers has steadily increased annually. Following the coronavirus disease 2019 (COVID-19) pandemic, there has been a sudden surge in relevant literature. Despite KL-6's potential as a biomarker, its value in the diagnosis, treatment, and prognosis varies across different respiratory diseases, including ILD, idiopathic pulmonary fibrosis (IPF), COVID-19, and lung cancer. Therefore, as an important serum biomarker in respiratory system diseases, the value of KL-6 still requires further investigation.

Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets.

BACKGROUND: This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0. METHODS: Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis. RESULTS: The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis. CONCLUSION: These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.

Dynamic Active Sites In Situ Formed in Metal Nanoparticle Reshaping under Reaction Conditions.

Understanding the nonequilibrium transformation of nanocatalysts under reaction conditions is important because metastable atomic structures may be created during the process, which offers unique activities in reactions. Although reshaping of metal nanoparticles (NPs) under reaction conditions has been widely recognized, the dynamic reshaping process has been less studied at the atomic scale. Here, we develop an atomistic kinetic Monte Carlo model to simulate the complete reshaping process of Pt nanoparticles in a CO environment and reveal the in situ formation of atomic clusters on the NP surface, a new type of active site beyond conventional understanding, boosting the reactivities in the CO oxidation reaction. Interestingly, highly active peninsula and inactive island clusters both form on the (111) facets and interchange in varying states of dynamic equilibrium, which influences the catalytic activities significantly. This study provides new fundamental knowledge of nanocatalysis and new guidance for the rational design of nanocatalysts.