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Mental rotation has emerged as an important predictor for success in science, technology, engineering, and math fields. Previous studies have shown that males and females perform mental rotation tasks differently. However, how the brain functions to support this difference remains poorly understood. Recent advancements in neuroimaging techniques have enabled the identification of sex differences in large-scale brain network connectivity. Using a classic mental rotation task with functional magnetic resonance imaging, the present study investigated whether there are any sex differences in large-scale brain network connectivity for mental rotation performance. Our results revealed that, relative to females, males exhibited less cross-network interaction (i.e. lower inter-network connectivity and participation coefficient) of the visual network but more intra-network integration (i.e. higher intra-network connectivity and local efficiency) and cross-network interaction (i.e. higher inter-network connectivity and participation coefficient) of the salience network. Across all participants, mental rotation performance was negatively correlated with cross-network interaction (i.e. participation coefficient) of the visual network, was positively correlated with cross-network interaction (i.e. inter-network connectivity) of the salience network, and was positively correlated with intra-network integration (i.e. local efficiency) of the somato-motor network. Interestingly, the cross-network integration indexes of both the visual and salience networks significantly mediated sex difference in mental rotation performance. The present findings suggest that large-scale brain network connectivity may constitute an essential neural basis for sex difference in mental rotation, and highlight the importance of considering sex as a research variable in investigating the complex network underpinnings of spatial cognition.
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Background: The long-term prognosis of heart failure with preserved ejection fraction (HFpEF) is influenced by malnutrition. Currently, there's a deficit in objective and comprehensive nutritional assessment methods to evaluate the nutritional status and predicting the long-term outcomes of HFpEF patients. Methods: Our retrospective study included two hundred and eighteen elderly HFpEF patients admitted to the cardiovascular ward at the Air Force Medical Centre from January 2016 to December 2021. Based on follow-up outcomes, patients were categorized into all-cause death (99 cases) and Survival (119 cases) groups. We compared general data, laboratory results, and nutritional indexes between groups. Differences in subgroups based on Triglyceride-Total Cholesterol-Body Weight Index (TCBI), Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), and Controlled Nutrition Score (CONUT) were analyzed using Kaplan-Meier survival curves and log-rank test. COX regression was used to identify all-cause mortality risk factors, and the predictive accuracy of the four nutritional indices was assessed using receiver operating characteristic (ROC) curves and Delong test analysis. Results: A total of 101 (45.41%) HFpEF patients experienced all-cause mortality during 59.02 ± 1.79 months of follow-up. The all-cause mortality group exhibited lower GNRI and PNI levels, and higher CONUT levels than the Survival group (p < 0.05). Kaplan-Meier analysis revealed lower cumulative survival in the low GNRI ( ≤ 96.50) and low PNI ( ≤ 43.75) groups, but higher in the low CONUT ( ≤ 2) group, compared to their respective medium and high-value groups. Multifactorial COX regression identified low PNI ( ≤ 43.75) as an independent all-cause mortality risk factor in elderly HFpEF patients. ROC and Delong's test indicated PNI (area under the curve [AUC] = 0.698, 95% confidence interval [CI] 0.629-0.768) as a more effective predictor of all-cause mortality than TCBI (AUC = 0.533, 95% CI 0.456-0.610) and CONUT (AUC = 0.621, 95% CI 0.547-0.695; p < 0.05). However, there was no significant difference compared to GNRI (AUC = 0.663, 95% CI 0.590-0.735; p > 0.05). Conclusions: In elderly HFpEF patients a PNI ≤ 43.75 was identified as an independent risk factor for all-cause mortality. Moreover, PNI demonstrates superior prognostic performance in predicting all-cause mortality in elderly patients with HFpEF when compared to TCBI, GNRI, and COUNT.
