Fine-Grained Recognition of Mixed Signals with Geometry Coordinate Attention.

With the advancement of technology, signal modulation types are becoming increasingly diverse and complex. The phenomenon of signal time-frequency overlap during transmission poses significant challenges for the classification and recognition of mixed signals, including poor recognition capabilities and low generality. This paper presents a recognition model for the fine-grained analysis of mixed signal characteristics, proposing a Geometry Coordinate Attention mechanism and introducing a low-rank bilinear pooling module to more effectively extract signal features for classification. The model employs a residual neural network as its backbone architecture and utilizes the Geometry Coordinate Attention mechanism for time-frequency weighted analysis based on information geometry theory. This analysis targets multiple-scale features within the architecture, producing time-frequency weighted features of the signal. These weighted features are further analyzed through a low-rank bilinear pooling module, combined with the backbone features, to achieve fine-grained feature fusion. This results in a fused feature vector for mixed signal classification. Experiments were conducted on a simulated dataset comprising 39,600 mixed-signal time-frequency plots. The model was benchmarked against a baseline using a residual neural network. The experimental outcomes demonstrated an improvement of 9% in the exact match ratio and 5% in the Hamming score. These results indicate that the proposed model significantly enhances the recognition capability and generalizability of mixed signal classification.

Mental health and academic performance of college students: Knowledge in the field of mental health, self-control, and learning in college.

The aim of this research is to analyze the impact of mental health on the academic performance of junior and senior students studying in a university setting during the 2022-2023 academic year, in the post-COVID period. The study was conducted in Beijing, China, with the participation of 600 students, including 300 first-year students and 300 fifth-year students. DASS (Depression, Anxiety, and Stress Scale) and PHQ-9 (Patient Health Questionnaire-9) questionnaires were employed to measure mental health. The DASS assesses symptoms of depression, anxiety, and stress, while the PHQ-9 specifically evaluates depression severity. Academic performance was evaluated using a 12-point scale, which incorporated various criteria such as exam scores, coursework performance, and participation in extracurricular activities. The research was conducted across five faculties of the university from 2022 to 2023. In the study, fifth-year students demonstrated a higher level of mental health compared to first-year students, with an average DASS score of 27.1 and 24.2, respectively. Interestingly, despite this, first-year students achieved higher academic performance indicators, with an average score of 8.2 compared to 9.8 in fifth-year students. Correlation analysis revealed significant associations between stress, depression, and anxiety levels with academic performance (stress: r = -0.25, p < 0.001; depression: r = -0.20, p = 0.003; anxiety: r = -0.18, p = 0.008). These findings highlight the critical importance of addressing students' mental well-being, particularly in later academic years. Recommendations include implementing support programs and developing online resources for students.

Longitudinal albuminuria patterns predict coronary artery calcification progression: Findings from the Coronary Artery Risk Development in Young Adults study.

BACKGROUND AND AIMS: Albuminuria is an established risk factor for adverse cardiovascular outcomes. However, few studies have characterized longitudinal albuminuria patterns based on long-term measurement of urine albumin-to-creatinine ratio (UACR) levels. We aimed to evaluate the association between longitudinal albuminuria patterns in midlife adults and subsequent CAC progression. METHODS: We included 1919 participants with CAC assessment by computed tomography from CARDIA (Coronary Artery Risk Development in Young Adults) study. CAC progression was determined for each individual as the difference of logarithmic CAC scores at follow-up and baseline. Albuminuria patterns across a 10-year span were estimated by longitudinal UACR levels. Multivariable general linear models were used to evaluate the association of long-term albuminuria patterns with CAC progression. RESULTS: Of the 1919 included participants, 583 (30.4 %) participants experienced CAC progression, and the mean (SD) age was 50.4 (3.5) years at year 25. A total of four dynamic albuminuria patterns were identified. After multivariable adjustment, there were significant differences in CAC progression by albuminuria patterns as demonstrated as percent change in CAC with 36.0 % (SE, 1.5) progression for mid- and late-life normoalbuminuria group, 46.0 % (SE, 7.6) for midlife normoalbuminuria and late-life high albuminuria group, 52.4 % (SE, 7.1) for midlife high albuminuria and late-life normoalbuminuria group, and 54.5 % (SE, 8.7) for mid- and late-life high albuminuria group (p = 0.019). Similar findings were also observed in CAC volume score changes. CONCLUSIONS: Longitudinal albuminuria patterns across a 10-year span were associated with worse CAC progression independent of baseline CAC level and albuminuria changes, suggesting that it may provide early identification of high-risk individuals with dynamic rises in albuminuria who may benefit from aggressive risk factor modification.

