Imaging diagnostics of pulmonary ground-glass nodules: a narrative review with current status and future directions.

Background and Objective: The incidence rate of lung cancer, which also has the highest mortality rates for both men and women worldwide, is increasing globally. Due to advancements in imaging technology and the growing inclination of individuals to undergo screening, the detection rate of ground-glass nodules (GGNs) has surged rapidly. Currently, artificial intelligence (AI) methods for data analysis and interpretation, image processing, illness diagnosis, and lesion prediction offer a novel perspective on the diagnosis of GGNs. This article aimed to examine how to detect malignant lesions as early as possible and improve clinical diagnostic and treatment decisions by identifying benign and malignant lesions using imaging data. It also aimed to describe the use of computed tomography (CT)-guided biopsies and highlight developments in AI techniques in this area. Methods: We used PubMed, Elsevier ScienceDirect, Springer Database, and Google Scholar to search for information relevant to the article's topic. We gathered, examined, and interpreted relevant imaging resources from the Second Affiliated Hospital of Nanchang University's Imaging Center. Additionally, we used Adobe Illustrator 2020 to process all the figures. Key Content and Findings: We examined the common signs of GGNs, elucidated the relationship between these signs and the identification of benign and malignant lesions, and then described the application of AI in image segmentation, automatic classification, and the invasiveness prediction of GGNs over the last three years, including its limitations and outlook. We also discussed the necessity of conducting biopsies of persistent pure GGNs. Conclusions: A variety of imaging features can be combined to improve the diagnosis of benign and malignant GGNs. The use of CT-guided puncture biopsy to clarify the nature of lesions should be considered with caution. The development of new AI tools brings new possibilities and hope to improving the ability of imaging physicians to analyze GGN images and achieving accurate diagnosis.

Association of polygenic risk scores with Alzheimer's disease and plasma biomarkers among Chinese older adults: A community-based study.

INTRODUCTION: We examined the associations of polygenic risk score (PRS) with Alzheimer's disease (AD) and plasma biomarkers in the Chinese population. METHODS: This population-based study used baseline data from MIND-China (2018; n = 4873) and follow-up data from dementia-free individuals (2014-2018; n = 2117). We measured AD-related plasma biomarkers in a subsample (n = 1256). Data were analyzed using logistic and Cox regression models. RESULTS: We developed PRS with (PRSAPOE) and without (PRSnon- APOE) apolipoprotein E (APOE) gene. In the longitudinal analysis, PRSAPOE was associated with a multivariable-adjusted hazards ratio of 1.91 (95% CI = 1.13-3.23) for AD. PRSAPOE in combination with demographics yielded discriminative (area under the curve [AUC]) and predictive(C-statistic) accuracy of 0.80 (95% confidence interval [CI] = 0.77-0.84) and 0.80 (0.77-0.82), respectively. PRSnon- APOE showed an association with AD risk similar to PRSAPOE. PRSAPOE, but not PRSnon- APOE, was associated with reduced plasma Aß42/Aß40 ratio and increased Neurofilament light chain (NfL) (p < 0.05). DISCUSSION: The PRS with and without APOE gene, in combination with demographics, shows good discriminative and predictive ability for AD. The AD-related pathologies underlie AD risk associated with PRSAPOE. HIGHLIGHTS: The PRSAPOE and PRSnon- APOE were associated with AD risk in the Chinese population. The PRSAPOE and PRSnon- APOE, in combination with demographics, showed good discriminative and predictive ability for AD. The AD-related pathologies underlie the AD risk associated with PRSAPOE but not PRSnon- APOE.

Structural, antioxidant activity, and stability studies of jellyfish collagen peptide-calcium chelates.