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Background: Accurate detection of atrial fibrillation (AF) recurrence after catheter ablation is crucial. In this study, we aimed to conduct a systematic review of machine-learning-based recurrence detection in the relevant literature. Methods: We conducted a comprehensive search of PubMed, Embase, Cochrane, and Web of Science databases from 1980 to December 31, 2022 to identify studies on prediction models for AF recurrence risk after catheter ablation. We used the prediction model risk of bias assessment tool (PROBAST) to assess the risk of bias, and R4.2.0 for meta-analysis, with subgroup analysis based on model type. Results: After screening, 40 papers were eligible for synthesis. The pooled concordance index (C-index) in the training set was 0.760 (95% confidence interval [CI] 0.739 to 0.781), the sensitivity was 0.74 (95% CI 0.69 to 0.77), and the specificity was 0.76 (95% CI 0.72 to 0.80). The combined C-index in the validation set was 0.787 (95% CI 0.752 to 0.821), the sensitivity was 0.78 (95% CI 0.73 to 0.83), and the specificity was 0.75 (95% CI 0.65 to 0.82). The subgroup analysis revealed no significant difference in the pooled C-index between models constructed based on radiomics features and those based on clinical characteristics. However, radiomics based showed a slightly higher sensitivity (training set: 0.82 vs. 0.71, validation set: 0.83 vs. 0.73). Logistic regression, one of the most common machine learning (ML) methods, exhibited an overall pooled C-index of 0.785 and 0.804 in the training and validation sets, respectively. The Convolutional Neural Networks (CNN) models outperformed these results with an overall pooled C-index of 0.862 and 0.861. Age, radiomics features, left atrial diameter, AF type, and AF duration were identified as the key modeling variables. Conclusions: ML has demonstrated excellent performance in predicting AF recurrence after catheter ablation. Logistic regression (LR) being the most widely used ML algorithm for predicting AF recurrence, also showed high accuracy. The development of risk prediction nomograms for wide application is warranted.
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While pioneering methods have demonstrated that bacterial N-acyl homoserine lactone (AHL) signaling molecules can influence the growth and self-aggregation of suspended microalgae, whether AHLs can affect the initial adhesion to a carrier has remained an open question. Here we revealed that the microalgae exhibited different adhesion potential under AHL mediation, where the performance was affiliated to both AHL types and concentrations. The result can be well explained by the interaction energy theory, where the energy barrier between the carriers and the cells varied due to AHL mediation. Depth analyses revealed that AHL acted through modifying the properties of the surface electron donor of the cells, which were dependent upon three major components, i.e., extracellular protein (PN) secretion, the PN secondary structure, and the PN amino acid composition. These findings expand the known diversity of AHLs mediation on microalgal initial adhesion and metabolisms, which may interface with other major cycles and become helpful to theoretically guide the application of AHLs in microalgal culture and harvesting.
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Acil-Butirolactonas , Microalgas , 4-Butirolactona/química , 4-Butirolactona/metabolismo , Transducción de Señal , BiopelículasRESUMEN
BACKGROUND: Heparin-induced thrombocytopenia (HIT) is immune-mediated thrombotic thrombocytopenia following the use of heparin, which contributes to a high limb-amputation rate and mortality if not appropriately handled. There is growing evidence suggesting that novel oral anticoagulants (NOACs) may be effective for treating HIT. METHODS: We described five rare cases of patients with HIT associated with deep vein thrombosis treated with dabigatran, a member of NOACs. We also reviewed representative cases and literature investigating the use of NOACs to treat patients with HIT to further discuss the efficacy and safety. RESULTS AND CONCLUSIONS: Following the treatment of dabigatran after argatroban, the platelet count of patients with HIT gradually elevated and reached the normal range eventually. There was no incidence of new symptomatic, objectively-confirmed arteriovenous thromboembolism observed within the 90-day-period follow up. The patient in case 3 presented with gastric bleeding after dabigatran treatment and died in the end. The results suggested that dabigatran use after argatroban may be effective in the treatment of patients with HIT. However, safety should be reconsidered since severe complications were observed in case 3.
