Tobacco control knowledge and beliefs among healthcare workers in respiratory departments in Fujian Province, China: A cross-sectional study.

INTRODUCTION: Smoking prevalence is high in China, and healthcare workers are important for tobacco control. This study aimed to determine the smoking status, cognition of tobacco hazards, and smoking cessation-related knowledge among respiratory healthcare workers, and to explore their ability to provide smoking cessation assistance. METHODS: A cross-sectional study was conducted in 2021 among 1028 respiratory healthcare workers from 89 hospitals in Fujian Province, China. A self-designed electronic questionnaire was used to collect data on smoking status, knowledge of smoking hazards, and smoking cessation knowledge. Descriptive statistics were calculated for all questions. Logistic regression analysis was used to explore the relationship between awareness of the tobacco control goals of Healthy China 2030 and demographic characteristics. RESULTS: Among the healthcare workers surveyed, 3.4% were smokers, all of whom were male. Most respondents (99.4%) were aware of smoking as a cause of lung cancer, but awareness of smoking as a cause of non-respiratory cancer was lower. The awareness rate of smoking cessation support was high (>90%), but only 40.0% of participants were aware of the Healthy China 2030 tobacco control targets. Male (HR=2.16; 95% CI: 1.69-2.80) and participation in the cessation clinic (HR=1.47; 95% CI: 1.10-1.96) were associated with higher awareness of the targets. CONCLUSIONS: Respiratory healthcare workers in Fujian Province demonstrated a high level of awareness regarding behavioral and pharmacotherapy support for smoking cessation. In order to enable healthcare workers to play a more active role in tobacco control, there is a need to increase public awareness of smoking cessation services in Fujian Province.

ncRS: A resource of non-coding RNAs in sepsis.

Sepsis, a life-threatening condition triggered by the body's response to infection, presents a significant global healthcare challenge characterized by disarrayed host responses, widespread inflammation, organ impairment, and heightened mortality rates. This study introduces the ncRS database (http://www.ncrdb.cn), a meticulously curated repository housing 1144 experimentally validated non-coding RNAs (ncRNAs) intricately linked with sepsis. ncRS offers comprehensive RNA data, exhaustive experimental insights, and integrated annotations from diverse databases. This resource empowers researchers and clinicians to decipher ncRNAs' roles in sepsis pathogenesis, potentially identifying vital biomarkers for early diagnosis and prognosis, thus facilitating personalized treatments.

Longitudinal analysis of quality of life in primary lung cancer patients with chlamydia pneumoniae infection: a time-to-deterioration model.

BACKGROUND: Chlamydia pneumoniae (Cpn) IgG and IgA has been strongly linked to lung cancer, but its impact on patients' quality of life remains unclear. Our objective was to investigate the relationship between pre-treatment Cpn IgG and IgA and time to deterioration (TTD) of the HRQoL in patients with primary lung cancer. METHODS: A prospective hospital-based study was conducted from June 2017 to December 2018, enrolling 82 patients with primary lung cancer admitted to the First Affiliated Hospital of Fujian Medical University for questionnaire surveys. Cpn IgG and IgA was detected by microimmunofluorescence method. HRQoL was assessed at baseline and during follow-up using the EORTC Quality of Life Questionnaire version 3.0 (EORTC QLQ-C30) and EORTC Quality of Life Questionnaire-Lung Cancer (EORTC QLQ-LC13). HRQoL scores were calculated using the QoLR package, and TTD events were determined (minimum clinically significant difference = 5 points). Cox regression analysis was used to evaluate the effect of Cpn IgG and IgA on HRQoL. RESULTS: We investigated the relationship between Cpn IgG and IgA and quality of life in patients with primary lung cancer. The study was found that 75.61% of cases were Cpn IgG + and 45.12% were Cpn IgA + . Cpn IgA + IgG + was 41.46%. For EORTC QLQ-C30, Physical function (PF) and Pain (PA) TTD events on the functional scale and Symptom scale were the most common during follow-up. After adjusting for gender and smoking status, Pre-treatment Cpn IgA + was found to signifcantly delay TTD of Physical functioning(HR = 0.539, 95% CI: 0.291-0.996, P = 0.048). In addition, Cpn IgG + before treatment significantly delayed TTD in Emotional functioning (HR = 0.310, 95% CI: 0.115-0.836, P = 0.021). For EORTC QLQ-LC13, deterioration of dyspnea (LC-DY) was the most common event. However, Cpn IgG and IgA before treatment had no effect on the TTD of EORTC QLQ-LC13 items. CONCLUSIONS: According to EORTC QLQ-C30 and EORTC QLQ-LC13, Cpn IgA delayed TTD in Physical functioning and Cpn IgG delayed TTD in Emotional functioning.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China.

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 µg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

Interactions of particulate matter with temperature, heat index and relative humidity on pediatric hand, foot, and mouth disease in a subtropical city.

The associations of hand, foot, and mouth disease (HFMD) with meteorological variables and particulate matter (PM) remain controversial, and limited evidence is available on heat index (HI) and coarse particulate (PM10-2.5). Moreover, temperature and humidity are considered major risk factors but their interaction with PM remains unclear. We combined the distributed lag non-linear and quasi-Poisson models to estimate the non-linear and lagged associations of meteorological variables and PM with HFMD based on reported HFMD during 2015-2019 in Fuzhou, China. The multiplicative term of interaction was used to explore the relationship between HFMD and meteorological variables or PM at different levels of another variable. Stratified analyses were used to identify vulnerable subpopulations. We observed inverted-V-shaped relationships between HFMD and temperature and HI, and the W- and N-shaped for relative humidity (RH) and PM, respectively. Extreme high (i.e., the 95th percentile) temperature, HI and RH increased the HFMD with relative risks (RR) of 4.00 (95% confidence interval, 2.79-5.75), 2.20 (1.71-2.83) and 1.54 (1.35-1.75) referent to the minimum effect value of 10.3 °C, 69.4 and 54.8%, respectively. Higher concentrations of PM rapidly increased the HFMD. Infants under 2 years suffered more from temperature, HI and PM. There were synergistic effects between meteorological variables and PM on HFMD. For instance, the RRs of temperature (30 °C) and RH (40%) on HFMD increased from 3.68 (2.24-6.06) to 6.44 (4.29-9.66) and from 0.45 (0.14-1.47) to 2.15 (0.90-5.12) at low (<25%) and high (>75%) categories of PM2.5, respectively. While the RRs of 70 µg/m3 of PM10 and PM10-2.5 increased from 0.65 (0.32-1.31) to 2.93 (1.63-5.26) and from 0.86 (0.23-3.21) to 3.26 (1.23-8.62) at low and high categories of HI. These findings are essential for the development a prediction and warning systems and prevention and control strategies for HFMD.

Nonlinear back-end optimization method for VSLAM with multi-convex combined maximum correntropy criterion.

Back-end optimization plays a key role in eliminating the accumulated error in Visual Simultaneous Localization And Mapping (VSLAM). Existing back-end optimization methods are usually premised on the Gaussian noise assumption which does not always hold true due to the non-convex nature of the image and the fact that non-Gaussian noises are often encountered in real scenes. In view of this, we propose a back-end optimization method based on Multi-Convex combined Maximum Correntropy Criterion (MCMCC). A MCMCC-based cost function is first tailored for nonlinear back-end optimization in the context of VSLAM and the optimization problem is solved through Levenberg-Marquardt algorithm iteratively. Then, the proposed method is applied to ORB-SLAM3 to test its performance on public indoor and outdoor datasets. The real time performance is also validated using a RaceBot platform in real indoor and outdoor environments. In addition, the reprojection error is statistically analyzed to demonstrate the non-Gaussian characteristics in the back-end optimization process. Finally, the suggestion parameters are also provided through experiments for further study.

Relationship between cancer stem cell-related SNPs and survival outcomes in patients with primary lung cancer.

BACKGROUND: Cancer stem cells may be the source of cancer-causing mutant cells and are closely related to the prognosis of cancer. Our study aimed to investigate the potential association between single-nucleotide polymorphisms (SNPs) of cancer stem cell-related genes and the prognosis of lung cancer patients. METHODS: The SNP loci were genotyped by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), and the overall survival of subjects was analyzed by log-rank test after stratifying and adjusting their demographic data, clinical data, and genotypes. The correlation between survival time and quality of life of lung cancer under codominant, dominant, recessive, and additive genetic models was analyzed by the Cox regression model. The association between SNP polymorphism and the prognosis of lung cancer was analyzed by Stata16.0 software, and their heterogeneity was tested. Interaction analysis was performed using R software (version 4.2.0). RESULTS: Stratified analysis unveiled that rs3740535 had recessive AA genotype and additive GG genotype; Rs3130932 dominant GT + GG genotype, additive TT genotype; Rs13409 additive TT genotype; Rs6815391 recessive CC genotype and additional TT genotype were associated with increased risk of lung cancer death. Rs3130932 recessive GG genotype was associated with a reduced risk of lung cancer death. CONCLUSION: Rs3740535, rs3130932, rs13409, and rs6815391 are associated with the overall survival of lung cancer patients and may be valuable for the prognosis of lung cancer patients.

Fault detection for NOx emission process in thermal power plants using SIP-PCA.

With the era of big data, data-driven models are increasingly vital to just-in-time decision support in pollution emission management and planning. This article aims to evaluate the usability of the proposed data-driven model to monitor NOx emission from a coal-fired boiler process using easily measured process variables. As the emission process is highly complex, process variables interact with each other, and they cannot guarantee that all the variables in the actual operation obey the Gaussian distributions. As conventional principal component analysis (PCA) can only extract variance information, a novel data-driven model is proposed, called survival information potential-based PCA (SIP-PCA) model, is proposed in this work. First, an improved PCA model is established based on the SIP performance index. SIP-PCA can extract more information in the latent space from the process variables following the non-Gaussian distributions. Then, the control limits for fault detection are determined based on the kernel density estimation method. Finally, the proposed algorithm is successfully applied to a real NOx emission process. By monitoring the operation of process variables, possible failures can be detected as soon as possible. Fault isolation and system reconstruction can be implemented in time, preventing NOx emissions from exceeding its standard.

Visual analysis of the prevention and control measures of COVID-19 in Chinese ports.

In 2022, COVID-19 solutions in China have entered a normal stage, and the solutions imported from ports have been transformed from emergency prevention and control measures to investigative long-term prevention and control measures. Therefore, it is necessary to study solutions for COVID-19 at border ports. In this study, 170 research papers related to the prevention and control measures of COVID-19 at ports from 2020 to September 2022 were retrieved from Wanfang database, HowNet database, Wip database, and WoS core collection. Citespace 6.1.R2 software was used to research institutions visualize and analyze researchers and keywords to explore their research hotspots and trends. After analysis, the overall volume of documents issued in the past 3 years was stable. The major contributors are scientific research teams such as the Chinese Academy of Inspection and Quarantine Sciences (Han Hui et al.) and Beijing Customs (Sun Xiaodong et al.), with less cross-agency cooperation. The top five high-frequency keywords with cumulative frequency are as follows: COVID-19 (29 times), epidemic prevention and control (29 times), ports (28 times), health quarantine (16 times), and risk assessment (16 times). The research hotspots in the field of prevention and control measures for COVID-19 at ports are constantly changing with the progress of epidemic prevention and control. Cooperation between research institutions needs to be strengthened urgently. The research hotspots are the imported epidemic prevention and control, risk assessment, port health quarantine, and the normalized epidemic prevention and control mechanism, which is the trend of research and needs further exploration in the future.

Effect of Low-Temperature Plasma Surface Treatment on Bonding Properties of Single-Lap Joint of Thermosetting Composites.

Bonding is one of the main forms of composite bonding. In order to investigate the effect of low-temperature plasma surface treatment on the bonding properties of carbon fiber-reinforced epoxy resin composites (CF/EP), a single-lap joint of CF/EP was prepared. The surface of the CF/EP was treated with atmospheric pressure "low-temperature plasma spray" equipment, and the tensile shear strength, surface morphology, surface contact angle and surface chemical composition of the CF/EP before and after plasma treatment were characterized. Finally, the samples were treated with traditional sandblasting, compared and analyzed. The results show that the effect of low-temperature plasma surface treatment on CF/EP joints is better than that of traditional sandblasting treatment. After low-temperature plasma surface treatment, the tensile shear strength of the CF/EP single-lap joint increased by 119.59% at most, and the failure form of the joint changed from untreated interface failure to mixed failure dominated by cohesion failure. Plasma can etch the surface of composite materials, the mechanical interlock between the carbon fiber and glue is enhanced and the bonding performance of the composite is improved. In addition, after low-temperature plasma surface treatment, the introduction of a large number of oxygen-containing active groups such as C-O and C=O can increase the surface free energy, reduce the contact angle and improve the surface activity and wettability of the composites. However, too long a treatment time will lead to excessive plasma etching of carbon fibers, thus weakening the active effect of the oxygen-containing active groups on the surface of the composites, and the surface wettability is no longer improved, but the adhesive properties of CF/EP are reduced. This paper plays a guiding role in the bonding technology of composite materials.

ECLNet: Center localization of eye structures based on Adaptive Gaussian Ellipse Heatmap.

Accurately localizing the center of specific biological structures in medical images is of great significance for clinical treatment. The center localization task can be viewed as an estimation problem of keypoints, and the heatmap is often used to describe the probability of the location of keypoints during estimation. Existing methods construct the heatmap from a Gaussian kernel function with a fixed standard deviation, therefore cannot adapt to morphologic changes of the target region. In this paper, we build a deep network, ECLNet, to localize the center of eye-related structures in medical images. Meanwhile, we propose a method called Adaptive Gaussian Ellipse Heatmap (AGEH), which can efficiently utilize the gradient feature of the target region to adjust the morphology of the heatmap. The ECLNet localizes the optic disc and fovea center with mean Euclidean Distance of 17.995 and 39.446 pixels, respectively, for IDRiD dataset. The ECLNet also successfully localizes the eye center with the mean absolute Position Error of 0.186±0.027 mm for CATARACT dataset. The results show that our proposed method has a better performance compared with some state-of-the-art methods.

A cyclodextrin-based turn-off fluorescent probe for naked-eye detection of copper ions in aqueous solution.

A novel fluorescent probe L consisting of ß-Cyclodextrin (ß-CD) and thiosemicarbazide moieties was designed for copper ions detection. Apparent fluorescence quenching of probe L in Tris-HCl（pH = 7.4）solution was observed only in the presence of Cu2+, among other interfering ions. The present probe L was 1:1 complexed with Cu2+ and the detection limit of probe L was calculated to be 1.37 µM. The results demonstrate that the probe L may provide a convenient method for visual detection of Cu2+ in the environmental and biological systems.

Association between physical activity and health-related quality of life: time to deterioration model analysis in lung adenocarcinoma.

BACKGROUND AND PURPOSE : Health-related quality of life (HRQoL) is a key aspect of care for cancer survivors that can be improved by physical activity. Our aim was to explore the relationship between physical activity and time to deterioration (TTD) of the HRQoL in patients with lung adenocarcinoma (LUAD). METHODS: We conducted a hospital-based prospective study. The International Physical Activity Questionnaire long-form (IPAQ-L) was used to investigate the pre-treatment physical activity levels, and the EORTC Quality of Life Questionnaire version 3.0 (EORTC QLQ-C30) and EORTC Quality of Life Questionnaire-Lung Cancer (EORTC QLQ-LC13) were used to assess HRQoL at baseline and during follow-up. The QoLR package was used to calculate the HRQoL scores and determine TTD events (minimal clinically important difference=5 points). The effect of physical activity on the HRQoL was assessed using Cox regression analysis. RESULTS: For EORTC QLQ-C30, TTD events of physical functioning (PF) and dyspnea (DY) in functional scales and symptom scales were the most common during follow-up. Pre-treatment physical activity was found to significantly delay TTD of insomnia (HR=0.635, 95%CI: 0.437-0.922, P=0.017) and diarrhea (HR=0.475, 95%CI: 0.291-0.774, P=0.003). For EORTC QLQ-LC13 scales, deterioration of dyspnea (LC-DY) was the most common event. Physical activity was found to delay the TTD of dyspnea (HR=0.654, 95%CI: 0.474-0.903, P=0.010), sore mouth (HR=0.457, 95%CI: 0.244-0.856, P=0.015), and dysphagia (HR=0.315, 95%CI: 0.172-0.580, P<0.001). CONCLUSIONS: Pre-treatment physical activity of LUAD patients may delay the TTD of multiple HRQoL indicators in EORTC QLQ-C30 and EORTC QLQ-LC13. IMPLICATION FOR CANCER SURVIVORS: Health-related quality of life (HRQoL) is a key aspect of care for cancer survivors (someone who is living with or beyond cancer), that can be improved by physical activity. Our aim was to explore the relationship between physical activity and time to deterioration (TTD) of the HRQoL in patients with lung adenocarcinoma (LUAD).

Induced Mutation in GmCOP1b Enhances the Performance of Soybean under Dense Planting Conditions.

CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1) is the key photomorphogenic inhibitor that has been extensively studied in higher plants. Nevertheless, its role has not been documented in the economically important soybean. Here we investigated the functions of two COP1 homologous genes, GmCOP1a and GmCOP1b, by analyzing Gmcop1a and Gmcop1b mutants with indels using CRISPR in soybean. We revealed that, although both genes are required for skotomorphogenesis in the dark, the GmCOP1b gene seems to play a more prominent role than GmCOP1a in promoting stem elongation under normal light conditions. Consistently, the bZIP transcriptional factors STF1/2, which repress stem elongation in soybean, accumulated to the highest level in the Gmcop1a1b double mutant, followed by the Gmcop1b and Gmcop1a mutants. Furthermore, the Gmcop1b mutants showed reduced shade response and enhanced performance under high-density conditions in field trials. Taken together, this study provides essential genetic resources for elucidating functional mechanisms of GmCOP1 and breeding of high yield soybean cultivars for future sustainable agriculture.

Construction of an immune-related lncRNA signature pair for predicting oncologic outcomes and the sensitivity of immunosuppressor in treatment of lung adenocarcinoma.

BACKGROUND: Although immunotherapy has shown clinical activity in lung adenocarcinoma (LUAD), LUAD prognosis has been a perplexing problem. We aimed to construct an immune-related lncRNA pairs (IRLPs) score for LUAD and identify what immunosuppressor are appropriate for which group of people with LUAD. METHODS: Based on The Cancer Genome Atlas (TCGA)-LUAD cohort, IRLPs were identified to construct an IRLPs scoring system by Cox regression and validated in the Gene Expression Omnibus (GEO) dataset using log-rank test and the receiver operating characteristic curve (ROC). Next, we used spearman's correlation analysis, t-test, signaling pathways analysis and gene mutation analysis to explore immune and molecular characteristics in different IRLP subgroups. The "pRRophetic" package was used to predict the sensitivity of immunosuppressant. RESULTS: The IRLPs score was constructed based on eight IRLPs calculated as 2.12 × (MIR31HG|RRN3P2) + 0.43 × (NKX2-1-AS1|AC083949.1) + 1.79 × (TMPO-AS1|LPP-AS2) + 1.60 × (TMPO-AS1|MGC32805) + 1.79 × (TMPO-AS1|PINK1-AS) + 0.65 × (SH3BP5-AS1|LINC01137) + 0.51 × (LINC01004|SH3PXD2A-AS1) + 0.62 × (LINC00339|AGAP2-AS1). Patients with a lower IRLPs risk score had a better overall survival (OS) (Log-rank test P TCGA train dataset < 0.001, P TCGA test dataset = 0.017, P GEO dataset = 0.027) and similar results were observed in the AUCs of TCGA dataset and GEO dataset (AUC TCGA train dataset = 0.777, AUC TCGA test dataset = 0.685, AUC TCGA total dataset = 0.733, AUC GEO dataset = 0.680). Immune score (Cor = -0.18893, P < 0.001), stoma score (Cor = -0.24804, P < 0.001), and microenvironment score (Cor = -0.22338, P < 0.001) were significantly decreased in the patients with the higher IRLP risk score. The gene set enrichment analysis found that high-risk group enriched in molecular changes in DNA and chromosomes signaling pathways, and in this group the tumor mutation burden (TMB) was higher than in the low-risk group (P = 0.0015). Immunosuppressor methotrexate sensitivity was higher in the high-risk group (P = 0.0052), whereas parthenolide (P < 0.001) and rapamycin (P = 0.013) sensitivity were lower in the high-risk group. CONCLUSIONS: Our study established an IRLPs scoring system as a biomarker to help in the prognosis, the identification of molecular and immune characteristics, and the patient-tailored selection of the most suitable immunosuppressor for LUAD therapy.

Exploring Factors and Associate Responses for Anxiety in the Coronavirus Disease 2019 Pandemic: A Web-Based Survey in Japan.

Background and Objectives: Anxiety plays an important role in psychology. An exploration of anxiety and its associated reactions may provide insight into measures for addressing mental health problems caused by the coronavirus disease 2019 (COVID-19) pandemic. Data from this study provide potential correlational responses to anxiety. Methods: A cross-sectional study using data collected via an online self-reported questionnaire was conducted in Japan during the COVID-19 pandemic. Using the State-Trait Anxiety Inventory (STAI-6), we assessed anxiety levels and explored the relationship between anxiety STAI-6 score, sources of COVID-19 information, the influences of COVID-19, social anxiety symptoms, discrimination, and evaluation of the government. Results: A total of 4,127 participants were included in the analysis. The level of anxiety was not equally distributed across the general population with respect to age, gender, educational level, occupation, income, presence of underlying disease, and location (p < 0.05). The number of sources of information on COVID-19 had a positive correlation with the STAI-6 score (Spearman's rho = 0.176, p < 0.001). The influence of the pandemic was correlated with moderate-severe anxiety. A high level of anxiety added to social anxiety (Spearman's rho = 0.04, p < 0.05) and discriminatory behavior (Spearman's rho = 0.11, p < 0.01). Being female (Estimate = 0.926) and from a non-emergency area (Estimate = -0.308) was related to higher STAI scores, and higher education (Estimate = -0.305), and income (Estimate = -0.168) decreased the STAI score. The respondents who had a lower evaluative score of the preventive activities undertaken by the national and local governments had higher STAI-6 scores. Conclusion: Our findings provide statistical evidence for the associated reaction of anxiety and that anxiety reactions may vary in predictable ways. Further studies should focus on the strategic interventions that may decrease the associated responses to anxiety, to address mental health issues due to the pandemic.

GmCRY1s modulate gibberellin metabolism to regulate soybean shade avoidance in response to reduced blue light.

Soybean is an important legume crop that displays the classic shade avoidance syndrome (SAS), including exaggerated stem elongation, which leads to lodging and yield reduction under density farming conditions. Here, we compared the effects of two shade signals, low red light to far-red light ratio (R:FR) and low blue light (LBL), on soybean status and revealed that LBL predominantly induces excessive stem elongation. We used CRISPR-Cas9-engineered Gmcry mutants to investigate the functions of seven cryptochromes (GmCRYs) in soybean and found that the four GmCRY1s overlap in mediating LBL-induced SAS. Light-activated GmCRY1s increase the abundance of the bZIP transcription factors STF1 and STF2, which directly upregulate the expression of genes encoding GA2 oxidases to deactivate GA1 and repress stem elongation. Notably, GmCRY1b overexpression lines displayed multiple agronomic advantages over the wild-type control under both dense planting and intercropping conditions. Our study demonstrates the integration of GmCRY1-mediated signals with the GA metabolic pathway in the regulation of LBL-induced SAS in soybean. It also provides a promising option for breeding lodging-resistant, high-yield soybean cultivars in the future.

Short-term prediction of urban PM2.5 based on a hybrid modified variational mode decomposition and support vector regression model.

PM2.5 (particulate matter with a size/diameter ≤ 2.5 µm) is an important air pollutant that affects human health, especially in urban environments. However, as time-series data of PM2.5 are non-linear and non-stationary, it is difficult to predict future PM2.5 distribution and behavior. Therefore, in this paper, we propose a hybrid short-term urban PM2.5 prediction model based on variational mode decomposition modified by the correntropy criterion, the state transition simulated annealing (STASA) algorithm, and a support vector regression model to overcome the disadvantages of traditional forecasting techniques which consider different environmental factors. Two experiments were performed with the model to assess its effectiveness and predictive ability: in experiment I, we verified the performance of STASA on benchmark functions, while in experiment II, we used PM2.5 data from different epochs and regions of Beijing to verify its forecasting performance. The experimental results showed that the proposed model is robust and can achieve satisfactory prediction results under different conditions compared with current forecasting techniques.

Effective Melanoma Recognition Using Deep Convolutional Neural Network with Covariance Discriminant Loss.

Melanoma recognition is challenging due to data imbalance and high intra-class variations and large inter-class similarity. Aiming at the issues, we propose a melanoma recognition method using deep convolutional neural network with covariance discriminant loss in dermoscopy images. Deep convolutional neural network is trained under the joint supervision of cross entropy loss and covariance discriminant loss, rectifying the model outputs and the extracted features simultaneously. Specifically, we design an embedding loss, namely covariance discriminant loss, which takes the first and second distance into account simultaneously for providing more constraints. By constraining the distance between hard samples and minority class center, the deep features of melanoma and non-melanoma can be separated effectively. To mine the hard samples, we also design the corresponding algorithm. Further, we analyze the relationship between the proposed loss and other losses. On the International Symposium on Biomedical Imaging (ISBI) 2018 Skin Lesion Analysis dataset, the two schemes in the proposed method can yield a sensitivity of 0.942 and 0.917, respectively. The comprehensive results have demonstrated the efficacy of the designed embedding loss and the proposed methodology.

The prevalence and influencing factors in anxiety in medical workers fighting COVID-19 in China: a cross-sectional survey.

The coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2 virus) has been sustained in China since December 2019, and has become a pandemic. The mental health of frontline medical staff is a concern. In this study, we aimed to identify the factors influencing medical worker anxiety in China during the COVID-19 outbreak. We conducted a cross-sectional study to estimate the prevalence of anxiety among medical staff in China from 10 February 2020 to 20 February 2020 using the Zung Self-rating Anxiety Scale (SAS) to assess anxiety, with the criteria of normal (⩽49), mild (50-59), moderate (60-70) and severe anxiety (⩾70). We used multivariable linear regression to determine the factors (e.g. having direct contact when treating infected patients, being a medical staff worker from Hubei province, being a suspect case) for anxiety. We also used adjusted models to confirm independent factors for anxiety after adjusting for gender, age, education and marital status. Of 512 medical staff in China, 164 (32.03%) had had direct contact treating infected patients. The prevalence of anxiety was 12.5%, with 53 workers suffering from mild (10.35%), seven workers suffering from moderate (1.36%) and four workers suffering from severe anxiety (0.78%). After adjusting for sociodemographic characteristics (gender, age, education and marital status), medical staff who had had direct contact treating infected patients experienced higher anxiety scores than those who had not had direct contact (ß value = 2.33, confidence interval (CI) 0.65-4.00; P = 0.0068). A similar trend was observed in medical staff from Hubei province, compared with those from other parts of China (ß value = 3.67, CI 1.44-5.89; P = 0.0013). The most important variable was suspect cases with high anxiety scores, compared to non-suspect cases (ß value = 4.44, CI 1.55-7.33; P = 0.0028). In this survey of hospital medical workers during the COVID-19 outbreak in China, we found that study participants experienced anxiety symptoms, especially those who had direct clinical contact with infected patients; as did those in the worst affected areas, including Hubei province; and those who were suspect cases. Governments and healthcare authorities should proactively implement appropriate psychological intervention programmes, to prevent, alleviate or treat increased anxiety.