Search

Objective·To evaluate the changes in cognitive function in overweight and obese adolescents, and explore the association between cognitive function and fibroblast growth factor 21 (FGF21).Methods·A total of 175 adolescents from a senior high school in Shanghai were divided into normal weight group (n=50), overweight group (n=50) and obese group (n=75) based on their body mass index (BMI). General information, anthropometric data and laboratory testing indicators of the adolescents were collected and compared. The cognitive function of the three groups of adolescents was assessed by using the accuracy (ACC) and reaction time of Flanker task and n-back task. Enzyme-linked immunosorbent assay (ELISA) was used to detect the serum FGF21 level of the three groups of adolescents. Partial correlation analysis and multiple linear regression model were used to evaluate the correlation between cognitive task performance and anthropometric data and laboratory testing indicators.Results·Compared with the normal weight group, systolic blood pressure, diastolic blood pressure, and the levels of fasting plasma glucose, glycosylated hemoglobin and triacylglycerol in the obese group were higher (all P

Photothermal therapy (PTT) is a promising cancer therapy modality with significant advantages such as precise targeting, convenient drug delivery, better efficacy, and minimal adverse effects. Photothermal therapy effectively absorbs the photothermal transducers in the near-infrared region (NIR), which induces the photothermal effect to work. Although PTT has a better role in tumor therapy, it also suffers from low photothermal conversion efficiency, biosafety, and incomplete tumor elimination. Therefore, the use of nanomaterials themselves as photosensitizers, the targeted modification of nanomaterials to improve targeting efficiency, or the combined use of nanomaterials with other therapies can improve the therapeutic effects and reduce side effects. Notably, noble metal nanomaterials have attracted much attention in PTT because they have strong surface plasmon resonance and an effective absorbance light at specific near-infrared wavelengths. Therefore, they can be used as excellent photosensitizers to mediate photothermal conversion and improve its efficiency. This paper provides a comprehensive review of the key role played by noble metal nanomaterials in tumor photothermal therapy. It also describes the major challenges encountered during the implementation of photothermal therapy. [ABSTRACT FROM AUTHOR]

Sonodynamic therapy (SDT) has attracted significant attention in recent years as it is an innovative approach to tumor treatment. It involves the utilization of sound waves or ultrasound (US) to activate acoustic sensitizers, enabling targeted drug release for precise tumor treatment. This review aims to provide a comprehensive overview of SDT, encompassing its underlying principles and therapeutic mechanisms, the applications of nanomaterials, and potential synergies with combination therapies. The review begins by introducing the fundamental principle of SDT and delving into the intricate mechanisms through which it facilitates tumor treatment. A detailed analysis is presented, outlining how SDT effectively destroys tumor cells by modulating drug release mechanisms. Subsequently, this review explores the diverse range of nanomaterials utilized in SDT applications and highlights their specific contributions to enhancing treatment outcomes. Furthermore, the potential to combine SDT with other therapeutic modalities such as photothermal therapy (PTT) and chemotherapy is discussed. These combined approaches aim to synergistically improve therapeutic efficacy while mitigating side effects. In conclusion, SDT emerges as a promising frontier in tumor treatment that offers personalized and effective treatment options with the potential to revolutionize patient care. As research progresses, SDT is poised to play a pivotal role in shaping the future landscape of oncology by providing patients with a broader spectrum of efficacious and tailored treatment options. [ABSTRACT FROM AUTHOR]

Against the background of climate warming, marine heatwaves (MHWs) and terrestrial drought events have become increasingly frequent in recent decades. However, the combined effects of MHWs and terrestrial drought on CO2 uptake in marginal seas are still unclear. The East China Sea (ECS) experienced an intense and long-lasting MHW accompanied by an extreme terrestrial drought in the Changjiang basin in the summer of 2022. In this study, we employed multi-source satellite remote sensing products to reveal the patterns, magnitude, and potential drivers of CO2 flux changes in the ECS resulting from the compounding MHW and terrestrial drought extremes. The CO2 uptake of the ECS reduced by 17.0% (1.06 Tg C) in the latter half of 2022 and the Changjiang River plume region shifted from a CO2 sink to a source (releasing 0.11 Tg C) in July-September. In the majority of the ECS, the positive sea surface temperature (SST) anomaly during the MHW diminished the solubility of CO2 in seawater, thereby reducing CO2 uptake. Moreover, the reduction in nutrient input associated with terrestrial drought, which is unfavorable to phytoplankton growth, further reduced the capacity of CO2 uptake. Meanwhile, the CO2 sink doubled for the offshore waters of the ECS continental shelf in July-September 2022, indicating the complexity and heterogeneity of the impacts of extreme climatic events in marginal seas. This study is of great significance in improving the estimation results of CO2 fluxes in marginal seas and understanding sea–air CO2 exchanges against the background of global climate change. [ABSTRACT FROM AUTHOR]