The aim of this study was to prepare and characterize jellyfish collagen peptide (JCP)-calcium chelates (JCP-Ca) using peptides with different molecular weights. Further analysis revealed that the low-molecular-weight jellyfish collagen peptide (JCP1) had a higher chelation rate. Structural characterization showed that functional groups such as N-H, C[bond, double bond]O, and -COO were involved in the formation of JCP-Ca, which shifted towards a more ordered and regular structure, and smaller-molecular-weight peptides were more likely to form a denser structure. In addition, JCPs chelated with calcium ions showed excellent antioxidant capacity. JCP-Ca showed good stability in heat-treated and gastrointestinal environments, whereas the antioxidant activity was significantly reduced under highly acidic conditions. The present study addresses the knowledge gap regarding the physicochemical properties of JCP-Ca and establishes a solid research foundation for its associated products.

Analyzing resilience influencing factors in the prefabricated building supply chain based on SEM-SD methodology.

The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC. A Structural Equation Model (SEM) was used to explore the relationships between these factors. System dynamics were applied to create a simulation model, assessing the resilience impact level and conducting sensitivity analysis. The results show that the transportation and procurement processes are the most significant factors influencing supply chain resilience. The external environmental factors wielded a more pronounced impact on the overall evaluation of supply chain resilience than the delivery and use processes, but delivery and use processes are more sensitive. The study uses the Pressure-State-Response (PSR) model to suggest strategies for enhancing supply chain resilience. This study contributes to more sustainable and efficient construction practices by offering an innovative theoretical framework to analyze the factors influencing PBSC resilience and proposing enhancement strategies.

Cardiometabolic multimorbidity, peripheral biomarkers, and dementia in rural older adults: The MIND-China study.

INTRODUCTION: Evidence has emerged that cardiometabolic multimorbidity (CMM) is associated with dementia, but the underlying mechanisms are poorly understood. METHODS: This population-based study included 5704 older adults. Of these, data were available in 1439 persons for plasma amyloid-ß (Aß), total tau, and neurofilament light chain (NfL) and in 1809 persons for serum cytokines. We defined CMM following two common definitions used in previous studies. Data were analyzed using general linear, logistic, and mediation models. RESULTS: The presence of CMM was significantly associated with an increased likelihood of dementia, Alzheimer's disease (AD), and vascular dementia (VaD) (p < 0.05). CMM was significantly associated with increased plasma Aß40, Aß42, and NfL, whereas CMM that included visceral obesity was associated with increased serum cytokines. The mediation analysis suggested that plasma NfL significantly mediated the association of CMM with AD. DISCUSSION: CMM is associated with dementia, AD, and VaD in older adults. The neurodegenerative pathway is involved in the association of CMM with AD. HIGHLIGHTS: The presence of CMM was associated with increased likelihoods of dementia, AD, and VaD in older adults. CMM was associated with increased AD-related plasma biomarkers and serum inflammatory cytokines. Neurodegenerative pathway was partly involved in the association of CMM with AD.

Subsurface Single-atom Catalyst Enabled by Mechanochemical Synthesis for Oxidation Chemistry.

Single-atom catalysts have garnered significant attention due to their exceptional atom utilization and unique properties. However, the practical application of these catalysts is often impeded by challenges such as sintering-induced instability and poisoning of isolated atoms due to strong gas adsorption. In this study, we employed the mechanochemical method to insert single Cu atoms into the subsurface of Fe2O3 support. By manipulating the location of single atoms at the surface or subsurface, catalysts with distinct adsorption properties and reaction mechanisms can be achieved. It was observed that the subsurface Cu single atoms in Fe2O3 remained isolated under both oxidation and reduction environments, whereas surface Cu single atoms on Fe2O3 experienced sintering under reduction conditions. The unique properties of these subsurface single-atom catalysts call for innovations and new understandings in catalyst design.

How well do models of visual cortex generalize to out of distribution samples?

