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Drought is a principal environmental factor that affects the growth and development of plants. Accordingly, plants have evolved adaptive mechanisms to cope with adverse environmental conditions. One of the mechanisms is gene regulation mediated by microRNAs (miRNAs). miRNAs are regarded as primary modulators of gene expression at the post-transcriptional level and have been shown to participate in drought stress response, including ABA response, auxin signaling, antioxidant defense, and osmotic regulation through downregulating the corresponding targets. miRNA-based genetic reconstructions have the potential to improve the tolerance of plants to drought. However, there are few precise classification and discussion of miRNAs in specific response behaviors to drought stress and their applications. This review summarized and discussed the specific response behaviors of miRNAs under drought stress and the role of miRNAs as regulators in the response of plants to drought and highlighted that the modification of miRNAs might effectively improve the tolerance of plants to drought.
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OBJECTIVES: To explore the long-term trends in unhealthy lifestyle factors and the risk sociodemographic subgroups among people with dyslipidemia. METHODS: Data extracted from the 1999 to 2018 National Health and Nutrition Examination Survey (NHANES). Lifestyle factors were smoking status, alcohol drinking, obesity, dietary quality, depression, physical activity, and sedentary behavior. A Joinpoint regression model was used to estimate trends in the log-transformed age-standardized prevalence. Multinomial logistic regression models adjusted for age, sex, and race/ethnicity were used to analyze subgroups by sociodemographic factors. RESULTS: Data for 33,680 respondents were extracted between 1999 and 2018. The prevalence of smoking and poor-quality diet decreased from 1999 to 2018 (P<0.001), while obesity significantly increased (P<0.001). The prevalence of depression marginally increased from 2005 to 2018 (P=0.074). We observed that non-Hispanic Black individuals, Hispanics, males, as well as those with lower family income-to-poverty ratios and education levels, unemployed individuals, or those lacking a spouse/live-in partner, were at elevated risk of unhealthy lifestyle factors when compared to the reference groups. CONCLUSIONS: Among NHANES respondents from 1999 to 2018 with dyslipidemia, significant reductions in the prevalence of current smoking and poor diet were observed, while the prevalence of obesity was markedly increased. There were sociodemographic differences in the management of lifestyle factors. Further initiatives to encourage people with dyslipidemia are required to reduce potential adverse outcomes.
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BACKGROUND: Angina with no obstructive coronary disease (ANOCA) and ischemia with no obstructive coronary disease, prevalent yet underrecognized conditions, mostly affect women. Previous studies rarely distinguished between them. We aimed to compare the prevalence of objective ischemia through various examinations in women with ANOCA and assess the impact of objective and subjective ischemia on their mental health. METHODS AND RESULTS: A total of 84 eligible women with ANOCA and 42 controls underwent mental stress, pharmacological stress, exercise stress, and Holter testing. Objective evidence of myocardial ischemia was assessed by positron emission tomography-computed tomography and ECG, and subjective symptoms were graded using the Canadian Cardiovascular Society scale (CCS). Psychological assessments were conducted using 6 scales. Among 84 women with ANOCA, 37 (44%) received a diagnosis of ischemia with no obstructive coronary disease following mental stress testing, 20 (28.6%) through pharmacological stress testing, 14 (21.2%) via exercise stress testing, and 24 (32.9%) from Holter. Mental stress-induced myocardial ischemia was more prevalent (P<0.05). Among 54 patients with ANOCA who completed all tests, 30% showed no ischemia, and only 1 (1.9%) showed ischemia in all tests. In addition, patients with ANOCA had higher psychological scores than controls (P<0.01). No significant differences was observed in psychological scores between ANOCA with positive and negative ischemia test results (P>0.05). However, ANOCA with milder angina (CCS I) exhibited higher scores across the Hospital Anxiety and Depression Scale, State-Trait Anxiety Inventory, Perceived Stress Scale, and Posttraumatic Stress Disorder Checklist-Civilian Version and a higher prevalence of Type D personality traits (P<0.05). CONCLUSIONS: In patients with ANOCA, the positive rate of myocardial ischemia exhibits variability among several noninvasive tests. A worsened psychological state is more closely linked to milder angina symptoms than to ischemia performance, highlighting the importance of focusing on symptom management in their psychological care. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03982901.
