Search

Background Understanding the burden of cervical cancer (CC) in young women aged 15–44 years old are essential for formulating effective preventive strategies. Methods Utilizing the Global Burden of Disease 2019 Study, we estimated incidence, disability-adjusted life-years (DALYs), years of life lost (YLLs) and years lived with disability (YLDs) due to CC among young women from 1990 to 2019. Additionally, we evaluated the temporal trends using estimated annual percentage changes (EAPCs) during this period. We conducted a decomposition analysis to assess the absolute contributions of three components: population growth, population age structure and epidemiologic changes. Results Globally, there were 187 609.22 incident cases of CC worldwide, resulting in 2621 917.39 DALYs in 2019. From1990 to 2019, the age-standardized rates were decline, only the age-standardized YLDs rate (EAPC = 0.02; 95% CI: −0.02 to 0.05) showed a stable trend. The largest increase in age-standardized incidence rate (ASIR) and age-standardized YLDs rate observed in the high-middle social demographic index (SDI) quintiles. Population growth and age structure changes were associated with substantial changes in cases of CC, especially in South Asia and East Asia. Conclusions Globally, the burden of CC in young women continues to increase, as measured by the absolute number. As populations are growing and age structure changes were associated with substantial changes in cases of CC, governments will face increasing demand for treatment, and support services for CC, especially in South Asia and East Asia. [ABSTRACT FROM AUTHOR]

Co-N-CDs-based MXene nanocomposites (MXene@PDA/Co-N-CDs) were constructed by decorating Co-N-CDs on polydopamine-functionalized MXene nanosheets. Both Co-N-CDs and MXene nanosheets have peroxidase-like activity; when the two materials are combined to form MXene@PDA/Co-N-CDs nanocomposites, the peroxide-like activity can be further enhanced. MXene@PDA/Co-N-CDs could oxidize the substrate 3,3′5,5′-tetramethylbenziline (TMB) to form ox-TMB, as confirmed by detecting the absorption of the blue products. A highly selective colorimetric biosensor was developed for the determination of glutathione (GSH) in the concentration range of 0.3 to 20 µM with a lower detection limit (LOD) of 0.12 µM, which realized the accurate detection of GSH in human serum and urine samples. Moreover, in the tumor microenvironment, MXene@PDA/Co-N-CDs could catalyze hydrogen peroxide to produce hydroxyl free radicals and produce a photothermal effect under the exposure of NIR-I irradiation. The catalytic activity of MXene@PDA/Co-N-CD nanocomposites was fully achieved for the death of cancer cells through photothermal/photodynamic synergistic therapy. The MXene@PDA/Co-N-CDs nanozyme offers multiple applications in GSH detection and tumor therapy. [ABSTRACT FROM AUTHOR]

Cuelure, an effective lure specifically targeting Tephritid fruit flies, has been widely adopted and applied in the monitoring and control of these pests, providing significant support for agricultural pest management. However, its uncontrollable release speed and duration usually lead to a lot of waste, diminishing its effectiveness and increasing the cost of pest control. In order to solve these problems, we focused on Zeugodacus cucurbitae Coquillett and developed a temperature-sensitive nano-controlled release agent for cuelure. The release rate of this agent can be adjusted by adjusting the ambient temperature. The results show that the temperature-sensitive cuelure nano-controlled release agent demonstrates remarkable temperature-responsive controlled release characteristics. It still exhibits exceptional stability even after being subjected to high-temperature treatment at 60 °C for a week, and the trapping efficiency of this attractant remains between 73% and 75%. This study not only holds immense practical value in monitoring, warning, and managing of fruit fly pests, but it also lays a novel theoretical foundation for the development of insect attractants. [ABSTRACT FROM AUTHOR]