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Anticoagulantes/efectos adversos , Antitrombinas/uso terapéutico , Arginina/análogos & derivados , Dabigatrán/uso terapéutico , Heparina/efectos adversos , Ácidos Pipecólicos/uso terapéutico , Sulfonamidas/uso terapéutico , Trombocitopenia/inducido químicamente , Trombosis de la Vena/inducido químicamente , Anciano , Antitrombinas/efectos adversos , Arginina/uso terapéutico , Dabigatrán/efectos adversos , Quimioterapia Combinada , Resultado Fatal , Femenino , Hemorragia Gastrointestinal/inducido químicamente , Humanos , Masculino , Persona de Mediana Edad , Recuento de Plaquetas , Trombocitopenia/tratamiento farmacológico , Trombosis de la Vena/tratamiento farmacológicoRESUMEN
OBJECTIVE: A decrease in nitric oxide, leading to vascular smooth muscle cell proliferation, is a common pathological feature of vascular proliferative diseases. Nitric oxide synthesis by eNOS (endothelial nitric oxide synthase) is precisely regulated by protein kinases including AKT1. ENH (enigma homolog protein) is a scaffolding protein for multiple protein kinases, but whether it regulates eNOS activation and vascular remodeling remains unknown. Approach and Results: ENH was upregulated in injured mouse arteries and human atherosclerotic plaques and was associated with coronary artery disease. Neointima formation in carotid arteries, induced by ligation or wire injury, was greatly decreased in endothelium-specific ENH-knockout mice. Vascular ligation reduced AKT and eNOS phosphorylation and nitric oxide production in the endothelium of control but not ENH-knockout mice. ENH was found to interact with AKT1 and its phosphatase PHLPP2 (pleckstrin homology domain and leucine-rich repeat protein phosphatase 2). AKT and eNOS activation were prolonged in VEGF (vascular endothelial growth factor)-induced ENH- or PHLPP2-deficient endothelial cells. Inhibitors of either AKT or eNOS effectively restored ligation-induced neointima formation in ENH-knockout mice. Moreover, endothelium-specific PHLPP2-knockout mice displayed reduced ligation-induced neointima formation. Finally, PHLPP2 was increased in the endothelia of human atherosclerotic plaques and blood cells from patients with coronary artery disease. CONCLUSIONS: ENH forms a complex with AKT1 and its phosphatase PHLPP2 to negatively regulate AKT1 activation in the artery endothelium. AKT1 deactivation, a decrease in nitric oxide generation, and subsequent neointima formation induced by vascular injury are mediated by ENH and PHLPP2. ENH and PHLPP2 are thus new proatherosclerotic factors that could be therapeutically targeted.
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Proteínas Adaptadoras Transductoras de Señales/metabolismo , Traumatismos de las Arterias Carótidas/enzimología , Arteria Carótida Común/enzimología , Proteínas de Microfilamentos/metabolismo , Óxido Nítrico Sintasa de Tipo III/metabolismo , Fosfoproteínas Fosfatasas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Remodelación Vascular , Proteínas Adaptadoras Transductoras de Señales/deficiencia , Proteínas Adaptadoras Transductoras de Señales/genética , Animales , Aterosclerosis/enzimología , Aterosclerosis/patología , Aterosclerosis/fisiopatología , Traumatismos de las Arterias Carótidas/genética , Traumatismos de las Arterias Carótidas/patología , Traumatismos de las Arterias Carótidas/fisiopatología , Arteria Carótida Común/patología , Arteria Carótida Común/fisiopatología , Células Cultivadas , Enfermedad de la Arteria Coronaria/enzimología , Enfermedad de la Arteria Coronaria/patología , Enfermedad de la Arteria Coronaria/fisiopatología , Modelos Animales de Enfermedad , Células Endoteliales de la Vena Umbilical Humana/enzimología , Humanos , Proteínas con Dominio LIM/genética , Proteínas con Dominio LIM/metabolismo , Ratones Endogámicos C57BL , Ratones Noqueados , Proteínas de Microfilamentos/deficiencia , Proteínas de Microfilamentos/genética , Neointima , Óxido Nítrico/metabolismo , Fosfoproteínas Fosfatasas/deficiencia , Fosfoproteínas Fosfatasas/genética , Fosforilación , Transducción de SeñalRESUMEN
To meet the requirements of theranostics with diagnosis and treatment, photodynamic-based therapy is simultaneously enabled with the incorporation of methylene blue (MB) as imaging agent and photosensitizer in core-shell structured drug vehicles. Citrate-modified hydroxyapatite (HAp) powders are first grafted with ß-cyclodextrin (CD), then combined with MB molecules through electrostatic interactions, and finally encapsulated with carbon shells through hydro-thermal carbonization of glucose to prepare HAp-CD-MB@C powders. Processing parameters of carbonization temperature, glucose addition, reaction time and CD addition are varied to prepare drug carriers with modulated crystallite degrees and photo-physical properties. Increased crystallite sizes of HAp are accompanied with the formation of C=O, C=C and C-OH groups in carbon shell, endowing sustainable release behaviors of MB through carbonous structures. High photoluminescence intensities are fairly related with red-shifted vibration peaks of groups in tightly combined MB molecules through hydrogen bonds. This hydrogen bonding effect is significantly increased for HAp-CD-MB@C140 with the splitting of CH3-involved vibration peaks in infrared spectra, which causes increase in photoluminescence intensity and four-fold increase in generation ratio of singlet oxygen. The present studies shed light on preparation of core-shell structured drug carriers, modulation of aggregate states of MB molecules, enhancement of photo-physical properties and improvement of generation ratio of singlet oxygen during photodynamic-based therapy.