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Angina de Pecho , Prueba de Esfuerzo , Isquemia Miocárdica , Humanos , Femenino , Persona de Mediana Edad , Isquemia Miocárdica/psicología , Isquemia Miocárdica/epidemiología , Isquemia Miocárdica/diagnóstico , Angina de Pecho/psicología , Angina de Pecho/epidemiología , Angina de Pecho/diagnóstico , Prevalencia , Anciano , Distrés Psicológico , Electrocardiografía Ambulatoria , Estudios de Casos y Controles , Tomografía Computarizada por Tomografía de Emisión de Positrones , Estrés Psicológico/epidemiologíaRESUMEN
BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists. METHODS: We developed a DL model using a manually annotated dataset (1196 cancer vs 1034 normal). The DL model was tested using an internal test set (98 vs 115), two external test sets (202 vs 265 in 1, and 252 vs 481 in 2), and a real-world test set (53 vs 1524). We compared the detection performance of the DL model with radiologists, and evaluated its capacity to enhance radiologists' detection performance. FINDINGS: In the four test sets, the DL model had the area under the receiver operating characteristic curves (AUCs) ranging between 0.957 and 0.994. In both the internal test set and external test set 1, the DL model yielded higher accuracy than that of radiologists (97.2% vs 86.0%, p < 0.0001; 94.9% vs 85.3%, p < 0.0001), and significantly improved the accuracy of radiologists (93.4% vs 86.0%, p < 0.0001; 93.6% vs 85.3%, p < 0.0001). In the real-world test set, the DL model delivered sensitivity comparable to that of radiologists who had been informed about clinical indications for most cancer cases (94.3% vs 96.2%, p > 0.99), and it detected 2 cases that had been missed by radiologists. INTERPRETATION: The developed DL model can accurately detect colorectal cancer and improve radiologists' detection performance, showing its potential as an effective computer-aided detection tool. FUNDING: This study was supported by National Science Fund for Distinguished Young Scholars of China (No. 81925023); Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U22A20345); National Natural Science Foundation of China (No. 82072090 and No. 82371954); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); High-level Hospital Construction Project (No. DFJHBF202105).
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Neoplasias Colorrectales , Medios de Contraste , Aprendizaje Profundo , Tomografía Computarizada por Rayos X , Humanos , Neoplasias Colorrectales/diagnóstico por imagen , Neoplasias Colorrectales/diagnóstico , Femenino , Masculino , Estudios Retrospectivos , Tomografía Computarizada por Rayos X/métodos , Persona de Mediana Edad , Anciano , Curva ROC , Adulto , Anciano de 80 o más AñosRESUMEN
Automated colorectal cancer (CRC) segmentation in medical imaging is the key to achieving automation of CRC detection, staging, and treatment response monitoring. Compared with magnetic resonance imaging (MRI) and computed tomography colonography (CTC), conventional computed tomography (CT) has enormous potential because of its broad implementation, superiority for the hollow viscera (colon), and convenience without needing bowel preparation. However, the segmentation of CRC in conventional CT is more challenging due to the difficulties presenting with the unprepared bowel, such as distinguishing the colorectum from other structures with similar appearance and distinguishing the CRC from the contents of the colorectum. To tackle these challenges, we introduce DeepCRC-SL, the first automated segmentation algorithm for CRC and colorectum in conventional contrast-enhanced CT scans. We propose a topology-aware deep learning-based approach, which builds a novel 1-D colorectal coordinate system and encodes each voxel of the colorectum with a relative position along the coordinate system. We then induce an auxiliary regression task to predict the colorectal coordinate value of each voxel, aiming to integrate global topology into the segmentation network and thus improve the colorectum's continuity. Self-attention layers are utilized to capture global contexts for the coordinate regression task and enhance the ability to differentiate CRC and colorectum tissues. Moreover, a coordinate-driven self-learning (SL) strategy is introduced to leverage a large amount of unlabeled data to improve segmentation performance. We validate the proposed approach on a dataset including 227 labeled and 585 unlabeled CRC cases by fivefold cross-validation. Experimental results demonstrate that our method outperforms some recent related segmentation methods and achieves the segmentation accuracy in DSC for CRC of 0.669 and colorectum of 0.892, reaching to the performance (at 0.639 and 0.890, respectively) of a medical resident with two years of specialized CRC imaging fellowship.