Simple Summary: Exposure to short-term high temperatures of 45 °C can enhance the development and reproduction of Zeugodacus cucurbitae (Coquillett). In this study, the function of the ZcVg3 gene in reproduction was studied by interfering with its expression via the injection of siRNA. The silencing of the ZcVg3 gene could affect the expression of other related genes. It also resulted in a significant reduction in egg production, spawning days, ovarian development and lifespan. The results suggest that the ZcVg3 gene plays a crucial role in pest reproduction under short-term high temperatures. Zeugodacus cucurbitae (Coquillett) is a significant pest affecting fruit and vegetables in tropical and subtropical regions, and its development and reproduction are enhanced after exposure to short-term high-temperature stress at 45 °C. Vitellogenin (Vg) is an essential precursor of yolk protein formation in eggs and plays a vital role in the ovarian development of insects. Interfering with the Z. cucurbitae vitellogenin receptor (ZcVgR) gene in short-term high-temperature conditions decreases the fecundity of female adults, while the transcription level of the ZcVg3 gene increases. To elucidate the reproductive function of the ZcVg3 gene and the synergistic relationship among the ZcVgs genes under short-term high temperatures, this study injected siRNA to interfere with the ZcVg3 gene after subjecting Z. cucurbitae to a 1 h treatment at 45 °C and 25 °C. The expression of the ZcVg3 gene was suppressed, leading to the upregulation of the ZcVg1 and ZcVg2 genes, and the expression of the ZcVgR gene was initially decreased and then increased. Silencing the ZcVg3 gene after a 1 h treatment at 45 °C resulted in a reduction of approximately 84.7% and 75.9% in the fecundity and spawning days of female adults compared to the control. The development rate of their ovaries and the ovarian diameter significantly decreased, and their lifespan was reduced by 71%. The ZcVg3 gene plays a crucial role in the reproduction of Z. cucurbitae in short-term high-temperature conditions. The results of this study provide potential targets for the development of RNAi-based techniques for the control of Z. cucurbitae. [ABSTRACT FROM AUTHOR]

The iron and steel industry puts considerable pressure on the regional environment of the Beijing-Tianjin-Hebei (BTH) area, and the PM2.5 pollution has caused serious harm to public health. To explore a detailed and high-resolution emission inventory of the iron and steel industry in the BTH region, a classification technology method with CAMx modelling system was developed and applied for classifying all the iron and steel enterprises in the BTH region. Besides, simulation scenarios were designed particularly for quantitatively assessing the effectiveness of the environmental protection measures. Results show that the pollutant emission of the iron and steel industry significantly contributes to the PM2.5, SO42-, NO3-, and SOA concentrations in the atmospheric environment in sub-areas. Therefore, the enterprises in western and central sub-areas show high classification coefficients. Restricting pollutant emissions using the developed classification technology method is more effective in reducing the PM2.5 concentration of the BTH region compared with the proportional reduction method. Thus, the classification method should be primarily implemented for reducing the air pollutant emissions of the iron and steel industry in the BTH region.

As the growth of society and the continuous upgrading of people's living standards increase, people's requirements for indoor environment are also increasing. To optimize the ventilation methods inside buildings, a numerical simulation method was used to construct numerical simulations of airflow organization and aerosol diffusion, and based on this model, better ventilation methods were determined. To optimize the determined better ventilation method, a multi-constraint optimization model was constructed using infection probability, thermal comfort, energy utilization coefficient, and velocity non-uniformity coefficient. The ventilation method was optimized through multi-objective constraints. To solve the optimization model, an optimized particle swarm algorithm was studied and designed. The results showed that under the "air rain" flow field, the maximum values of aerosol particles at the human body, bed surface, and outlet were 171, 769, and 19,973, respectively, while the minimum values were 4, 169, and 2197, respectively. The "air rain" flow field is a better ventilation method. The maximum and minimum values of the original non-uniformity coefficient were 0.44 and 0.08, respectively. After optimization by the particle swarm optimization algorithm, the maximum and minimum predicted non-uniformity coefficients were 0.457 and 0.08, respectively. The original value and predicted value are very close. The numerical model and algorithm constructed by the research institute are effective. The algorithm designed by the research institute can provide technical support for multi-objective optimization of indoor ventilation methods. [ABSTRACT FROM AUTHOR]