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Carbono/química , Hidroxiapatitas/química , Azul de Metileno/química , beta-Ciclodextrinas/química , Cristalización , Portadores de Fármacos/química , Glucosa/química , Enlace de Hidrógeno , Azul de Metileno/metabolismo , Fotoquimioterapia/métodos , Fármacos Fotosensibilizantes/química , Fármacos Fotosensibilizantes/metabolismo , Oxígeno Singlete/química , TemperaturaRESUMEN
BACKGROUND AND AIMS: Serum uric acid (SUA) levels have been reported to be associated with an increased risk of coronary artery disease (CAD) among patients with diabetes in observational study. Whether this relationship is causal remains unclear. The current study aimed to explore the causal association between SUA and the risk of CAD in patients with diabetes. METHODS AND RESULTS: A two-sample Mendelian randomization (MR) approach was employed to evaluate the causal effect of SUA on the risk of CAD in patients with diabetes. A total of 28 single nucleotide polymorphisms (SNPs) related to SUA were identified as instruments. Genetic association with CAD were obtained from a recently published genome-wide association study (GWAS) of 15,666 patients with diabetes (3968 CAD cases and 11,696 controls). The fixed-effects inverse variance-weighted method was employed to estimate the causal effect for the primary analysis, and other robust methods were employed for sensitivity analyses. In addition, the whole analyses were repeated using 9 non-pleiotropic SNPs. Genetic determined SUA levels were not significantly associated with the risk of CAD in patients with diabetes in the primary analysis (odds ratio = 1.13, 95% confidence interval: 0.98-1.16, P = 0.09). Consistent results were observed in the sensitivity analyses using various robust methods. In addition, this finding was confirmed by the repeated analyses using 9 non-pleiotropic SNPs. CONCLUSIONS: This two-sample MR study does not support a causal effect of genetically predicted SUA levels on the risk of CAD in patients with diabetes.
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Enfermedad de la Arteria Coronaria/genética , Diabetes Mellitus/genética , Hiperuricemia/genética , Polimorfismo de Nucleótido Simple , Ácido Úrico/sangre , Biomarcadores/sangre , Estudios de Casos y Controles , Enfermedad de la Arteria Coronaria/diagnóstico , Diabetes Mellitus/diagnóstico , Estudio de Asociación del Genoma Completo , Humanos , Hiperuricemia/sangre , Hiperuricemia/complicaciones , Hiperuricemia/diagnóstico , Análisis de la Aleatorización Mendeliana , Medición de Riesgo , Factores de Riesgo , Regulación hacia ArribaRESUMEN
BACKGROUND: To investigate the causal association between serum 25-hydroxyvitamin D (25OHD), calcium (Ca), and parathyroid hormone (PTH) levels and the risk of coronary artery disease (CAD) in patients with diabetes using a Mendelian randomization approach. METHODS: Genetic signatures associated with serum 25OHD, Ca, and PTH levels were extracted from recently published genome-wide association study (GWAS), including 79,366, 39,400, 29,155 individuals, respectively. Genetic association estimates for CAD in patients with diabetes were obtained from a GWAS of 15,666 individuals with diabetes (3,968 CAD cases, 11,696 controls). The inverse-variance-weighted method was employed for the primary analysis, and other robust methods were applied for sensitivity analyses. RESULTS: Six, seven and five single nucleotide polymorphisms were identified as instrumental variables for serum 25OHD, Ca and PTH levels, respectively. There was no significant association between genetically predicted serum 25OHD levels and the risk of CAD in patients with diabetes (odds ratio (OR) = 1.04, 95% confidence interval (CI): 0.58 - 1.87, P = 0.888). Similarly, genetically predicted serum Ca (OR = 1.83, 95% CI: 0.62 - 5.35, P = 0.273) and PTH levels (OR = 1.27, 95% CI: 0.67 - 2.44, P = 0.464) were not significantly associated with the risk of CAD in patients with diabetes. These findings were robust in sensitivity analyses. CONCLUSIONS/INTERPRETATION: Serum 25OHD, Ca and PTH levels may not be causally associated with the risk of CAD in patients with diabetes.