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The thermal bleaching percentage of coral holobionts shows interspecific differences under heat-stress conditions, which are closely related to the coral-associated microbiome. However, the ecological effects of community dynamics and interactions between Symbiodiniaceae and fungi on coral thermal bleaching susceptibility remain unclear. In this study, we analyzed the diversity, community structure, functions, and potential interaction of Symbiodiniaceae and fungi among 18 coral species from a high thermal bleaching risk atoll using next-generation sequencing. The results showed that heat-tolerant C3u sub-clade and Durusdinium dominated the Symbiodiniaceae community of corals and that there were no core amplicon sequence variants in the coral-associated fungal community. Fungal richness and the abundance of confirmed functional animal-plant pathogens were significantly positively correlated with the coral thermal bleaching percentage. Fungal indicators, including Didymellaceae, Chaetomiaceae, Schizophyllum, and Colletotrichum, were identified in corals. Each coral species had a complex Symbiodiniaceae-fungi interaction network (SFIN), which was driven by the dominant Symbiodiniaceae sub-clades. The SFINs of coral holobionts with low thermal bleaching susceptibility exhibited low complexity and high betweenness centrality. These results indicate that the extra heat tolerance of coral in Huangyan Island may be linked to the high abundance of heat-tolerant Symbiodiniaceae. Fungal communities have high interspecific flexibility, and the increase of fungal diversity and pathogen abundance was correlated with higher thermal bleaching susceptibility of corals. Moreover, fungal indicators were associated with the degrees of coral thermal bleaching susceptibility, including both high and intermediate levels. The topological properties of SFINs suggest that heat-tolerant coral have limited fungal parasitism and strong microbial network resilience.IMPORTANCEGlobal warming and enhanced marine heatwaves have led to a rapid decline in coral reef ecosystems worldwide. Several studies have focused on the impact of coral-associated microbiomes on thermal bleaching susceptibility in corals; however, the ecological functions and interactions between Symbiodiniaceae and fungi remain unclear. We investigated the microbiome dynamics and potential interactions of Symbiodiniaceae and fungi among 18 coral species in Huangyan Island. Our study found that the Symbiodiniaceae community of corals was mainly composed of heat-tolerant C3u sub-clade and Durusdinium. The increase in fungal diversity and pathogen abundance has close associations with higher coral thermal bleaching susceptibility. We first constructed an interaction network between Symbiodiniaceae and fungi in corals, which indicated that restricting fungal parasitism and strong interaction network resilience would promote heat acclimatization of corals. Accordingly, this study provides insights into the role of microorganisms and their interaction as drivers of interspecific differences in coral thermal bleaching.
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Antozoos , Dinoflagelados , Microbiota , Animales , Antozoos/microbiología , Arrecifes de Coral , Simbiosis , Hongos/genéticaRESUMEN
Accurate and automated segmentation of breast tumors in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a critical role in computer-aided diagnosis and treatment of breast cancer. However, this task is challenging, due to random variation in tumor sizes, shapes, appearances, and blurred boundaries of tumors caused by inherent heterogeneity of breast cancer. Moreover, the presence of ill-posed artifacts in DCE-MRI further complicate the process of tumor region annotation. To address the challenges above, we propose a scheme (named SwinHR) integrating prior DCE-MRI knowledge and temporal-spatial information of breast tumors. The prior DCE-MRI knowledge refers to hemodynamic information extracted from multiple DCE-MRI phases, which can provide pharmacokinetics information to describe metabolic changes of the tumor cells over the scanning time. The Swin Transformer with hierarchical re-parameterization large kernel architecture (H-RLK) can capture long-range dependencies within DCE-MRI while maintaining computational efficiency by a shifted window-based self-attention mechanism. The use of H-RLK can extract high-level features with a wider receptive field, which can make the model capture contextual information at different levels of abstraction. Extensive experiments are conducted in large-scale datasets to validate the effectiveness of our proposed SwinHR scheme, demonstrating its superiority over recent state-of-the-art segmentation methods. Also, a subgroup analysis split by MRI scanners, field strength, and tumor size is conducted to verify its generalization. The source code is released on (https://github.com/GDPHMediaLab/SwinHR).