Against the backdrop of global warming, extreme precipitation events have become more frequent. In complex terrain regions, due to the vulnerability of their ecosystems, extreme precipitation events can lead to significant secondary disasters. Utilizing daily rainfall data from the National Meteorological Information Center of China and statistical analysis, this study explores the spatial and temporal distribution of extreme precipitation in the Central Southwest China (CSC) region. The temporal pattern of extreme precipitation in CSC shows a consistent trend, while the spatial distribution reveals an opposite phase between the northern and southern parts of CSC. Based on this, we propose a new method for constructing extreme precipitation prediction models for complex terrain regions based on physical mechanisms, and take CSC area as a study case. Instead of anonymous feature selection, this method improves the accuracy and stability of the model by studying the impact of sea–air interactions on extreme precipitation and then introducing it into deep learning. It was found that the sea surface temperature (SST) anomaly in the South Indian Ocean affects extreme precipitation in the CSC by influencing uplift, atmospheric instability, and moisture. The SST anomaly also affects the intensity of cross-equatorial airflow, which changes the trajectory of the Pacific–Japan teleconnection wave and impacts extreme precipitation. These findings provide a comprehensive and reliable approach for forecasting extreme precipitation in CSC and are further integrated into the extreme precipitation prediction models. [ABSTRACT FROM AUTHOR]

The spatiotemporal variations in suspended sediment concentration (SSC) in the lower reaches of the Yellow River exhibit significant variability and are influenced by reservoir operations. Understanding the spatiotemporal distribution characteristics of SSC in water holds crucial implications for environmental protection and reservoir operation management. Based on daily-scale SSC monitoring data from four hydrological stations in the lower Yellow River, this study established an SSC remote sensing model applicable to Landsat series satellite data. The independent variable of the model, Rrs(NIR)/(Rrs(G) + Rrs(R) + Rrs(SWIR)), demonstrated sensitivity to water bodies with different SSC values. Distinctive spatiotemporal characteristics in sediment transport were observed across the lower Yellow River. Spatially, the SSC values in the Sanmenxia and Xiaolangdi reservoirs were notably lower than those in other river sections, averaging 1008.42 ± 602.83 mg/L and 1177.89 ± 627.95 mg/L, respectively. Over time, the majority of the river sections (96%) exhibited decreasing trends in SSC during 1984–2022, particularly in the downstream Xiaolangdi reservoir, with average SSC values of 4265.58 ± 1101.77 mg/L in the 1980s and 1840.80 ± 2255.15 mg/L in the 2020s. Seasonal variations in SSC were prominent, with higher summer concentrations, averaging 5536.43 ± 2188.77 mg/L (2020s summer) and 814.11 ± 158.27 mg/L (2020s winter). Reductions in SSC during 1984–2022 primarily occurred in summer, weakening its seasonal variability in the lower Yellow River. Water discharge emerged as a critical factor influencing suspended sediment transport, with SSC increasing in high-water-flow months. Following the construction of the Xiaolangdi reservoir, the relationship between SSC and water discharge at different stations underwent notable alterations. This study enhances our understanding of the spatiotemporal dynamics of suspended sediment transport in the lower Yellow River, providing valuable insights for utilizing long-term Landsat series data in the dynamic monitoring of river sediment transport. [ABSTRACT FROM AUTHOR]

Sensitive high‐energy photon detection from UV to X‐ray and high‐resolution array imaging are critical for medical diagnosis, space exploration, and scientific research. The key challenges for high‐performance photodetector and imaging arrays are the effective material and device design strategies for the miniaturization and integration of the device. Here, photon‐controlled diodes (i.e., the detector has rectifying characteristics only under light irradiation) are proposed for high‐resolution and anti‐crosstalk array imaging applications without integrating the switching element. Based on ultra‐wide bandgap semiconductor Ga2O3, the sensitive DUV/X‐ray photon‐controlled diodes are realized by the design of high‐resistance Ga2O3 film and high‐barrier contact. The device exhibits remarkable detection performance, including high photo‐responsivity (168 A W−1) and specific detectivity (1.45 × 1015 Jones) under DUV illumination, as well as a high sensitivity (1.23 × 105 µC Gyair−1 cm−2) under X‐ray light. Moreover, the low dark current and excellent rectification characteristics are obtained. Furthermore, its potential for high‐density and anti‐crosstalk array imaging applications is verified. These results not only bring forth new insights in the implementation of high‐performance DUV/X‐ray photodetector, but also pave a feasible way to realize high pixel density detector array through the simplified fabrication process for high‐resolution imaging applications. [ABSTRACT FROM AUTHOR]

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P < 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P < 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening., (© 2024. The Author(s).)