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Enfermedad de la Arteria Coronaria , Diabetes Mellitus , Calcio , Enfermedad de la Arteria Coronaria/genética , Estudio de Asociación del Genoma Completo , Humanos , Análisis de la Aleatorización Mendeliana , Hormona Paratiroidea , Factores de Riesgo , Vitamina D/análogos & derivadosRESUMEN
Background: This systematic review and meta-analysis aimed to explore the effects of different sodium-glucose cotransporter-2 inhibitors (SGLT2i) on prognosis and cardiac structural remodeling in patients with heart failure (HF). Methods: Relevant studies published up to 20 March 2024 were retrieved from PubMed, EMBASE, Web of Science, and Cochrane Library CNKI, China Biomedical Literature Service, VIP, and WanFang databases. We included randomized controlled trials of different SGLT2i and pooled the prognosis data of patients with HF. We compared the efficacy of different SGLT2i in patients with HF and conducted a sub-analysis based on left ventricular ejection fraction (LVEF). Results: We identified 77 randomized controlled trials involving 43,561 patients. The results showed that SGLT2i significantly enhanced outcomes in HF, including a composite of hospitalizations for HF and cardiovascular death, individual hospitalizations for HF, Kansas City Cardiomyopathy Questionnaire (KCCQ) scores, left atrial volume index (LAVi), and LVEF among all HF patients (P < 0.05) compared to a placebo. Sotagliflozin was superior to empagliflozin [RR = 0.88, CI (0.79-0.97)] and dapagliflozin [RR = 0.86, CI (0.77-0.96)] in reducing hospitalizations for HF and CV death. Dapagliflozin significantly reduced hospitalizations [RR = 0.51, CI (0.33-0.80)], CV death [RR = 0.73, CI (0.54-0.97)], and all-cause mortality [RR = 0.69, CI (0.48-0.99)] in patients with HF with reduced ejection fraction (HFrEF). SGLT2i also plays a significant role in improving cardiac remodeling and quality of life (LVMi, LVEDV, KCQQ) (P < 0.05). Among patients with HF with preserved ejection fraction (HFpEF), SGLT2i significantly improved cardiac function in HFpEF patients (P < 0.05). In addition, canagliflozin [RR = 0.09, CI (0.01-0.86)] demonstrated greater safety compared to sotagliflozin in a composite of urinary and reproductive infections of HFpEF patients. Conclusion: Our systematic review showed that SGLT2i generally enhances the prognosis of patients with HF. Sotagliflozin demonstrated superiority over empagliflozin and dapagliflozin in a composite of hospitalization for HF and CV death in the overall HF patients. Canagliflozin exhibited greater safety compared to sotagliflozin in a composite of urinary and reproductive infections of HFpEF. Overall, the efficacy of SGLT2i was greater in HFrEF patients than in HFpEF patients.
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Stereo matching cost constrains the consistency between pixel pairs. However, the consistency constraint becomes unreliable in ill-posed regions such as occluded or ambiguous regions of the images, making it difficult to explore hidden correspondences. To address this challenge, we introduce an Error-area Feature Refinement Mechanism (EFR) that supplies context features for ill-posed regions. In EFR, we innovatively obtain the suspected error region according to aggregation perturbations, then a simple Transformer module is designed to synthesize global context and correspondence relation with the identified error mask. To better overcome existing texture overfitting, we put forward a Dual-constraint Cost Volume (DCV) that integrates supplementary constraints. This effectively improves the robustness and diversity of disparity clues, resulting in enhanced details and structural accuracy. Finally, we propose a highly accurate stereo matching network called Error-rectify Feature Guided Stereo Matching Network (ERCNet), which is based on DCV and EFR. We evaluate our model on several benchmark datasets, achieving state-of-the-art performance and demonstrating excellent generalization across datasets. The code is available at https://github.com/dean7liu/ERCNet_2023.