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Neoplasias de la Mama , Neoplasias Mamarias Animales , Humanos , Animales , Femenino , Diagnóstico por Computador , Neoplasias de la Mama/patología , Imagen por Resonancia Magnética/métodos , Programas Informáticos , Procesamiento de Imagen Asistido por ComputadorRESUMEN
Background: Radiomics models could help assess the benign and malignant invasiveness and prognosis of pulmonary nodules. However, the lack of interpretability limits application of these models. We thus aimed to construct and validate an interpretable and generalized computed tomography (CT) radiomics model to evaluate the pathological invasiveness in patients with a solitary pulmonary nodule in order to improve the management of these patients. Methods: We retrospectively enrolled 248 patients with CT-diagnosed solitary pulmonary nodules. Radiomic features were extracted from nodular region and perinodular regions of 3 and 5 mm. After coarse-to-fine feature selection, the radiomics score (radscore) was calculated using the least absolute shrinkage and selection operator logistic method. Univariate and multivariate logistic regression analyses were performed to determine the invasiveness-related clinicoradiological factors. The clinical-radiomics model was then constructed using the logistic and extreme gradient boosting (XGBoost) algorithms. The Shapley additive explanations (SHAP) method was then used to explain the contributions of the features. After removing batch effects with the ComBat algorithm, we assessed the generalization of the explainable clinical-radiomics model in two independent external validation cohorts (n=147 and n=149). Results: The clinical-radiomic XGBoost model integrating the radscore, CT value, nodule length, and crescent sign demonstrated better predictive performance than did the clinical-radiomics logistic model in assessing pulmonary nodule invasiveness, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.889 [95% confidence interval (CI), 0.848-0.927] in the training cohort. The SHAP algorithm illustrates the contribution of each feature in the final model. The specific model decision process was visualized using a tree-based decision heatmap. Satisfactory generalization performance was shown with AUCs of 0.889 (95% CI, 0.823-0.942) and 0.915 (95% CI, 0.851-0.963) in the two external validation cohorts. Conclusions: An interpretable and generalized clinical-radiomics model for predicting pulmonary nodule invasibility was constructed to help clinicians determine the invasiveness of pulmonary nodules and devise assessment strategies in an easily understandable manner.
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The widespread use of pesticides hampers the immune system of non-target organisms, however, there is a lack of common biomarkers to detect such effects. Myeloid differentiation primary response factor 88 (MyD88) is a crucial junction protein in the Toll-like receptor signaling pathway, which plays an important role in the inflammatory response. In this study, we investigated MyD88 as a potential biomarker for pesticide-induced stress. Phylogenetic analysis revealed that MyD88 was a conserved protein in the evolution of vertebrates and invertebrates. MyD88s usually have death domain (DD) and Toll/interleukin-1 receptor (TIR) domain. Bombyx mori (B. mori) is an important economic insect that is sensitive to toxic substances. We found microbial pesticides enhanced the expression level of MyD88 in B. mori. Transcriptome analysis demonstrated that MyD88 expression level was increased in the fatbody after dinotefuran exposure, a third-generation neonicotinoid pesticide. Moreover, the expression of MyD88 was upregulated in fatbody and midgut by imidacloprid, a first-generation neonicotinoid pesticide. Additionally, insect growth regulator (IGR) pesticides, such as methoprene and fenoxycarb, could induce MyD88 expression in the fatbody of B. mori. These results indicated that MyD88 is a potential biomarker for pesticide-induced stress in B. mori. This study provides novel insights into screening common biomarkers for multiple pesticide stresses and important implications for the development of more sustainable pest management strategies.
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Bombyx , Plaguicidas , Animales , Plaguicidas/farmacología , Factor 88 de Diferenciación Mieloide/genética , Factor 88 de Diferenciación Mieloide/metabolismo , Factor 88 de Diferenciación Mieloide/farmacología , Filogenia , Biomarcadores , Neonicotinoides/toxicidad , Proteínas de Insectos/genética , Proteínas de Insectos/metabolismoRESUMEN
It is common for diabetic kidney disease (DKD) to be complicated by abnormal blood glucose, blood lipids, and blood pressure rhythms. Thus, it is essential to examine diagnostic and treatment plans from the perspective of circadian disruption. This brief review discusses the clinical relevance of circadian rhythms in DKD and how the core clock gene encoding brain and muscle arnt-like protein 1 (BMAL1) functions owing to the importance of circadian rhythm disruption processes, including the excretion of urinary protein and irregular blood pressure, which occur in DKD. Exploring Bmal1 and its potential mechanisms and signaling pathways in DKD following contact with Sirt1 and NF-κB is novel and important. Finally, potential pharmacological and behavioral intervention strategies for DKD circadian rhythm disturbance are outlined. This review aids in unveiling novel, potential molecular targets for DKD based on circadian rhythms.
