Efficacy of respiratory support therapies during pulmonary rehabilitation exercise training in chronic obstructive pulmonary disease patients: a systematic review and network meta-analysis.

BACKGROUND: Exercise training is fundamental in pulmonary rehabilitation (PR), but patients with chronic obstructive pulmonary disease (COPD) often struggle with exercise intolerance. Respiratory support during exercise in COPD patients may be a beneficial adjunct therapy. In this study, the effect of different respiratory support therapy during pulmonary rehabilitation exercise training in COPD patients was assessed through a network meta-analysis. METHODS: Five databases were searched to obtain randomized controlled trials involving different respiratory support therapies during PR exercise training in COPD patients. The Cochrane Handbook tool was employed to assess the risk bias of included studies. Network meta-analysis was performed using the STATA software. The study protocol was registered at PROSPERO (CRD42023491139). RESULTS: A total of 35 studies involving 1321 patients and 6 different interventions were included. Network meta-analysis showed that noninvasive positive pressure ventilation (NPPV) is superior in improving exercise capacity (6-Minute Walk Test distance, peak work rate, endurance time), dyspnea, and physiological change (peak VO2, tidal volume, minute ventilation and lactate level) in stable COPD patients who were at GOLD stage III or IV during PR exercise training. The final surface under the cumulative ranking curve value indicated that NPPV therapy achieved the best assistive rehabilitation effect. CONCLUSIONS: The obtained results indicate that NPPV is most powerful in assisting exercise in severe COPD patients under stable condition. Researchers should focus more on the safety, feasibility, and personalization of interventions. Furthermore, there is a need for additional high-quality trials to assess the consistency of evidence across various respiratory support approaches. TRIAL REGISTRATION: The study was registered at PROSPERO (CRD42023491139).

Long noncoding RNA PM maintains cerebellar synaptic integrity and Cbln1 activation via Pax6/Mll1-mediated H3K4me3.

Recent studies have shown that long noncoding RNAs (lncRNAs) are critical regulators in the central nervous system (CNS). However, their roles in the cerebellum are currently unclear. In this work, we identified the isoform 204 of lncRNA Gm2694 (designated as lncRNA-Promoting Methylation (lncRNA-PM)) is highly expressed in the cerebellum and derived from the antisense strand of the upstream region of Cerebellin-1 (Cbln1), a well-known critical cerebellar synaptic organizer. LncRNA-PM exhibits similar spatiotemporal expression pattern as Cbln1 in the postnatal mouse cerebellum and activates the transcription of Cbln1 through Pax6/Mll1-mediated H3K4me3. In mouse cerebellum, lncRNA-PM, Pax6/Mll1, and H3K4me3 are all associated with the regulatory regions of Cbln1. Knockdown of lncRNA-PM in cerebellum causes deficiencies in Cbln1 expression, cerebellar synaptic integrity, and motor function. Together, our work reveals an lncRNA-mediated transcriptional activation of Cbln1 through Pax6-Mll1-H3K4me3 and provides novel insights of the essential roles of lncRNA in the cerebellum.

The association between green space around schools, screen time for entertainment, and adolescent depressive symptoms: A nationwide study from China.

BACKGROUND: Natural green environments are beneficial to people's mental health, while too much screen time may be harmful to adolescents' mental health. However, it is not clear how green spaces and screen time affect mental health together in adolescents. METHODS: A total of 22,868 adolescents were recruited from October to December 2021 in eight cities in China, through multistage cluster sampling. The Patient Health Questionnaire (PHQ-9) was used to investigate adolescents' depressive symptoms, and the Normalised Vegetation Index for the 200m, 500m and 1000m buffer zones around the school represents the green cover around the school. We used binary logistic regression to analyse the association between green space, screen time and depressive symptoms. RESULTS: In fully adjusted models, the highest quartile of NDVI in the 200m, 500m and 1000m buffer zones around the school was a protective factor for depressive symptoms. For less than 2 h of recreational screen time, the highest quartiles of the NDVI and the association with depressive symptoms were negatively correlated for the 200m, 500m and 1000m buffer zones (NDVI200: 0.904(0.848-0.964)), NDVI500: 0.863(0.808-0.921), NDVI1000: 0.862(0.808-0.920)). The highest quartiles of NDVI in all buffers were not associated with depressive symptoms when the screen time was >2 h. The association between green space and depressive symptoms at lower recreational screen time was observed to be stronger in the group of adolescents with a lower family economic status (NDVI200: 0.780(0.695-0.876), NDVI500: 0.838(0.748-0.938), NDVI1000: 0.783(0.698-0.879)). No potential gender differences were observed. CONCLUSIONS: For adolescents with less than 2 h of recreational screen time per day, the greenery around the school had a protective effect on their mental health, especially for adolescents from economically disadvantaged families. Green spaces around schools are significant in improving health inequities.

