To get to know the mental status of community workers involved in the prevention of COVID-19 epidemic, provide them with mental counseling and guidance, and predict their mental health status, a ...cloud model for the mental health prediction of community workers involved in the prevention of COVID-19 epidemic was constructed in this paper. First, the method to collect data about mental health was determined; second, the basic definition of cloud was discussed, the digital features of cloud were analyzed, and then, the cloud theory model was constructed; third, a model to predict the mental health of community workers involved in the prevention of COVID-19 epidemic was constructed based on the cloud theory, and corresponding algorithm was designed. Finally, a community was chosen as the research object to analyze and predict its mental health status. The research results suggest that the model can effectively predict the mental health status of community workers involved in the prevention of COVID-19 epidemic.
The substituted p-phenylenediamines (PPDs) represent a suite of effective antioxidants broadly applied in rubber industries. However, knowledge of their environmental occurrences and fate remains ...extremely limited. Herein, we explored the occurrence of six major PPD antioxidants and one newly defined transformation product in dust particles from different environments, including roads, underground parking lots, vehicles, and houses. The majority of the PPDs exhibited ubiquitous occurrence in these environments. Median concentrations of total PPDs were determined to be 226 ng/g in road dust, 232 ng/g in parking lot dust, and 156 ng/g in vehicle dust, orders of magnitude greater than those in house dust (14.0 ng/g). Different composition profiles of PPDs were also found between house dust and vehicle-related dust, likely indicating the influence of vehicle tires or other rubber products. In addition, a major ozonation product of N-(1,3-dimethylbutyl)-N′-phenyl-1,4-phenylenediamine (6PPD), 6PPD-qunione, was also identified in dust with levels (median range of 32.2–80.9 ng/g) comparable to that of 6PPD except in house dust. To the best of our knowledge, this is the first systematic investigation of the occurrence of major PPD antioxidants and 6PPD-qunione in various dust matrices. Our findings would attract attention to their environmental fate and ecological and human health risks.
The present study aimed to investigate risk factors for early onset breast cancer that are related to lifestyle and psychological stress. A comparative case-control study was performed among patients ...from the Department of Breast Surgery in Shanghai Cancer Center of Fudan University. The information regarding risk factors associated with the development of early onset breast cancer was collected using a questionnaire in a face-to-face interview. The distribution of the risk factors associated with the development of early onset breast cancer between the patient group and the control group was analyzed with logistic regression. A total of 582 cases of young patients (≤40 years old) with breast cancer and 540 controls of young patients (≤40 years old) with benign breast disease were included in this study. The risk factors for breast cancer in young women include age at first birth (odds ratio OR = 0.93, 95% confidence interval CI: 0.88-0.98), history of breast cancer in an immediate family member (OR = 2.36, 95% CI: 1.14-4.89), history of genital surgery (OR = 2.11, 95% CI: 1.16-3.82), active and passive smoking in daily life or the environment (OR = 1.64, 95% CI: 1.19-2.25), weekly intake of soy products (OR = 1.24, 95% CI: 1.02-1.49), use of household cooking oil (OR = 2.04, 95% CI: 1.04-4.00), disharmonious marital status (OR = 1.16, 95% CI: 1.06-1.26), frequent depression (OR = 1.32, 95% CI: 1.00-1.75), and negative emotional experiences (OR = 1.15, 95% CI: 1.03-1.29). Our study could provide the basis for risk assessment and preventive interventions for early onset breast cancer.
Amid the COVID-19 pandemic, two important antiracist movements, namely, Black Lives Matter and Stop Asian Hate, swept across the United States between 2020 and early 2021. Social media platforms such ...as Twitter have become an increasingly important tool for mobilizing social movements. To gain a comprehensive understanding of social media users' attention and reactions to racial injustice during this unprecedented time, the current study explores and compares the discursive characteristics of Twitter discussions of these two movements: their volume changes, word diversities, and moral and emotional sentiments. By analyzing the text of approximately 5 million tweets from April 2020 to April 2021 using a dictionary-based word count method, this research showed that compared to #BlackLivesMatter, #StopAsianHate was less diverse, more morally charged, and less positive in emotional sentiment. Additionally, #StopAsianHate contained stronger moral emotions than #BlackLivesMatter. The study connects these distinct characteristics to the two movements' differences in their objectives, progress and participants' demographics and provides implications for effective antiracist activism on social media.