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Líquidos Corporales , Diabetes Mellitus , Nefropatías Diabéticas , Humanos , Factores de Transcripción ARNTL/genética , Presión Sanguínea , Ritmo Circadiano , Diabetes Mellitus/genética , Nefropatías Diabéticas/genéticaRESUMEN
BACKGROUND: Accurately assessing the risk of recurrence in patients with locally advanced rectal cancer (LARC) before treatment is important for the development of treatment strategies. The purpose of this study is to develop an MRI-based scoring system to predict the risk of recurrence in patients with LARC. METHODS: This was a multicenter observational study that enrolled participants who underwent neoadjuvant chemoradiotherapy. To evaluate the risk of recurrence in these patients, we developed the mrDEC scoring system and assessed inter-reader agreement. Additionally, we plotted Kaplan-Meier curves to compare the 3-year disease-free survival (DFS) and 5-year overall survival (OS) rates among patients with different mrDEC scores. RESULTS: A total of 1287 patients with LARC were included in this study. We observed substantial inter-reader agreement for mrDEC. Based on the mrDEC scores ranging from 0 to 3, the patients were categorized into four groups. The 3-year DFS rates for the groups were 91.0%, 79.5%, 65.5%, and 44.0% (P < 0.0001), respectively, and the 5-year OS rates were 92.9%, 87.1%, 74.8%, and 44.5%, respectively (P < 0.0001). CONCLUSIONS: The mrDEC scoring system proved to be an effective tool for predicting the prognosis of patients with LARC and can assist clinicians in clinical decision-making.
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Neoplasias del Recto , Humanos , Resultado del Tratamiento , Neoplasias del Recto/terapia , Neoplasias del Recto/tratamiento farmacológico , Quimioradioterapia , Pronóstico , Supervivencia sin Enfermedad , Terapia Neoadyuvante , Imagen por Resonancia Magnética , Medición de Riesgo , Estudios Retrospectivos , Estadificación de NeoplasiasRESUMEN
Objectives: To examine national trends in unhealthy lifestyle factors among adults with cardiovascular disease (CVD) in the United States (US) between 1999 and 2018. Methods: We analyzed data from National Health and Nutrition Examination Survey (NHANES), a nationally representative survey of participants with CVD who were aged ≥20 years, which was conducted between 1999 and 2000 and 2017-2018. CVD was defined as a self-report of congestive heart failure, coronary heart disease, angina, heart attack, or stroke. The prevalence rate of each unhealthy lifestyle factor was calculated among adults with CVD for each of the 2-year cycle surveys. Regression analyses were used to assess the impact of sociodemographic characteristics (age, sex, race/ethnicity, family income, education level, marital status, and employment status). Results: The final sample included 5610 NHANES respondents with CVD. The prevalence rate of their current smoking status remained stable among respondents with CVD between 1999 and 2000 and 2017-2018. During the same period, there was a decreasing trend in the age-adjusted prevalence rate of poor diet [primary American Heart Association (AHA) score <20; 47.5% (37.9%-57.0%) to 37.5% (25.7%-49.3%), p < 0.01]. Physical inactivity marginally increased before decreasing, with no statistical significance. The prevalence rate of sedentary behavior increased from 2007 to 2014 but subsequently returned to its original level in 2018 with no statistical significance. The age-adjusted prevalence rate of obesity increased from 32% (27.2%-36.8%) in 1999-2000 to 47.9% (39.9%-55.8%) in 2017-2018 (p < 0.001). The age-adjusted prevalence rate of depression increased from 7% (4.2%-9.9%) in 1999-2000 to 13.9% (10.2%-17.6%) in 2017-2018 (p = 0.056). Trends in mean for each unhealthy lifestyle factor were similar after adjustment for age. We found that respondents who had low education and income levels were at a higher risk of being exposed to unhealthy lifestyle factors (i.e., smoking, poor diet, and physical inactivity) than those who had high education and income levels. Conclusions: There is a significant reduction in the prevalence rate of poor diet among US adults with CVD between 1999 and 2018, while the prevalence rate of obesity showed increasing trends over this period. The prevalence rate of current smoking status, sedentary behavior, and depression was either stable or showed an insignificant increase. These findings suggest that there is an urgent need for health policy interventions targeting unhealthy lifestyles among adults with CVD.