Novel ethylenediamine-ß-cyclodextrin grafted membranes for the chiral separation of mandelic acid and its derivatives.

In the present study, flat cellulose acetate ultrafiltration membranes were prepared first by nonsolvent induced phase separation method. Then chiral membranes for separating the enantiomers were prepared by grafting the ultrafiltration membranes using ethylenediamine-ß-cyclodextrin as the chiral selector and epichlorohydrin as the spacer arm. The pure water permeability of the ultrafiltration membrane was around 115 L·m-2·h-1·bar-1. The properties of the chiral membranes were characterized using infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The chiral membrane performance in enantiomer separation was evaluated with racemates, such as mandelic acid (MA), 2-chloromandelic acid (2-ClMA), 4-chloromandelic acid (4-ClMA), and methyl mandelate (MM). The influence of feed concentration on the separation efficiency was also investigated. The results indicated that the enantiomeric excess percentages (e.e%) of the racemic mixtures for these four chiral compounds were up to 31.8%, 25.4%, 17.8%, and 32.6%, respectively. The binding free energy of the chiral selector with the (S)-enantiomer calculated by molecular dynamics simulations was stronger than that with the (R)-enantiomer, which was consistent with the experimental results (higher concentration of (R)-enantiomer in the permeate). This supports the affinity absorption-separation mechanism.

Drug-Free Antimicrobial Nanomotor for Precise Treatment of Multidrug-Resistant Bacterial Infections.

Manufacturing heteronanostructures with specific physicochemical characteristics and tightly controllable designs is very appealing. Herein, we reported NIR-II light-driven dual plasmonic (AuNR-SiO2-Cu7S4) antimicrobial nanomotors with an intended Janus configuration through the overgrowth of copper-rich Cu7S4 nanocrystals at only one high-curvature site of Au nanorods (Au NRs). These nanomotors were applied for photoacoustic imaging (PAI)-guided synergistic photothermal and photocatalytic treatment of bacterial infections. Both the photothermal performance and photocatalytic activity of the nanomotors are dramatically improved owing to the strong plasmon coupling between Au NRs and the Cu7S4 component and enhanced energy transfer. The motion behavior of nanomotors promotes transdermal penetration and enhances the matter-bacteria interaction. More importantly, the directional navigation and synergistic antimicrobial activity of the nanomotors could be synchronously driven by NIR-II light. The marriage of active motion and enhanced antibacterial activity resulted in the expected good antibacterial effects in an abscess infection mouse model.

Sustainable flood control strategies under extreme rainfall: Allocation of flood drainage rights in the middle and lower reaches of the yellow river based on a new decision-making framework.