Unit activity in particular deep neural networks (DNNs) are remarkably similar to the neuronal population responses to static images along the primate ventral visual cortex. Linear combinations of DNN unit activities are widely used to build predictive models of neuronal activity in the visual cortex. Nevertheless, prediction performance in these models is often investigated on stimulus sets consisting of everyday objects under naturalistic settings. Recent work has revealed a generalization gap in how predicting neuronal responses to synthetically generated out-of-distribution (OOD) stimuli. Here, we investigated how the recent progress in improving DNNs' object recognition generalization, as well as various DNN design choices such as architecture, learning algorithm, and datasets have impacted the generalization gap in neural predictivity. We came to a surprising conclusion that the performance on none of the common computer vision OOD object recognition benchmarks is predictive of OOD neural predictivity performance. Furthermore, we found that adversarially robust models often yield substantially higher generalization in neural predictivity, although the degree of robustness itself was not predictive of neural predictivity score. These results suggest that improving object recognition behavior on current benchmarks alone may not lead to more general models of neurons in the primate ventral visual cortex.

Characterisation and comparison of enzymatically prepared donkey milk whey protein hydrolysates.

This study evaluated the structural characteristics, processing properties, and antioxidant properties of hydrolysates prepared from donkey milk (DM) whey protein using different proteases (Alcalase, Neutrase, papain, and Flavourzyme). The results showed that enzymatic hydrolysis significantly increased hydrolysate solubility and reduced average particle size compared to those of DM whey protein. Neutrase and Flavourzyme hydrolysates exhibited higher degrees of hydrolysis (DH), along with elevated emulsification properties and surface hydrophobicity. The choice of protease influenced secondary and tertiary protein structures and amino acid composition. Enzymatic hydrolysis led to decreased molecular weight of DM whey proteins. Moreover, all hydrolysates exhibited higher fluorescence intensity at λmax compared to DM whey protein, implying distinct properties due to the varied impacts of the four proteases on DM whey protein structure. The preparation of hydrolysates from DM whey proteins using proteases contributes to the development of integrated-value DM products.

Construction of an Exercise Intervention Program for Patients with Sarcopenic Obesity: A Delphi Method Study.

Purpose: Construct an exercise intervention program for patients with sarcopenic obesity. Material and Methods: Based on the COM-B theoretical model and evidence-based principles, the program was constructed using qualitative methods of literature analysis and Delphi method. The Delphi panel consisted of 15 experts from the fields of clinical medicine, rehabilitation medicine, medical technology, and nursing. Results: Fifteen experts were consulted, and the consultation recovery rate was 100%; the authority coefficient of the 1st round was 0.83, with coefficients of variation ranging from 0.00 to 0.27, and importance scores ranging from (4.13±1.13) to (5±0); the authority coefficient of the 2nd round was 0.82, with coefficients of variation ranging from 0.00 to 0.20, and importance scores ranging from (4.53±0.64) to (5±0); Kendall's harmony coefficient was 0.102, 0.115, respectively, and the differences were statistically significant(P < 0.05). The constructed exercise intervention program for patients with sarcopenic obesity included 4 primary indicators, 12 secondary indicators, and 28 tertiary indicators. Conclusion: The constructed exercise intervention program for patients with sarcopenic obesity is scientific, feasible and generalizable, and can provide useful reference for related personnel to develop exercise programs for patients with sarcopenic obesity.

Tartronic Acid as a Potential Inhibitor of Pathological Calcium Oxalate Crystallization.

Kidney stones are a pervasive disease with notoriously high recurrence rates that require more effective treatment strategies. Herein, tartronic acid is introduced as an efficient inhibitor of calcium oxalate monohydrate (COM) crystallization, which is the most prevalent constituent of human kidney stones. A combination of in situ experimental techniques and simulations are employed to compare the inhibitory effects of tartronic acid with those of its molecular analogs. Tartronic acid exhibits an affinity for binding to rapidly growing apical surfaces of COM crystals, thus setting it apart from other inhibitors such as citric acid, the current preventative treatment for kidney stones. Bulk crystallization and in situ atomic force microscopy (AFM) measurements confirm the mechanism by which tartronic acid interacts with COM crystal surfaces and inhibits growth. These findings are consistent with in vivo studies that reveal the efficacy of tartronic acid is similar to that of citric acid in mouse models of hyperoxaluria regarding their inhibitory effect on stone formation and alleviating stone-related physical harm. In summary, these findings highlight the potential of tartronic acid as a promising alternative to citric acid for the management of calcium oxalate nephropathies, offering a new option for clinical intervention in cases of kidney stones.

