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BACKGROUND: During the prolonged period from Human Papillomavirus (HPV) infection to cervical cancer development, Low-Grade Squamous Intraepithelial Lesion (LSIL) stage provides a critical opportunity for cervical cancer prevention, giving the high potential for reversal in this stage. However, there is few research and a lack of clear guidelines on appropriate intervention strategies at this stage, underscoring the need for real-time prognostic predictions and personalized treatments to promote lesion reversal. METHODS: We have established a prospective cohort. Since 2018, we have been collecting clinical data and pathological images of HPV-infected patients, followed by tracking the progression of their cervical lesions. In constructing our predictive models, we applied logistic regression and six machine learning models, evaluating each model's predictive performance using metrics such as the Area Under the Curve (AUC). We also employed the SHAP method for interpretative analysis of the prediction results. Additionally, the model identifies key factors influencing the progression of the lesions. RESULTS: Model comparisons highlighted the superior performance of Random Forests (RF) and Support Vector Machines (SVM), both in clinical parameter and pathological image-based predictions. Notably, the RF model, which integrates pathological images and clinical multi-parameters, achieved the highest AUC of 0.866. Another significant finding was the substantial impact of sleep quality on the spontaneous clearance of HPV and regression of LSIL. CONCLUSIONS: In contrast to current cervical cancer prediction models, our model's prognostic capabilities extend to the spontaneous regression stage of cervical cancer. This model aids clinicians in real-time monitoring of lesions and in developing personalized treatment or follow-up plans by assessing individual risk factors, thus fostering lesion spontaneous reversal and aiding in cervical cancer prevention and reduction.
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Lesões Pré-Cancerosas , Medicina de Precisão , Neoplasias do Colo do Útero , Humanos , Feminino , Neoplasias do Colo do Útero/patologia , Neoplasias do Colo do Útero/virologia , Lesões Pré-Cancerosas/patologia , Lesões Pré-Cancerosas/virologia , Adulto , Aprendizado de Máquina , Pessoa de Meia-Idade , Progressão da Doença , Modelos BiológicosRESUMO
Lipid oxidation is a major cause of quality deterioration in salad dressings. This study evaluated the effect of incorporating microencapsulated polyphenol extracts via spray drying from pomegranate peels (MPP) to delay lipid oxidation in Italian-style salad dressings (ISD) during accelerated (55°C) and ambient (25°C) storage conditions. ISDs, prepared at high (5000 rpm) and low (250 rpm) shear rates conditions, were formulated with unencapsulated polyphenol extracts from pomegranate peels (PPP), MPP, and/or grape seed extract (GSE). Lipid oxidation in ISDs was evaluated by measuring peroxide value (PV), iodine value (IV), and TBARS, stored in accelerated and ambient conditions for 21 days and 8 weeks, respectively. Tannis in extracts were measured via HPLC-DAD and the total hydrolyzable tannin content of PPP and MPP was 283.09 and 427.74 (mg/g extract), respectively. Condensed tannins were not detected in PPP and MPP but were found in GSE (348.53 mg/g extract). Salad dressings prepared at high shear rates had significantly (p < .05) higher emulsion stability than those homogenized at low shear rates. Mixing conditions did not affect the lipid oxidative stability of IDSs. Salad dressing stored under accelerated storage had higher lipid oxidation (higher PV, lower IV, and higher TBARS) after 21 days than IDSs stored under ambient conditions for 8 weeks. ISDs prepared with MPPP showed significantly (p < .05) lower lipid oxidation than the other ISDs at the end of the shelf life studies. Results from the accelerated storage suggested that incorporating MPP could have extended the shelf life of IDSs by 20% compared to using unencapsulated polyphenol extracts. The study demonstrated that MPP delays lipid oxidation in ISDs during storage more effectively than unencapsulated extracts. MPP may serve as a natural and effective functional food ingredient for controlling lipid oxidation in high-lipid and acidified foods.
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This study proposed an interpretable multi-scale infrared small object detection network (IMD-Net) design method to improve the precision of infrared small object detection and contour segmentation in complex backgrounds. To this end, a multi-scale object enhancement module was constructed, which converted artificially designed features into network structures. The network structure was used to enhance actual objects and extract shallow detail and deep semantic features of images. Next, a global object response, channel attention, and multilayer feature fusion modules were introduced, combining context and channel information and aggregated information, selected data, and decoded objects. Finally, the multiple loss constraint module was constructed, which effectively constrained the network output using multiple losses and solved the problems of high false alarms and high missed detections. Experimental results showed that the proposed network model outperformed local energy factor (LEF), self-regularized weighted sparse model (SRWS), asymmetric contextual modulation (ACM), and other state of the art methods in the intersection-over-union (IoU) and Fmeasure values by 10.8% and 11.3%, respectively. The proposed method performed best on the currently available datasets, achieving accurate detection and effective segmentation of dim and small objects in various infrared complex background images.