Gonadotropin-releasing hormone (GnRH) is secreted in brief pulses from the hypothalamus and regulates follicle-stimulating hormone β-subunit (FSHβ) gene expression in pituitary gonadotropes in a frequency-sensitive manner. The mechanisms underlying its preferential and paradoxical induction of FSHβ by low frequency GnRH pulses are incompletely understood. Here, we identify growth differentiation factor 9 (GDF9) as a GnRH-suppressed autocrine inducer of FSHβ gene expression. GDF9 gene transcription and expression were preferentially decreased by high frequency GnRH pulses. GnRH regulation of GDF9 was concentration-dependent and involved ERK and PKA. GDF9 knockdown or immunoneutralization reduced FSHβ mRNA expression. Conversely, exogenous GDF9 induced FSHβ expression in immortalized gonadotropes and in mouse primary pituitary cells. GDF9 exposure increased FSH secretion in rat primary pituitary cells. GDF9 induced Smad2/3 phosphorylation, which was impeded by ALK5 knockdown and by activin receptor-like kinase (ALK) receptor inhibitor SB-505124, which also suppressed FSHβ expression. Smad2/3 knockdown indicated that FSHβ induction by GDF9 involved Smad2 and Smad3. FSHβ mRNA induction by GDF9 and GnRH was synergistic. We hypothesized that GDF9 contributes to a regulatory loop that tunes the GnRH frequency-response characteristics of the FSHβ gene. To test this, we determined the effects of GDF9 knockdown on FSHβ induction at different GnRH pulse frequencies using a parallel perifusion system. Reduction of GDF9 shifted the characteristic pattern of GnRH pulse frequency sensitivity. These results identify GDF9 as contributing to an incoherent feed-forward loop, comprising both intracellular and secreted components, that regulates FSHβ expression in response to activation of cell surface GnRH receptors.

Control of gene expression following activation of membrane receptors results from the regulation of intracellular signaling pathways and transcription factors. Accordingly, research to elucidate the regulatory control circuits and cellular data processing mechanisms focuses on intracellular mechanisms. While autocrine and paracrine signaling are acknowledged in endocrinology, secreted factors are not typically recognized as fundamental components of the pathways connecting cell surface receptors to gene control in the nucleus. Studies of the gonadotrope suggest that extracellular regulatory loops may play a central role in the regulation of gonadotropin gene expression by gonadotropin-releasing hormone (GnRH) receptor activation. We review emerging evidence for this phenomenon, which we refer to as exosignaling, in gonadotropin gene control and in other receptor-mediated signaling systems. We propose that basic signaling circuit modules controlling gene expression can be seamlessly distributed across intracellular and exosignaling components that together orchestrate the precise physiological control of gene expression.

In adaptive optics systems, the precision wavefront sensor determines the closed-loop correction effect. The accuracy of the wavefront sensor is severely reduced when light energy is weak, while the real-time performance of wavefront sensorless adaptive optics systems based on iterative algorithms is poor. The wavefront correction algorithm based on deep learning can directly obtain the aberration or correction voltage from the input image light intensity data with better real-time performance. Nevertheless, manually designing deep-learning models requires a multitude of repeated experiments to adjust many hyperparameters and increase the accuracy of the system. A wavefront sensorless system based on convolutional neural networks with automatic hyperparameter optimization was proposed to address the aforementioned issues, and networks known for their superior performance, such as ResNet and DenseNet, were constructed as constructed groups. The accuracy of the model was improved by over 26%, and there were fewer parameters in the proposed method, which was more accurate and efficient according to numerical simulations and experimental validation. [ABSTRACT FROM AUTHOR]