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CONTEXT: 3,4-bis(3-nitrofurazan-4-yl)furoxan (DNTF) is a new energetic compound with high energy and high density, and it is an important component of propellant and melt cast explosive. In order to study the effect of solvent on the growth morphology of DNTF, the growth plane of DNTF in vacuum is predicted by attachment energy (AE) model, and then the modified attachment energy of each growth plane in different solvents is calculated by molecular dynamics simulation. The morphology of crystal in solvent is predicted by modified attachment energy (MAE) model. The factors affecting crystal growth in solvent environment are analyzed by mass density distribution, radial distribution function and diffusion coefficient. The results show that the growth morphology of crystal in solvent is not only related to the adsorption strength of solvent to crystal plane, but affected by the attraction of crystal plane to solute. The hydrogen bond plays an important role in the adsorption strength between solvent and crystal plane. The polarity of solvent has a great influence on the crystal morphology, and the interaction between the solvent with stronger polarity and the crystal plane is stronger. The morphology of DNTF in n-butanol solvent is closer to spherical, which can effectively reduce the sensitivity of DNTF. METHODS: The molecular dynamics simulation is carried out under the COMPASS force field of Materials Studio software. Gaussian software is used to calculate the electrostatic potential of DNTF at B3LYP-D3/6-311 + G (d, p) theoretical level.
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PURPOSE: To compare the effects of three occlusal adjustment methods in different sequences by articulating paper on the delayed occlusal characteristics of single molars. METHODS: Thirty-two implants of first molars were divided into group A(n=12), group B (n=12) and group C (n=12) by sequential adjustment according to random number means, and (100+40), (100+50+30) and (100+40+20) µm sequence occlusal papers were used for occlusal adjustment, respectively. TeeTester was used to measure the delay time and force ratio between prosthesis and adjacent teeth at restoration day, 3 and 6 months after restoration, and to record the number of cases readjusting in each group during follow-up. SPSS 25.0 software package was used for data analysis. RESULTS: There were significant differences in delay time between groups at restoration day (Pï¼0.05), and 3 and 6 months after restoration, delay time of group C was still smaller than that of group A and B (Pï¼0.05). During follow-up, the time of each group showed a trend of shortening (Pï¼0.05), but there was still delayed occlusion. Compared with group B and C, the force ratio in group A was lower at each time(Pï¼0.05). The ratio of each group showed an increasing trend during follow-up (Pï¼0.05), and group C showed the largest increase (Pï¼0.001). The number of cases readjusting was relatively small in group A, and the most was in group C(Pï¼0.05). There was positive correlation between delay time and force difference of prosthesis and adjacent teeth(Pï¼0.001). CONCLUSIONS: The (100+40) µm sequence group had higher occlusal stability and better clinical applicability. The smaller the occlusal contact space realized by the sequential method, the greater the change might be, which requires close follow-up in clinical practice.