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Algoritmos , Redes Neurales de la Computación , Procesamiento de Imagen Asistido por Computador/métodos , Humanos , Reconocimiento de Normas Patrones Automatizadas/métodosRESUMEN
The objective of this study was to evaluate the predictive value of the Geriatric Nutritional Risk Index (GNRI) combined with the Systemic Immunoinflammatory Index (SII) for the risk of major adverse cardiovascular events (MACE) following percutaneous coronary intervention in elderly patients with acute coronary syndrome (ACS). We retrospectively reviewed the medical records of 1202 elderly patients with acute coronary syndromes divided into MACE and non-MACE groups according to whether they had a MACE. The sensitivity analysis utilized advanced machine learning algorithms to preliminarily identify the critical role of GNRI versus SII in predicting MACE risk. We conducted a detailed analysis using a restricted cubic spline approach to investigate the nonlinear relationship between GNRI, SII, and MACE risk further. We constructed a clinical prediction model based on three key factors: GNRI, SII, and Age. To validate the accuracy and usefulness of this model, we compared it to the widely used GRACE score using subject work and recall curves. Additionally, we compared the predictive value of models and GRACE scores in assessing the risk of MACE using the Integrated Discriminant Improvement Index (IDI) and the Net Reclassification Index (NRI). This study included 827 patients. The GNRI scores were lower in the MACE group than in the non-MACE group, while the SII scores were higher in the MACE group (P < 0.001). The multifactorial analysis revealed a low GNRI (OR = 2.863, 95% CI: 2.026-4.047, P = 0.001), High SII (OR = 3.102, 95% CI: 2.213-4.348, P = 0.001). The area under the curve (AUC) for the predictive model was 0.778 (95% CI: 0.744-0.813, P = 0.001), while the AUC for the GRACE score was 0.744 (95% CI: 0.708-0.779, P = 0.001). NRI was calculated to be 0.5569, with NRI + at 0.1860 and NRI- at 0.3708. The IDI was found to be 0.0571, with a P-value of less than 0.001. These results suggest that the newly developed prediction model is more suitable for use with the population in this study than the GRACE score. The model constructed using GNRI and SII demonstrated good standardization and clinical impact, as evidenced by the standard, DCA, and clinical impact curves. The study shows that combining GNRI and SII can be a simple, cost-effective, and valuable way to predict the risk of MACE within one year in elderly acute coronary syndromes.
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Síndrome Coronario Agudo , Intervención Coronaria Percutánea , Humanos , Anciano , Síndrome Coronario Agudo/diagnóstico , Síndrome Coronario Agudo/etiología , Pronóstico , Estudios Retrospectivos , Modelos Estadísticos , Intervención Coronaria Percutánea/efectos adversos , Medición de RiesgoRESUMEN
Deep vein thrombosis (DVT) is a life-threatening condition that can lead to its sequelae pulmonary embolism (PE) or post-thrombotic syndrome (PTS). Murine models of DVT are frequently used in early-stage disease research and to assess potential therapies. This creates the need for the reliable and easy quantification of blood clots. In this paper, we present a novel high-frequency 3D ultrasound approach for the quantitative evaluation of the volume of DVT in an in vitro model and an in vivo murine model. The proposed method involves the use of a high-resolution ultrasound acquisition system and semiautomatic segmentation of the clot. The measured 3D volume of blood clots was validated to be correlated with in vitro blood clot weights with an R2 of 0.89. Additionally, the method was confirmed with an R2 of 0.91 in the in vivo mouse model with a cylindrical volume from macroscopic measurement. We anticipate that the proposed method will be useful in pharmacological or therapeutic studies in murine models of DVT.