Baicalin-peptide supramolecular self-assembled nanofibers effectively inhibit ferroptosis and attenuate doxorubicin-induced cardiotoxicity.

Doxorubicin, an anthracycline chemotherapeutic agent, elicits a deleterious cardiotoxicity known as doxorubicin-induced cardiomyopathy (DIC) that circumscribes its chemotherapy utility for malignancies. Recent empirical evidence implicates ferroptosis, an iron-dependent form of regulated cell death, as playing a pivotal role in the pathogenesis of DIC. We postulated that anti-ferroptosis agents may constitute a novel therapeutic strategy for mitigating DIC. To test this hypothesis, we engineered baicalin-peptide supramolecular self-assembled nanofibers designed to selectively target the angiotensin II type I receptor (AT1R), which is upregulated in doxorubicin-damaged cardiomyocytes. This enabled targeted delivery of baicalin, a natural antioxidant compound, to inhibit ferroptosis in the afflicted myocardium. In vitro, the nanofibers ameliorated cardiomyocyte death by attenuating peroxide accumulation and suppressing ferroptosis. In a murine model of DIC, AT1R-targeted baicalin delivery resulted in efficacious cardiac accumulation and superior therapeutic effects compared to systemic administration. This investigation delineates a promising framework for developing targeted therapies that alleviate doxorubicin-induced cardiotoxicity by inhibiting the ferroptosis pathway in cardiomyocytes.

Lonicera japonica Thunb extract ameliorates lipopolysaccharide-induced acute lung injury associated with luteolin-mediated suppression of NF-κB signaling pathway.

OBJECTIVE: Lonicera japonica Thunb (LJT) is a commonly used herbal soup to treat inflammation-related diseases. However, the effect of LJT on ALI is unknown. The present study was aimed at investigating the protective effects of LJT extract (LTE) and its active ingredient luteolin (Lut) on lipopolysaccharide (LPS)-stimulated ALI and investigate its potential mechanism. MATERIALS AND METHODS: The effects of LTE and Lut were explored in an ALI mouse model induced by intraperitoneal injection of lipopolysaccharide (LPS). Besides, the LPS-induced inflammation model in BEAS-2B cells was used to clarify the underlying mechanisms. The ALI pathological changes in lung tissues were tested through Haematoxylin and eosin (HE) staining. The apoptosis of cells in lung tissue and the cell model in vitro was evaluated by TUNEL assays, respectively. Meanwhile, the viability of cells in vitro was evaluated by Cell Counting Kit-8 (CCK-8) assay. The levels/concentrations of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), IL-1ß and IL-10 in BALF were detected by enzyme-linked immunosorbent assay (ELISA). Besides, through quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting, the expression of the above-mentioned inflammatory factors and key factors in the NF-κB signaling pathway was examined. The distribution of inflammatory factors in tissue was observed through immunohistochemistry (IHC) assays . RESULTS: In relative to LPS-stimulated group, the in vivo study showed that LTE and different concentrations of Lut dramatically alleviated LPS-evoked lung pathological injury and lung edema based on the changes in total protein levels and lung wet/dry (W/D) ratio in the bronchoalveolar lavage fluid (BALF) from ALI mice. LTE and different concentrations of Lut also suppressed the inflammatory response, as reflected by the variations of neutrophil accumulation and the production of proinflammatory and anti-inflammatory cytokines in the lung tissues and BALF of ALI mice. The in vitro research also demonstrated that LTE and Lut visibly facilitated cell viability and restrained the apoptosis of BEAS-2B cells stimulated by LPS. Lut hindered LPS-inducible activation of NF-κB pathway in BEAS-2B cells. CONCLUSION: The present study proved that LTE might suppress LPS-induced acute injury and inflammation in mice and BEAS-2B cells through the Lut-caused suppression of NF-κB signal path (Figure 1).