EP300-ZNF384 transactivates IL3RA to promote the progression of B-cell acute lymphoblastic leukemia.

The EP300-ZNF384 fusion gene is an oncogenic driver in B-cell acute lymphoblastic leukemia (B-ALL). In the present study, we demonstrated that EP300-ZNF384 substantially induces the transcription of IL3RA and the expression of IL3Rα (CD123) on B-ALL cell membranes. Interleukin 3 (IL-3) supplementation promotes the proliferation of EP300-ZNF348-positive B-ALL cells by activating STAT5. Conditional knockdown of IL3RA in EP300-ZF384-positive cells inhibited the proliferation in vitro, and induced a significant increase in overall survival of mice, which is attributed to impaired propagation ability of leukemia cells. Mechanistically, the EP300-ZNF384 fusion protein transactivates the promoter activity of IL3RA by binding to an A-rich sequence localized at -222/-234 of IL3RA. Furthermore, forced EP300-ZNF384 expression induces the expression of IL3Rα on cell membranes and the secretion of IL-3 in CD19-positive B precursor cells derived from healthy individuals. Doxorubicin displayed a selective killing of EP300-ZNF384-positive B-ALL cells in vitro and in vivo. Collectively, we identify IL3RA as a direct downstream target of EP300-ZNF384, suggesting CD123 is a potent biomarker for EP300-ZNF384-driven B-ALL. Targeting CD123 may be a novel therapeutic approach to EP300-ZNF384-positive patients, alternative or, more likely, complementary to standard chemotherapy regimen in clinical setting.

Association of Triglyceride-Glucose Index With Cognitive Function and Brain Atrophy: A Population-Based Study.

OBJECTIVE: To investigate the associations of triglyceride-glucose (TyG) index, a reliable surrogate marker for insulin resistance, with the function of various cognitive domains and brain structures among older adults. DESIGN: A population-based cross-sectional study. SETTING: Older adults living in the rural communities in China. PARTICIPANTS: About 4,541 rural-dwelling dementia-free participants (age ≥65 years; 56.37% women) undertook examinations in March-September 2018 for MIND-China. MEASUREMENTS: TyG index was calculated as ln[fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. A neuropsychological test battery was used to assess memory, attention, verbal fluency, and executive function. Volumetric brain measures were assessed on magnetic resonance imaging (MRI) in a subsample (n = 1,019). Data were analyzed with restricted cubic spline and multivariable general linear models. RESULTS: An inverted J-shaped association was observed between TyG index and z-scores of multiple cognitive domains, such that among individuals with TyG index ≥8.57 (median), a higher TyG index was significantly associated with lower z-scores of memory, attention, verbal fluency, executive function, and global cognition (all p < 0.05); among people with TyG index <8.57, a higher TyG index was significantly associated with a higher executive function z-score (p < 0.05), but not with any of the other examined cognitive domains. In the MRI subsample, a higher TyG index was significantly associated with lower volumes of total brain tissue, gray matter, and white matter as well as greater cerebrospinal fluid volume (p < 0.05), but not with white matter hyperintensity volume. CONCLUSIONS: Insulin resistance, as indicated by a high TyG index, was associated with poor function in multiple cognitive domains and global brain atrophy.

Multimorbidity, cognitive phenotypes, and Alzheimer's disease plasma biomarkers in older adults: A population-based study.