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Ajuste Oclusal , Diente , Fuerza de la Mordida , Diente Molar/cirugía , Oclusión DentalRESUMEN
OBJECTIVES: The aim of this study is to evaluate the feasibility of clinicopathological characteristics and computed tomography (CT) morphological features in predicting lymph node metastasis (LNM) for patients with T1 colorectal cancer (CRC). METHODS: A total of 144 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in our study. The clinicopathological characteristics and CT morphological features were assessed by two observers. Univariate and multiple logistic regression analyses were used to identify significant LNM predictive variables. Then a model was developed using the independent predictive factors. The predictive model was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate the calibration curve and relative C-index. RESULTS: LNM were found in 30/144 patients (20.83%). Four independent risk factors were determined in the multiple logistic regression analysis, including presence of necrosis (adjusted odds ratio [OR] = 10.32, 95% confidence interval [CI] 1.96-54.3, p = 0.004), irregular outer border (adjusted OR = 5.94, 95% CI 1.39-25.45, p = 0.035), and heterogeneity enhancement (adjusted OR = 7.35, 95% CI 3.11-17.38, p = 0.007), as well as tumor location (adjusted ORright-sided colon = 0.05 [0.01-0.60], p = 0.018; adjusted ORrectum = 0.22 [0.06-0.83], p = 0.026). In the internal validation cohort, the model showed good calibration and good discrimination with a C-index of 0.89. CONCLUSIONS: There are significant associations between lymphatic metastasis status and tumor location as well as CT morphologic features in T1 CRC, which could help the doctor make decisions for additional surgery after endoscopic resection. KEY POINTS: ⢠LNM more frequently occurs in left-sided T1 colon cancer than in right-sided T1 colon and rectal cancer. ⢠CT morphologic features are risk factors for LNM of T1 CRC, which may be related to fundamental biological behaviors. ⢠The combination of tumor location and CT morphologic features can more effectively assist in predicting LNM in patients with T1 CRC, and decrease the rate of unnecessary extra surgeries after endoscopic resection.
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Neoplasias del Colon , Neoplasias Colorrectales , Humanos , Metástasis Linfática/patología , Neoplasias Colorrectales/patología , Estudios Retrospectivos , Neoplasias del Colon/patología , Factores de Riesgo , Ganglios Linfáticos/patologíaRESUMEN
RATIONALE AND OBJECTIVES: To develop an easy-to-use model by combining pretreatment MRI and clinicopathologic features for early prediction of tumor regression pattern to neoadjuvant chemotherapy (NAC) in breast cancer. MATERIALS AND METHODS: We retrospectively analyzed 420 patients who received NAC and underwent definitive surgery in our hospital from February 2012 to August 2020. Pathologic findings of surgical specimens were used as the gold standard to classify tumor regression patterns into concentric and non-concentric shrinkage. Morphologic and kinetic MRI features were both analyzed. Univariable and multivariable analyses were performed to select the key clinicopathologic and MRI features for pretreatment prediction of regression pattern. Logistic regression and six machine learning methods were used to construct prediction models, and their performance were evaluated with receiver operating characteristic curve. RESULTS: Two clinicopathologic variables and three MRI features were selected as independent predictors to construct prediction models. The apparent area under the curve (AUC) of seven prediction models were in the range of 0.669-0.740. The logistic regression model yielded an AUC of 0.708 (95% confidence interval [CI]: 0.658-0.759), and the decision tree model achieved the highest AUC of 0.740 (95% CI: 0.691-0.787). For internal validation, the optimism-corrected AUCs of seven models were in the range of 0.592-0.684. There was no significant difference between the AUCs of the logistic regression model and that of each machine learning model. CONCLUSION: Prediction models combining pretreatment MRI and clinicopathologic features are useful for predicting tumor regression pattern in breast cancer, which can assist to select patients who can benefit from NAC for de-escalation of breast surgery and modify treatment strategy.
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Neoplasias de la Mama , Imágenes de Resonancia Magnética Multiparamétrica , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/cirugía , Imágenes de Resonancia Magnética Multiparamétrica/métodos , Terapia Neoadyuvante/métodos , Estudios Retrospectivos , Resultado del Tratamiento , Imagen por Resonancia Magnética/métodosRESUMEN
Diabetes Mellitus (DM) is a metabolic disorder characterized by hyperglycemia. Over the years, scientists have identified many factors that may have causal relationships with DM development. Identified factors are either genetic or environmental, and they may promote or prevent DM development. This review discusses various factors that are involved in the molecular pathogenesis, development, and therapeutic strategies of type 2 diabetes. DM is caused by interactions between multiple factors and triggers. Altered metabolic pathways and cellular functions, primarily in organs involved in glucose metabolisms, such as the pancreas and liver, often result in metabolic dysfunction, leading to DM. Additionally, abnormal levels of some factors, the presence of some pathogens, or the use of some types of medicine, such as immuno-inflammatory mediators, glucagon, apolipoprotein E4, chromogranin-A, exosomes, vitamin D, viruses, glucocorticoid medication, and antipsychotic drugs, may play roles in the development of DM. Some of these factors and mechanisms are well-studied, while others are more controversial and have contradicting experimental results. Further research is needed to confirm the roles of these factors in DM and fully understand how they contribute to DM development. Numerous medications for diabetics have been developed to help alleviate the symptoms of hyperglycemia and its complications. Several types of small compounds or peptide drugs with anti-diabetic effects can decrease blood glucose levels, improve insulin resistance, and inhibit key enzymes involved in the development and progression of diabetes. Here, we review the commonly used effective antidiabetic drugs, including the most recent innovative ones, such as GLP- 1R/GIPR and GLP-1R/GCGR agonists, and Chinese medicine.