A positive interaction between plant populations is a type of population relationship formed during long-term evolution. This interaction can alleviate population competition, improve resource ...utilization in populations, and promote population harmony and community stability. However, cultivated plant populations may have insufficient time to establish a positive interaction, thereby hindering the formation of the positive interaction. As current studies have not fully addressed these issues, our study established soybean/wheat intercropping populations beneficial for growth and explored the effects of nutrient level and planting density on the positive interaction between the two crops. Changes across population modules in both sole cropping and intercropping populations of soybean and wheat were analyzed. Results using nutrient levels of ½- or ¼-strength Hoagland solution indicated that soybean/wheat intercropping population modules significantly increased at low planting densities (D20 and D26) and significantly decreased at high planting densities (D32 and D60). Therefore, as planting density increased, the modules of both intercropping populations initially increased before decreasing. Similarly, positive interaction initially strengthened before weakening. Moreover, at an intermediate planting density, the population modules reached their maxima, and the positive interaction was the strongest. Under the same planting density, ¼-strength Hoagland solution recorded better growth for the soybean/wheat intercropping population modules compared to results using the ½-strength Hoagland solution. These findings indicated that low nutrient level can increase the positive interaction of intercropping populations at a given planting density, and that environmental nutrient level and population planting densities constrain the positive interaction between soybean and wheat populations in the intercropping system. This study highlights issues that need to be addressed when constructing intercropping populations.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Effect of side-chain substitutions on the morphology of self-assembly of perylene diimide molecules has been studied with two derivatives modified with distinctly different side-chains, ...N,N‘-di(dodecyl)-perylene-3,4,9,10-tetracarboxylic diimide (DD-PTCDI) and N,N‘-di(nonyldecyl)-perylene-3,4,9,10-tetracarboxylic diimide (ND-PTCDI). Due to the different side-chain interference, the self-assembly of the two molecules results in totally different morphologies in aggregate: one-dimensional (1D) nanobelt vs zero-dimensional (0D) nanoparticle. The size, shape, and topography of the self-assemblies were extensively characterized by a variety of microscopies including SEM, TEM, AFM, and fluorescence microscopy. The distinct morphologies of self-assembly have been obtained from both the solution-based processing and surface-supported solvent-vapor annealing. The nanobelts of DD-PTCDI fabricated in solution can feasibly be transferred to both polar (e.g., glass) and nonpolar (e.g., carbon) surfaces, implying the high stability of the molecular assembly (due to the strong π−π stacking). The side-chain-dependent molecular interaction was comparatively investigated using various spectrometries including UV−vis absorption, fluorescence, X-ray diffraction, and differential scanning calorimetry. Compared to the emission of ND-PTCDI aggregate, the emission of DD-PTCDI aggregate was significantly red-shifted (ca. 30 nm) and the emission quantum yield decreased about three times, primarily due to the more favorable molecular stacking for DD-PTCID. Moreover, the aggregate of DD-PTCDI shows a pronounced absorption band at the longer wavelength, whereas the absorption of ND-PTCDI aggregate is not significant in the same wavelength region. These optical spectral observations are reminiscent of the previous theoretical investigation on the side-chain-modulated electronic properties of PTCDI assembly.
Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to ...handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children.
Real-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered.