INTRODUCTION: To examine the burden and clusters of multimorbidity in association with mild cognitive impairment (MCI), dementia, and Alzheimer's disease (AD)-related plasma biomarkers among older adults. METHODS: This population-based study included 5432 participants (age ≥60 years); of these, plasma amyloid beta (Aß), total tau, and neurofilament light chain (NfL) were measured in a subsample (n = 1412). We used hierarchical clustering to generate five multimorbidity clusters from 23 chronic diseases. We diagnosed dementia and MCI following international criteria. Data were analyzed using logistic and linear regression models. RESULTS: The number of chronic diseases was associated with dementia (multivariable-adjusted odds ratio = 1.22; 95% confidence interval [CI] = 1.11 to 1.33), AD (1.13; 1.01 to 1.26), vascular dementia (VaD) (1.44; 1.25 to 1.64), and non-amnestic MCI (1.25; 1.13 to 1.37). Metabolic cluster was associated with VaD and non-amnestic MCI, whereas degenerative ocular cluster was associated with AD (p < 0.05). The number of chronic diseases was associated with increased plasma Aß and NfL (p < 0.05). DISCUSSION: Multimorbidity burden and clusters are differentially associated with subtypes of dementia and MCI and AD-related plasma biomarkers in older adults. HIGHLIGHTS: We used hierarchical clustering to generate five clusters of multimorbidity. The presence and load of multimorbidity were associated with dementia and mild cognitive impairment. Multimorbidity clusters were differentially associated with subtypes of dementia and Alzheimer's disease plasma biomarkers.

Hybridized gated recurrent unit with variational mode decomposition and an error compensation mechanism for multi-step-ahead monthly rainfall forecasting.

Highly accurate monthly rainfall predictions can provide early warnings for rain-related disasters, such as floods and droughts, and allow governments to make timely decisions. This paper proposes a two-phase error compensation model based on a gated recurrent unit (GRU), variational mode decomposition (VMD), and error compensation mechanism (ECM) (GRU-VMD-ECM) for accurate multi-step-ahead monthly rainfall forecasts. In the first phase, the GRU model is used to make an initial monthly rainfall prediction, and the error series is extracted. In the second phase, the error series is decomposed into eight subseries using the VMD method. Each subseries is then input into the GRU model to build different forecasting models. These predicted error sequences are added to the initial prediction results to obtain the final forecast. The model's performance is tested using six evaluation indicators based on Beijing's monthly rainfall data from 1951 to 2018. The results show that the error compensation mechanism significantly improved the prediction accuracy, particularly in the Nash-Sutcliffe efficiency (NSE) of single-step-ahead prediction which recorded a substantial increase of 281.16% from 0.259981 to 0.990944, as well as a decrease in root mean square error (RMSE) from 2.257580 to 0.249746. Furthermore, the GRU-VMD-ECM model outperforms the RF, GRU-CNN, and VMD-GRU models in terms of precision across all forecasting horizons. These findings highlight the potential of the GRU-VMD-ECM model in providing highly accurate monthly rainfall predictions for early warnings and informed decision-making by governments.

TAX1BP1 downregulation by STAT3 in cardiac fibroblasts contributes to diabetes-induced heart failure with preserved ejection fraction.