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Persistent oxidative stress and endoplasmic reticulum (ER) stress are the primary mechanisms of age-related cardiovascular diseases. Although exercise training is viewed as an effective anti-aging approach, further exploration is needed to identify the mechanisms and functional targets. In this study, the impact of resistance training (RT) on the expression of Smyd1, the levels of reactive oxygen species (ROS) and the expression of ER stress-related protein in the hearts of mice of different ages were assessed. In addition, the role of Smyd1 in the aging-induced oxidative stress and ER stress were evaluated in d-galactose (D-gal)-treated H9C2 cells. We demonstrated that RT in middle age increased the expression of Smyd1 and restricted heart aging-induced ER stress. Overexpression of Smyd1 restrained oxidative stress and ER stress in D-gal-treated H9C2 cells, while the inhibition of Nrf2 and Smyd1 escalated ER stress. These findings demonstrate that Smyd1 has significant impact in regulating age-related ER stress. RT in middle age can up-regulates Smyd1 expression and inhibits oxidative stress and ER stress in the heart.
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Treinamento Resistido , Humanos , Camundongos , Animais , Coração , Estresse do Retículo Endoplasmático/genética , Estresse Oxidativo , Espécies Reativas de Oxigênio/metabolismo , Apoptose , Proteínas de Ligação a DNA/metabolismo , Proteínas Musculares/metabolismo , Fatores de Transcrição/metabolismoRESUMO
BACKGROUND: Restrictions on international travel were widely applied to contain cross-border COVID-19 diffusion, while such applications varied globally, and little was known about their impacts on the long-term epidemic progression. METHODS: We explored the global diversity in maintaining border policies classified to four levels (screening, quarantine, ban on regions and total border closure) using data of 185 countries and regions between 01 January 2020 to 31 December 2021. By using Ordinary least squares (OLS) regression and quantile regression (QR) models, we examined the relationship between total COVID-19 incidence and the cumulative duration of each policy level in 2020-2021, and the heterogeneity of such association across different transmission severity countries. RESULTS: Firstly, "ban on regions" was the most durable policy applied in high-income countries, while in low-income countries, less stringent measures of screening and quarantine arrivals were applied the longest. Secondly, the cumulatively longer maintenance of the border quarantine was significantly associated with lower infections (log) in COVID-19 high-prevalent countries (75th QR, coefficient estimates [ß] = -0.0038, 95% confidence interval: -0.0066 to -0.0010). By contrast, in medium and high transmission severity countries, those with longer duration of imposing bans on regions showed no suppressing effects but significantly higher COVID-19 incidence (OLS regression, ß = 0.0028, 95% CI: 0.0009-0.0047; 75th QR, ß = 0.0039, 95% CI: 0.0014-0.0063). No other significant results were found. CONCLUSION: From the long-term perspective, inbound quarantine was effective in mitigating severe epidemics. However, in countries with medium or high COVID-19 prevalence, our findings of ban on regions highlighted its ineffectiveness in the long-term epidemic progression.
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COVID-19 , Epidemias , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , SARS-CoV-2 , Epidemias/prevenção & controle , Quarentena , Incidência , ViagemRESUMO
Populations of pathogens may increase in fresh produce when subjected to temperature abuse. Smartphone-based infrared (SBIR) cameras are potential alternatives for temperature measurements of fresh produce during postharvest handling and storage. This study compared the performance of SBIR cameras (FLIR and Seek) against conventional temperature acquisition devices for evaluating fresh produce's simulated hydrocooling and storage conditions. First, thermal images of fresh produce were obtained with SBIR cameras and handheld thermal imagers at ~35 °C, ~20 °C, and ~4 °C to simulate outdoor, packinghouse, and refrigerated environments, respectively. Next, fresh produce was incubated at ~42 °C for 20 h and immersed in chilled water for a hydrocooling simulation. Then, boxes containing cooled fresh produce were stored in a walk-in cooler at different heights for three days. FLIR SBIR cameras were more effective at capturing thermal images of fresh produce than Seek SBIR cameras in all evaluated conditions. More importantly, SBIR cameras accurately acquired temperature profiles of fresh produce during simulated hydrocooling and cold storage. Additionally, the accuracy and quality of thermal images obtained with FLIR cameras were better than those obtained with Seek cameras. The study demonstrated that SBIR cameras are practical, easy-to-use, and cost-effective devices to monitor fresh produce's temperature during postharvest handling and storage.
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The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan has aroused widespread concern and attention from all over the world. Many articles have predicted the development of the epidemic. Most of them only use very basic SEIR model without considering the real situation. In this paper, we build a model called e-ISHR model based on SEIR model. Then we add hospital system and time delay system into the original model to simulate the spread of COVID-19 better. Besides, in order to take the government's control and people's awareness into consideration, we change our e-ISHR model into a 3-staged model which effectively shows the impact of these factors on the spread of the disease. By using this e-ISHR model, we fit and predict the number of confirmed cases in Wuhan and China except Hubei. We also change some of parameters in our model. The results indicate the importance of isolation and increasing the number of beds in hospital.