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Diabetes Mellitus Tipo 2 , Hiperglucemia , Humanos , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/diagnóstico , Patología Molecular , Hipoglucemiantes/uso terapéutico , Hiperglucemia/tratamiento farmacológico , Páncreas/metabolismoRESUMEN
BACKGROUND: Unhealthy lifestyle factors are risk factors for stroke, and they play a key role in stroke secondary prevention. A better understanding of these factors may aid with improvements in public health policy. OBJECTIVE: Our objective was to comprehensively understand the trends in unhealthy lifestyle factors in people who have previously had a stroke in the US. METHODS: Utilizing data from the biannual United States National Health and Nutrition Examination Surveys (NHANESs) between 1999 and 2018, we collated data on unhealthy lifestyle factors (smoking, alcohol drinking, depression, unhealthy diet, high BMI, physical inactivity, and sedentary behavior) in adults with a history of stroke. The Joinpoint Regression model was used to calculate the annual percentage change (APC) and average annual percentage change (AAPC) to identify trends. Logistic regression modeling was used to identify the influence of sociodemographic factors (age, sex, race/ethnicity, marital status, employment status, family income, and highest education level). RESULTS: The analysis included 2017 respondents with a history of stroke. Current alcohol drinking (39.3% (95% confidence interval: 29.8, 48.7) to 57.4% (45.7, 69.0) p = 0.008) and obesity (39.2% (28.3, 50.2) to 49.4% (38.9, 59.8) p = 0.029) increased significantly from 1999 to 2018. The prevalence of smoking and depression remained generally stable. The proportion of respondents with an unhealthy diet decreased from 1999 (44.5% (32.4, 56.5)) to 2011 (29.0% (17.5, 40.4) p = 0.019), but then returned to its original prevalence in 2018 (42.0% (31.4, 52.7)). From 2007 to 2018, the proportion of respondents who were physically inactive decreased significantly, from 70.4% (64.4, 76.3) to 55.1% (46.1, 64.2; p = 0.017). After a gradual increase in sedentary activity from 2007 to 2012, this declined from 2013 to 2018, with no statistical significance. We found stroke survivors who were widowed, divorced, separated, or unemployed were at a higher risk of having unhealthy lifestyles than those who were employed or had other marital statuses. CONCLUSIONS: A modest reduction in the prevalence of physical inactivity was observed in Americans with a history of stroke between 1999 and 2018. The prevalences of smoking, drinking, depression, poor diet, obesity, and sedentary behavior were stable or increasing.
RESUMEN
Replication licensing, a prerequisite of DNA replication, helps to ensure once-per-cell-cycle genome duplication. Some DNA replication-initiation proteins are sequentially loaded onto replication origins to form pre-replicative complexes (pre-RCs). ORC and Noc3p bind replication origins throughout the cell cycle, providing a platform for pre-RC assembly. We previously reported that cell cycle-dependent ORC dimerization is essential for the chromatin loading of the symmetric MCM double-hexamers. Here, we used Saccharomyces cerevisiae separation-of-function NOC3 mutants to confirm the separable roles of Noc3p in DNA replication and ribosome biogenesis. We also show that an essential and cell cycle-dependent Noc3p dimerization cycle regulates the ORC dimerization cycle. Noc3p dimerizes at the M-to-G1 transition and de-dimerizes in S-phase. The Noc3p dimerization cycle coupled with the ORC dimerization cycle enables replication licensing, protects nascent sister replication origins after replication initiation, and prevents re-replication. This study has revealed a new mechanism of replication licensing and elucidated the molecular mechanism of Noc3p as a mediator of ORC dimerization in pre-RC formation.