Heart failure (HF) with preserved ejection fraction (HFpEF) is now the most common form of HF and has been reported to be closely related to diabetes. Accumulating evidence suggests that HFpEF patients exhibit cardiac fibrosis. This study investigates whether direct targeted inhibition of the activation of cardiac fibroblasts (CFs), the main effector cells in cardiac fibrosis, improves diabetes-induced HFpEF and elucidates the underlying mechanisms. Twenty-week-old db/db mice exhibited HFpEF, as confirmed by echocardiography and hemodynamic measurements. Proteomics was performed on CFs isolated from the hearts of 20-week-old C57BL/6 and db/db mice. Bioinformatic prediction was used to identify target proteins. Experimental validation was performed in both high glucose (HG)-treated neonatal mouse CFs (NMCFs) and diabetic hearts. TAX1 binding protein 1 (TAX1BP1) was identified as the most significantly differentially expressed protein between 20-week-old C57BL/6 and db/db mice. TAX1BP1 mRNA and protein were markedly downregulated in CFs from diabetic hearts and HG-cultured NMCFs. Overexpression of TAX1BP1 profoundly inhibited HG/diabetes-induced NF-κB nuclear translocation and collagen synthesis in CFs, improved cardiac fibrosis, hypertrophy, inflammation and HFpEF in diabetic mice. Mechanistically, signal transducer and activator of transcription 3 (STAT3), which is phosphorylated and translocated from the cytoplasm into the nucleus under hyperglycemic conditions, bound to TAX1BP1 promoter and blocked TAX1BP1 transcriptional activity, consequently promoting NF-κB nuclear translocation and collagen synthesis in CFs, aggravating cardiac fibrosis, hypertrophy and inflammation, leading to HFpEF in db/db mice. Taken together, our findings demonstrate that targeting regulation of STAT3-TAX1BP1-NF-κB signaling in CFs may be a promising therapeutic approach for diabetes-induced HFpEF.

RNA-seq analysis of small intestine transcriptional changes induced by starvation stress in piglets.

Piglets may experience a variety of stress injuries, but the molecular regulatory mechanisms underlying these injuries are not well understood. In this study, we analysed the ileum of Large White (LW) and Mashen (MS) piglets at different times of starvation using chemical staining and transcriptome analysis. The intestinal barrier of piglets was damaged after starvation stress, but the intestinal antistress ability of MS piglets was stronger than LW piglets. A total of 8021 differentially expressed genes (DEGs) were identified in two breeds. Interestingly, the immune capacity (CHUK, TLR3) of MS piglets increased significantly after short-term starvation stress, while energy metabolism (NAGS, PLA2G12B, AGCG8) was predominant in LW piglets. After long-term starvation stress, the level of energy metabolism (PLIN5, PLA2G12B) was significantly increased in MS piglets. The expression of immune (HLA-DQB1, IGHG4, COL3A1, CD28, LAT) and disease (HSPA1B, MINPPI, ADH1C, GAL3ST1) related genes were significantly increased in two breeds of piglets. These results suggest that short-term stress mainly enhances immunity and energy metabolism in piglets, while long-term starvation produces greater stress on piglets, making it difficult for them to compensate for the damage to their bodies through self-regulation. This information can help improve the stress resistance of piglets through molecular breeding.

Resting heart rate, cognitive function, and inflammation in older adults: a population-based study.

BACKGROUND: Emerging evidence has linked elevated resting heart rate (RHR) with poor cognitive function in older adults, but the mechanisms underlying their association are poorly understood. METHODS: This population-based cross-sectional study included 4510 dementia-free participants (age ≥ 65 years; 56.9% females; 38.3% no formal education) in the baseline examination of the Multidomain Interventions to Delay Dementia and Disability in Rural China study. Of these, 1,386 had data on serum proinflammatory cytokines and adhesion molecules. RHR was measured using 12-lead electrocardiograph. We used the Mini-Mental State Examination (MMSE) and a neuropsychological test battery to assess cognitive function. Data were analyzed using the general linear and restricted cubic splines models. RESULTS: People with high RHR were more likely to have cardiometabolic diseases and worse cognitive function (p < 0.05). There was an inverted J-shaped association of RHR with MMSE and attention scores. Having RHR ≥ 80 bpm (vs. 60-69 bpm) was significantly associated with the multivariable-adjusted ß coefficients of - 0.58 [95% confidence interval (CI), - 1.00, - 0.16] for MMSE score and - 0.08 (- 0.15, - 0.01) for attention score. In the serum biomarker subsample, RHR was linearly associated with serum interleukin-6 (IL-6) (ß coefficient = 0.19; 95%CI 0.14, 0.24), IL-8 (0.08; 0.02, 0.13), IL-10 (0.09; 0.04, 0.15), tumor necrosis factor-α (0.06; 0.01, 0.11), monocyte chemotactic protein-1 (0.09; 0.04, 0.15), intercellular adhesion molecule-1 (0.16; 0.11, 0.22), and vascular cell adhesion molecule-1 (0.11; 0.06, 0.16). CONCLUSIONS: There is an inverted J-shaped association of RHR with attention and global cognition. Poor cognitive function and high RHR may be linked through systemic low-grade inflammation and endothelial injury.