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This study explores the potential of green digital finance and green agricultural growth to contribute to the green economic recovery of the BRICS economies. We examine the relationship between these variables using empirical data and various statistical techniques, including vector error correction, co-integration, unit root tests and long-run analysis. Our results suggest that well-functioning financial institutions play a crucial role in facilitating the structural transformation of green digital finance and promoting green agricultural growth to achieve green economic recovery in the BRICS region. Our findings underscore the need for pro-financial and green economic development policies and institutions to support and enhance economic recovery. Our results are robust and supported by our study. We also suggest future research directions for stakeholders interested in promoting sustainable economic growth in the BRICS countries.
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Agricultura , Desarrollo Económico , Políticas , Crecimiento Sostenible , ChinaRESUMEN
Background: Recently, identifying the psychological mechanism of college students' loneliness has attracted wide attention because the maladjustment caused by college students' loneliness is increasingly common. This study explored the relationship and potential mechanism between college students' neuroticism and loneliness in a large sample. Methods: A total of 4,600 college students completed the Big Five Personality Scale, Loneliness Scale, Self-efficacy Scale and Social Avoidance and Distress Scale. Results: By examining the chain mediating roles of self-efficacy, social avoidance and distress (SAD) in the relation between neuroticism and loneliness, the present study found that college students' neuroticism was positively associated with loneliness via self-efficacy and SAD, respectively, and sequentially. Conclusions: The results suggest a significant positive association between neuroticism and loneliness, which is influenced by the mediating effects of both self-efficacy and social avoidance and distress (SAD), as well as the chained mediating effects of self-efficacy and SAD.
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Background: Previous observational studies have shown an association between smoking and coronary artery disease (CAD) in patients with diabetes. Whether this association reflects causality remains unestablished. This study aimed to explore the causal effect of smoking on CAD in patients with diabetes. Methods: Genetic signatures for smoking were extracted from a large genome-wide association study (GWAS), consisted of up to 1.2 million participants. Four smoking phenotypes were included: smoking initiation, cigarettes per day, age at initiation of regular smoking, and smoking cessation. Genetic associations with CAD in patients with diabetes were extracted from another GWAS, which included 15,666 participants (3,968 CAD cases and 11,696 controls). The analyses were performed using the univariable and multivariable Mendelian randomization (MR) method. Results: MR analysis revealed that smoking initiation was positively related to CAD risk in patients with diabetes (OR = 1.322, 95% CI = 1.114 - 1.568, P = 0.001), but this association was attenuated when adjusted for cardiovascular risk factors (OR = 1.212, 95% CI = 1.008 - 1.457, P = 0.041). Age at initiation of regular smoking was negatively related to CAD in patients with diabetes (OR = 0.214, 95% CI = 0.070 - 0.656, P = 0.007), but this association became insignificant when adjusted for cardiovascular risk factors. Conclusions: This study supported the effect of smoking initiation on the risk of CAD in patients with diabetes.
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Enfermedad de la Arteria Coronaria , Diabetes Mellitus , Humanos , Enfermedad de la Arteria Coronaria/epidemiología , Enfermedad de la Arteria Coronaria/genética , Factores de Riesgo , Fumar/efectos adversos , Análisis de la Aleatorización Mendeliana , Estudio de Asociación del Genoma Completo , Diabetes Mellitus/epidemiología , Diabetes Mellitus/genéticaRESUMEN
Radionuclide drug conjugates (RDCs) with antibodies serve as a novel approach for the treatment of malignant tumors including glioblastoma. However, RDCs require optimal antibodies to work efficiently. Hu4G4, a novel B7-H3-targeting humanized monoclonal IgG1 antibody, is highly specific for the human B7-H3 protein (a marker of tumor cells, including glioblastoma cells). Herein, we established 131I-labeled hu4G4 (131I-hu4G4) and showed that it specifically bound to B7-H3 with high affinity (Kd = 0.99 ± 0.07 nM) and inhibited the growth of U87 cells in vitro. 131I-hu4G4 displayed potent in situ antitumor activity in a mouse model of glioma based on GL261 Red-Fluc-B7-H3 cells. More importantly, 131I-hu4G4 remodeled the tumor microenvironment and promoted the transformation of glioma from "cold" to "hot" tumors by promoting CD4+ and CD8+ T cell infiltration and the polarization of M2 to M1. Therefore, the antitumor activity observed with 131I-hu4G4, together with its ability to enhance antitumor immune responses, makes it a novel candidate for radioimmunotherapy of glioblastoma.