To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Radiotherapy is the primary treatment for nasopharyngeal carcinoma (NPC), but radioresistance severely reduces NPC radiocurability. Here, we have established a radio-resistant NPC cell line, CNE-2R, ...and investigate the role of miRNAs in radioresistance. The miRNAs microarray assay reveals that miRNAs are differentially expressed between CNE-2R and its parental cell line CNE-2. We find that miR-205 is elevated in CNE-2R. A target prediction algorithm suggests that miR-205 regulates expression of PTE N, a tumor-suppressor. Introducing miR-205 into CNE-2 cells suppresses PTE N protein expression, followed by activation of AKT, increased number of foci formation and reduction of cell apoptosis postirradiation. On the other hand, knocking down miR-205 in CNE-2R cells compromises the inhibition of PTE N and increases cell apoptosis. Significantly, immunohistochemistry studies demonstrate that PTE N is downregulated at late stages of NPC, and that miR-205 is significantly elevated followed the radiotherapy. Our data conclude that miR-205 contributes to radioresistance of NPC by directly targeting PTE N. Both miR-205 and PTE N are potential predictive biomarkers for radiosensitivity of NPC and may serve as targets for achieve successful radiotherapy in NPC.
Although child maltreatment (CM) experiences are recognized risk factors for nonsuicidal self-injury (NSSI), the mechanisms underlying this relationship remain unclear. The purpose of this study was ...to examine whether difficulty in emotion regulation (DER) and depressive symptoms mediate the relationship between child maltreatment experiences and NSSI severity, adjusting for demographic variables.
The participants were 224 adolescent inpatients recruited from a hospital in China (mean age 15.30 years, SD = 1.83; 78.6% females). Study measures included the Clinician-Rated Severity of Nonsuicidal Self-Injury (CRSNSSI), Childhood Trauma Questionnaire (CTQ-SF), Difficulties in Emotion Regulation Scale (DERS), and Patient Health Questionnaire-9 (PHQ-9). The hypothesized chain mediation model was tested using the structural equation model.
A total of 146 (65.18%) adolescents reported engaging in NSSI during the past 12 months, and 103 (45.98%) participants met the DSM-5 diagnostic criteria for NSSI. Emotional neglect (48.1%) and emotional abuse (46.1%) had the highest prevalence, followed by physical neglect (43.1%) and physical abuse (24.1%), whereas sexual abuse (12.5%) was the least prevalent form of CM. Separately, both DER and depressive symptoms significantly mediated the association between CM and NSSI, with DER being the strongest mediator, with an indirect effect of 49.40% (p = 0.014). At the same time, we also proved a potential chain-mediated pathway of DER and depression in the relationship between CM and NSSI.
Child maltreatment seems to play a role in the aetiology of NSSI. DER and depressive symptoms both have a mediating role in the relationship between CM and NSSI. Importantly, DER seems to be a mediator with a stronger indirect effect compared to depressive symptoms.
In clinical and epidemiological researches, continuous predictors are often discretized into categorical variables for classification of patients. When the relationship between a continuous predictor ...and log relative hazards is U-shaped in survival data, there is a lack of a satisfying solution to find optimal cut-points to discretize the continuous predictor. In this study, we propose a novel approach named optimal equal-HR method to discretize a continuous variable that has a U-shaped relationship with log relative hazards in survival data.
The main idea of the optimal equal-HR method is to find two optimal cut-points that have equal log relative hazard values and result in Cox models with minimum AIC value. An R package 'CutpointsOEHR' has been developed for easy implementation of the optimal equal-HR method. A Monte Carlo simulation study was carried out to investigate the performance of the optimal equal-HR method. In the simulation process, different censoring proportions, baseline hazard functions and asymmetry levels of U-shaped relationships were chosen. To compare the optimal equal-HR method with other common approaches, the predictive performance of Cox models with variables discretized by different cut-points was assessed.
Simulation results showed that in asymmetric U-shape scenarios the optimal equal-HR method had better performance than the median split method, the upper and lower quantiles method, and the minimum p-value method regarding discrimination ability and overall performance of Cox models. The optimal equal-HR method was applied to a real dataset of small cell lung cancer. The real data example demonstrated that the optimal equal-HR method could provide clinical meaningful cut-points and had good predictive performance in Cox models.
In general, the optimal equal-HR method is recommended to discretize a continuous predictor with right-censored outcomes if the predictor has an asymmetric U-shaped relationship with log relative hazards based on Cox regression models.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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