Plasma Amyloid-ß, Total Tau, and Neurofilament Light Chain Across the Alzheimer's Disease Clinical Spectrum: A Population-Based Study.

BACKGROUND: Plasma biomarkers have emerged as a promising approach for characterizing pathophysiology in mild cognitive impairment (MCI) and Alzheimer's disease (AD). OBJECTIVE: We aimed to characterize plasma biomarkers for AD and neurodegeneration across the AD clinical continuum, and to assess their ability to differentiate between AD, MCI, and normal cognition. METHODS: This population-based study engaged 1,446 rural-dwelling older adults (age ≥60 years, 61.0% women) derived from MIND-China; of these, 402 were defined with MCI and 142 with AD. Plasma amyloid-ß (Aß), total tau (t-tau), and neurofilament light chain (NfL) concentrations were analyzed using the Simoa platform. Data were analyzed using linear and logistic regression models, and receiver operating characteristic (ROC) analysis. RESULTS: Across the AD clinical spectrum, plasma Aß40 and NfL increased, whereas Aß42/Aß40 ratio decreased. Plasma t-tau was higher in people with AD dementia than those with MCI or normal cognition. Plasma NfL outperformed other biomarkers in differentiating AD from normal cognition (area under the ROC curve [AUC] = 0.75), but all plasma biomarkers performed poorly to distinguish MCI from normal cognition (AUC <0.60). Plasma NfL in combination with age, sex, education, and APOE genotype yielded the AUC of 0.87 for differentiating between AD and normal cognition, 0.79 between AD and MCI, and 0.64 between MCI and normal cognition. CONCLUSIONS: In this Chinese population, AD plasma biomarkers vary by age, sex, and APOE genotype. Plasma Aß, t-tau, and NfL differ across the AD clinical spectrum, and plasma NfL appears to be superior to plasma Aß and t-tau for defining the clinical spectrum.

Circ_0001589/miR-1248/HMGB1 axis enhances EMT-mediated metastasis and cisplatin resistance in cervical cancer.

Cervical cancer is the fourth most common malignant tumors in female worldwide. Cirular RNAs (circRNA) represent a new class of regulatory RNA and play a pivotal role in the carcinogenesis and development of tumors. However, their functions have not been fully elucidated in cervical cancer. In this study, we identified an upregulated circRNA, circ_0001589, both in fresh clinical samples and tissue microarray of cervical cancer. Transwell assay and cell apoptosis assay by flow cytometry demonstrated circ_0001589 promotes epithelial-mesenchymal transition (EMT)-mediated cell migration and invasion, and enhanced cisplatin resistance in vitro. In addition, in nude mice model, circ_0001589 increased the number of lung metastases and recovered xenograft growth from cisplatin treatment in vivo. Mechanistically, RNA pull-down assay, RNA immunoprecipitation, and dual-luciferase reporter assay disclosed that circ_0001589 function as an competing endogenous RNA to sponge miR-1248, which directly target the 3' untranslated region of high mobility group box-B1 (HMGB1). Thereby, circ_0001589 upregulated HMGB1 protein expression and accelerate cervical cancer progression. The rescue experiments also revealed that miR-1248 overexpression or HMGB1 knockdown partially reversed the regulatory functions of circ_0001589 on cell migration, invasion, and cisplatin resistance. In summary, our findings suggest the upregulation of circ_0001589 promoted EMT-mediated cell migration and invasion, and enhanced cisplatin resistance via regulating miR-1248/HMGB1 axis in cervical cancer. These results provided new evidence for understanding the carcinogenesis mechanism and finding new therapeutic target for cervical cancer.