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Glioblastoma , Glioma , Humanos , Animales , Ratones , Glioblastoma/radioterapia , Microambiente Tumoral , Radioinmunoterapia , Glioma/radioterapia , Anticuerpos Monoclonales HumanizadosRESUMEN
Abdominal aortic aneurysm (AAA) is a permanent, asymptomatic segmental dilatation of the abdominal aorta, with a high mortality risk upon rupture. Identification of potential key genes and pathways may help to develop curative drugs for AAA. We conducted RNA-seq on abdominal aortic tissues from both AAA patients and normal individuals as a control group. Integrated bioinformatic analysis was subsequently performed to comprehensively reveal potential key genes and pathways. A total of 1148 differential expressed genes (DEGs) (631 up-regulated and 517 down-regulated) were identified in our study. Gene Ontology (GO) analysis revealed enrichment in terms related to extracellular matrix organization, while KEGG analysis indicated enrichment in hematopoietic cell lineage and ECM-receptor interaction. Protein-protein interaction (PPI) network analysis revealed several candidate key genes, and differential expression of 6 key genes (CXCL8, CCL2, PTGS2, SELL, CCR7, and CXCL1) was validated by Gene Expression Omnibus (GEO) datasets. Receiver operating characteristic curve (ROC) analysis demonstrated these genes' high discriminatory ability between AAA and normal tissues. Immunohistochemistry indicated that several key genes were highly expressed in AAA tissues. Single-cell RNA sequencing revealed differential distribution patterns of these identified key genes among various cell types. 26 potential drugs linked to our key genes were found through DGIdb. Overall, our study provides a comprehensive evaluation of potential key genes and pathways in AAA, which could pave the way for the development of curative pharmacological therapies.
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To determine the most appropriate nutritional assessment tool for predicting the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI from four nutritional assessment tools including PNI, GNRI, CONUT, and BMI. Consecutive cases diagnosed with acute coronary syndrome (ACS) and underwent percutaneous coronary intervention (PCI) in the Department of Cardiovascular Medicine of the Air force characteristic medical center from 1 January 2020 to 1 April 2022 were retrospectively collected. The basic clinical characteristics and relevant test and examination indexes were collected uniformly, and the cases were divided into the MACE group (174 cases) and the non-MACE group (372 cases) according to whether a major adverse cardiovascular event (MACE) had occurred within 1 year. Predictive models were constructed to assess the nutritional status of patients with the Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI), Controlling nutritional status (CONUT) scores, and Body Mass Index (BMI), respectively, and to analyze their relationship with prognosis. The incremental value of the four nutritional assessment tools in predicting risk was compared using the Integrated Discriminant Improvement (IDI) and the net reclassification improvement (NRI). The predictive effect of each model on the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI was assessed using area under the ROC curve (AUC), calibration curves, decision analysis curves, and clinical impact curves; comparative analyses were performed. Among the four nutritional assessment tools, the area under the curve (AUC) was significantly higher for the PNI (AUC: 0.798, 95%CI 0.755-0.840 P < 0.001) and GNRI (AUC: 0.760, 95%CI 0.715-0.804 P < 0.001) than for the CONUT (AUC: 0.719,95%CI 0.673-0.765 P < 0.001) and BMI (AUC: 0.576, 95%CI 0.522-0.630 P < 0.001). The positive predictive value (PPV) of PNI: 67.67% was better than GNRI, CONUT, and BMI, and the negative predictive value (NPV): of 83.90% was better than CONUT and BMI and similar to the NPV of GNRI. The PNI, GNRI, and CONUT were compared with BMI, respectively. The PNI had the most significant improvement in the Integrated Discriminant Improvement Index (IDI) (IDI: 0.1732, P < 0.001); the PNI also had the most significant improvement in the Net Reclassification Index (NRI) (NRI: 0.8185, P < 0.001). In addition, of the four nutritional assessment tools used in this study, the PNI was more appropriate for predicting the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI.