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.

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.

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.

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.

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.

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.

SIP-Based Single Neuron Stochastic Predictive Control for Non-Gaussian Networked Control Systems with Uncertain Metrology Delays.

In this paper, a novel data-driven single neuron predictive control strategy is proposed for non-Gaussian networked control systems with metrology delays in the information theory framework. Firstly, survival information potential (SIP), instead of minimum entropy, is used to formulate the performance index to characterize the randomness of the considered systems, which is calculated by oversampling method. Then the minimum values can be computed by optimizing the SIP-based performance index. Finally, the proposed strategy, minimum entropy method and mean square error (MSE) are applied to a networked motor control system, and results demonstrated the effectiveness of the proposed strategy.

An Ameliorated Prediction of Drug-Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features.

The prediction of drug-target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper, we propose a kind of drug-target interactions predictor adopting multi-scale discrete wavelet transform and network features (named as DAWN) in order to solve the DTIs prediction problem. We encode the drug molecule by a substructure fingerprint with a dictionary of substructure patterns. Simultaneously, we apply the discrete wavelet transform (DWT) to extract features from target sequences. Then, we concatenate and normalize the target, drug, and network features to construct feature vectors. The prediction model is obtained by feeding these feature vectors into the support vector machine (SVM) classifier. Extensive experimental results show that the prediction ability of DAWN has a compatibility among other DTI prediction schemes. The prediction areas under the precision-recall curves (AUPRs) of four datasets are 0 . 895 (Enzyme), 0 . 921 (Ion Channel), 0 . 786 (guanosine-binding protein coupled receptor, GPCR), and 0 . 603 (Nuclear Receptor), respectively.

[Spectrum-Effect Relationship of GualouXiebai Dropping Pills on Myocardial Ischemia].

OBJECTIVE: To study the relationship between HPLC characteristic spectrum and pharmacodynamics on anti-myocardial ischemia of GualouXiebai dropping pills. METHODS: HPLC characteristic spectrum of GualouXiebai dropping pills was established, dropping pills were divided into five dose groups (3.75, 11.25, 22.5, 33.75 and 45 g/kg, equivalent to the crude herb g/kg), the mice were orally administered dropping pills once daily for 7 d, 90 min after the mice were given by intraperitoneal injection of isoprenaline to establish myocardial ischemia models, the level of CK in blood plasma were detected; Then, the correlation between characteristic spectrum and biochemical index CK was studied by grey relational analysis method. RESULTS: The correlation between each common peak and CK had gradually increased with the dose increased from 3.73 g/kg to 33.75 g/kg, but when the dose reached to 45 g/kg, the correlation between each common peak and CK had decreased. The variation trends of correlation of spectrum-effect relationship for different dose were similar,but the correlation variation trend of the efficacy on the No. 8 peak in 33.75 g/kg group with the other four groups in the opposite, the change trends of the No. 11 peak in 22.5 g/kg group, the No. 24 peak in 33. 75 g/kg group and the No. 37 peak in 45 g/ kg group with 3.75 g/kg group and 11.25 g/kg group on the contrary. The relational orders of spectrum-effect relationship were not consistent, respectively( the first 15 peaks) :11 > 37 > 24 > 30 > 8 > 21 > 2 > 16 > 1 > 3 > 20 > 15 > 12 > 19 > 7;11 > 37 > 30 > 8 > 21 > 24 > 2 > 1 > 16 > 3 > 27 > 12 > 22 > 20 >10; 8 > 30 > 1 > 2 > 21 > 27 > 31 > 22 > 16 > 12 > 3 > 10 > 9 > 20 > 4; 1 > 2 > 27 > 21 > 31 > 22 > 12 > 16 > 9 > 3 > 10 > 4 > 17 > 30 > 20; 8 > 30 > 1 > 2 > 2 > 2 > 7 > 31 > 22 > 16 > 12 > 3 > 9 > 10 > 20 > 17. CONCLUSION: Anti-myocardial ischemia effect of GualouXiebai dropping pills comes from the synergistic or antagonistic effect among various active ingredients related to the dose. With the difference of the dosage, the relational orders of chemical components to play the role is not the same, but the main components to play a pharmacodynamic of five dose groups are consistent,the existence of the component groups lay a foundation for further study of GualouXiebai dropping pills.

Artificial intelligence and job performance of healthcare providers in China.

Introduction: This study explores the influence of artificial intelligence (A.I.) applications on the job performance of healthcare providers, based on data from standardised-trained residents in the First People's Hospital of Yunnan Province in China. Methods: The ordinary least squares model is employed to examine the relationship between A.I. applications and job performance. To address potential endogeneity and missing variables, we utilise the propensity score matching method and alternative regression models. Results: The findings indicate that the job performance of standardised-trained residents positively correlates with A.I. applications. This relationship remains robust after addressing endogenous and missing variables. Further discussion reveals that patients' support mediates the relationship between A.I. and job performance. Under identical conditions, the job performance of female residents empowered by A.I. is found to be significantly better than that of their male counterparts. Conversely, no heterogeneity is observed regarding the impact of A.I. on the job performance of medical practitioners and clinical medical technicians. Discussion: This study underscores the positive role of A.I. applications in enhancing the job performance of standardised-trained residents. The results highlight the mediating role of patient support and suggest gender-based differences in the efficacy of A.I. empowerment.

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.

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.

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.

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.

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.

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.

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).