Climate change has exacerbated the frequency and magnitude of extreme rainfall, which has led to the perpetuation of flooding as a hazard to humans and society. China has begun to consider introducing Flood drainage rights (FDR), a sustainable flood control measure, into non-engineering measures as a complement to engineering measures for flood control. FDR represent the right of regions to discharge regional floodwaters caused by extreme rainfall into the river, and are the primary means of controlling the amount of floodwaters from regions when regional flood capacity is exceeded. However, existing studies on quantitative FDR allocation still have limitations, and some previous methods have resulted in allocation schemes that are not entirely reasonable and fair because they do not comprehensively consider the influencing factors of FDR or the allocation method is unreasonable. This paper explores the impact of flooding on rural and agricultural areas. We incorporate the factors of agricultural economy and security and construct a system of the allocation indicators of FDR composed of five principles: Natural Environmental Endowment, General Economic and Social Development, Agricultural Economy and Security, Macro policy regulation, and Respect for Historical Background. Second, considering the influence of expert judgment and data of different time nodes on the allocation of FDR, we introduce the concepts of expert weight and time weight into the allocation model of FDR, and construct a new set of framework for the allocation of FDR, i.e., "[(expert weight + subjective weight)+(time weight + objective weight)]+decision making model ". To reduce the loss of information during the transformation of subjective judgments, we also introduced triangular fuzzy numbers for the transformation between expert judgments and numbers. Finally, we take the five provinces in the middle and lower reaches of the Yellow River as an example. Using the data from 2010 to 2021, we obtain the final allocation scheme (proportion) of FDR as Henan (33.26%) > Shaanxi (23.08%) > Inner Mongolia (21.31%) > Shanxi (14.44%) > Shandong (7.91%). On this basis, this paper utilizes sensitivity analysis and comparative validation to demonstrate the rationality and effectiveness of the method, and identifies several indicators that have a greater impact on the results of the allocation of FDR. FDR can form part of a set of integrated flood management system together with flood control projects, which greatly alleviates the drainage conflicts arising from flooding caused by extreme precipitation. Under extreme rainfall conditions, FDR improves drainage efficiency and minimizes the overall damage caused by flooding in the watershed. This study can contribute to the sustainable development of the watershed and provide a reference for the promotion and utilization of sustainable flood control measures.

Reaction Process of Solid Waste Composite-Based Cementitious Materials for Immobilizing and Characterizing Heavy Metals in Lead and Zinc Tailings: Based on XRD, SEM-EDS and Compressive Strength Characterization.

This study investigates the synergistic effect and mechanism of gelling materials with blast furnace slag (BFS), steel slag (SS) and desulphurization gypsum (DG) as the main components on the hardening of heavy metal ions by lead and zinc tailings. It is found that lead and zinc tailing (LZT) is mainly composed of dolomite and quartz and contain small amounts of calcium, aluminum, iron, magnesium and other elements as well as heavy metals such as lead and zinc. By the mechanical activation method, it is found that the lead and zinc tailings powder has the largest specific surface area and the highest activity index when the ball milling time is 2 h. At a hardening timepoint of 28 d, the calcite crystals in the samples are intertwined with the amorphous C-S-H gel (C-S-H gels are mainly composed of 3CaO∙SiO2 and 2CaO∙SiO2), which enhances the structural strength of the samples. The chemical reaction analysis confirmed that the formation of calcite is a major driver for the hydration reaction of the steel slag-desulphurization gypsum (SSSDG) system. Overall, the slag, steel slag and desulphurization gypsum solid waste-based gelling materials have synergistic effects in hardening heavy metals by limiting the leaching of metal ions, adsorbing metal ions and hardening heavy metals, and facilitating the hydration process through the formation of compound salt precipitates.

Adsorption Potential, Speciation Transformation, and Risk Assessment of Hg-, Cd-, and Pb-Contaminated Soils Using Biochar in Combination with Potassium Dihydrogen Phosphate.

The objective of this study is to develop a remediation technology for composited heavy metal-contaminated soil. Biochars (BC300, BC400, and BC500) derived from corn were combined with potassium dihydrogen phosphate (KH2PO4) to immobilize and remove heavy metal ions, including mercury (Hg2+), cadmium (Cd2+), and lead (Pb2+). The adsorption kinetics of metal ions in aqueous solutions with different concentrations was tested, and the fitting effects of the two models were compared. The findings demonstrate that the joint application of biochar and KH2PO4 could markedly enhance the immobilization efficacy of Pb2+, whereas the utilization of KH2PO4 on its own exhibited a more pronounced immobilization impact on Cd2+. Furthermore, the present study underscores the shortcomings of various remediation techniques that must be taken into account when addressing heavy metal-contaminated soils. It also emphasizes the value of comprehensive remediation techniques that integrate multiple remediation agents. This study offers a novel approach and methodology for addressing the intricate and evolving challenges posed by heavy metal contamination in soil. Its practical value and potential for application are significant.

Steam explosion-assisted grinding improves the functional properties and antioxidant activity of Java tea-leaf powders (Clerodendranthus spicatus).

BACKGROUND: Java tea is widely consumed and has multiple health effects. This study established a steam explosion (SE) pretreatment method to prepare Java tea-leaf powders. The physicochemical, functional properties, phenolic extraction, and antioxidant activity of Java tea-leaf powders produced by simple and SE-assisted milling methods were investigated. RESULTS: In comparison with simple milling, SE pretreatment broke the cell wall effectively and reduced the particle size of Java tea-leaf powders. Steam explosion-treated powders showed higher values for sensory signals, bulk and tap density, and for the water solubility index. After SE treatment, the adsorption capacities to glucose, soybean oil, and cholesterol of leaf powders were increased by up to 55, 95, and 80% respectively. The extracts from SE-treated powders also showed higher total polyphenol content and antioxidant activity. CONCLUSION: Steam explosion treatment is helpful for the improvement of functional properties and antioxidant activity, which can benefit the development and application of Java tea-leaf powders. © 2024 Society of Chemical Industry.

Chemical modification, structure elucidation and antifungal mechanism studies of a peptide extracted from garlic (Allium sativum L.).

BACKGROUND: Garlic is a promising source of antimicrobial peptide separation, and chemical modification is an effective method for activity improvement. The present study aimed to improve the antifungal activity of a peptide extracted from garlic. Chemical modifications were conducted, and the structure-activity relationship and antifungal mechanism were investigated. RESULTS: The results indicated that the cationic charge induced by Lys residue at the N-terminal was important for the antimicrobial activity, and the modified sequence exhibited significant antifungal activity with low mammalian toxicity and a low tendency of drug resistance (p < 0.05). The structure-activity relationship analysis revealed that the modified active peptide had a predominant α-helical structure and an inner cyclic correlation. Transcriptomic analysis showed that peptide KMLKKLFR (Lys-Met-Leu-Lys-Lyse-Leu-Phe-Arg) affected the rRNA processing and carbon metabolism process of Candida albicans. In addition, the membrane potential study indicated a non-membrane destruction mechanism, and molecular docking analysis and a DNA interaction assay suggested promising inner targets. CONCLUSION: The results of the present study indicate that chemical modification by amino acid substitution was effective for antimicrobial activity improvement. The present study would benefit future antimicrobial peptide development and suggests that garlic is a great source of antibacterial peptides and peptide template separations for coping with antibiotic resistance. © 2024 Society of Chemical Industry.

[Effects of childhood abuse experience, recent life events and coping styles on depressive symptoms of medical students].

OBJECTIVE: To analyze the influence of childhood abuse experience, recent life events and coping styles on depression symptoms of medical students based on the model of "vulnerability-stress-coping". METHODS: A longitudinal study design was adopted to select freshmen from Hefei City and Anqing City in Anhui province by cluster sampling. A total of 4211 questionnaires were collected at baseline from November to December 2019. Follow-up surveys were conducted in November to December 2020, and a total of 3662 medical students were finally included in this study. The childhood trauma questionnaire, adolescent self-rating life events checklist, coping style questionnaire and self-rating depression scale were used to evaluate childhood abuse experience, recent life events, coping styles and depression symptoms of medical students. The PROCESS software model 1(double interaction analysis) and model 3(triple interaction analysis) were used to investigate the independent and interactive effects of childhood abuse experience, recent life events, and different coping styles on depressive symptoms of medical students during follow-up. RESULTS: Among the 3662 medical students, 976 were male and 2686 were female, with an average age of(19.2±1.0) years. Spearman correlation analysis showed that childhood abuse experience, recent life events, self-blame, fantasy, problem avoidance, and rationalization coping style were positively related to depressive symptoms(P<0.05). The coping style of problem solving and seeking help was negatively related to depressive symptoms(P<0.05). In model 1, both childhood abuse experience(ß=0.097, 95%CI 0.065-0.129) and recent life events(ß=0.102, 95%CI 0.073-0.132) had a positive predictive effect on depressive symptoms, and they also had positive interaction on depressive symptoms(ß=0.030, 95%CI 0.025-0.004). In model 3, there was a negative interaction between childhood abuse, recent life events and seeking help(ß=-0.034, 95%CI-0.061--0.007) or fantasy(ß=-0.039, 95%CI-0.065--0.013) coping styles on depressive symptoms. CONCLUSION: Childhood abuse experience and recent life events are the predisposition factors for depressive symptoms of medical students, and they can mutually promote depression, while seeking help and fantasy coping styles could weaken the promoting effects of both.

DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.

DNA N4-methylcytosine (4mC) is an important epigenetic modification that plays a vital role in regulating DNA replication and expression. However, it is challenging to detect 4mC sites through experimental methods, which are time-consuming and costly. Thus, computational tools that can identify 4mC sites would be very useful for understanding the mechanism of this important type of DNA modification. Several machine learning-based 4mC predictors have been proposed in the past 3 years, although their performance is unsatisfactory. Deep learning is a promising technique for the development of more accurate 4mC site predictions. In this work, we propose a deep learning-based approach, called DeepTorrent, for improved prediction of 4mC sites from DNA sequences. It combines four different feature encoding schemes to encode raw DNA sequences and employs multi-layer convolutional neural networks with an inception module integrated with bidirectional long short-term memory to effectively learn the higher-order feature representations. Dimension reduction and concatenated feature maps from the filters of different sizes are then applied to the inception module. In addition, an attention mechanism and transfer learning techniques are also employed to train the robust predictor. Extensive benchmarking experiments demonstrate that DeepTorrent significantly improves the performance of 4mC site prediction compared with several state-of-the-art methods.

Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.

Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique ability to target cancer cells without affecting healthy cells directly, they have been extensively studied. Many peptide-based drugs are currently evaluated in the preclinical and clinical trials. Accurate identification of ACPs has received considerable attention in recent years; as such, a number of machine learning-based methods for in silico identification of ACPs have been developed. These methods promote the research on the mechanism of ACPs therapeutics against cancer to some extent. There is a vast difference in these methods in terms of their training/testing datasets, machine learning algorithms, feature encoding schemes, feature selection methods and evaluation strategies used. Therefore, it is desirable to summarize the advantages and disadvantages of the existing methods, provide useful insights and suggestions for the development and improvement of novel computational tools to characterize and identify ACPs. With this in mind, we firstly comprehensively investigate 16 state-of-the-art predictors for ACPs in terms of their core algorithms, feature encoding schemes, performance evaluation metrics and webserver/software usability. Then, comprehensive performance assessment is conducted to evaluate the robustness and scalability of the existing predictors using a well-prepared benchmark dataset. We provide potential strategies for the model performance improvement. Moreover, we propose a novel ensemble learning framework, termed ACPredStackL, for the accurate identification of ACPs. ACPredStackL is developed based on the stacking ensemble strategy combined with SVM, Naïve Bayesian, lightGBM and KNN. Empirical benchmarking experiments against the state-of-the-art methods demonstrate that ACPredStackL achieves a comparative performance for predicting ACPs. The webserver and source code of ACPredStackL is freely available at http://bigdata.biocie.cn/ACPredStackL/ and https://github.com/liangxiaoq/ACPredStackL, respectively.

DeepGenGrep: a general deep learning-based predictor for multiple genomic signals and regions.

MOTIVATION: Accurate annotation of different genomic signals and regions (GSRs) from DNA sequences is fundamentally important for understanding gene structure, regulation and function. Numerous efforts have been made to develop machine learning-based predictors for in silico identification of GSRs. However, it remains a great challenge to identify GSRs as the performance of most existing approaches is unsatisfactory. As such, it is highly desirable to develop more accurate computational methods for GSRs prediction. RESULTS: In this study, we propose a general deep learning framework termed DeepGenGrep, a general predictor for the systematic identification of multiple different GSRs from genomic DNA sequences. DeepGenGrep leverages the power of hybrid neural networks comprising a three-layer convolutional neural network and a two-layer long short-term memory to effectively learn useful feature representations from sequences. Benchmarking experiments demonstrate that DeepGenGrep outperforms several state-of-the-art approaches on identifying polyadenylation signals, translation initiation sites and splice sites across four eukaryotic species including Homo sapiens, Mus musculus, Bos taurus and Drosophila melanogaster. Overall, DeepGenGrep represents a useful tool for the high-throughput and cost-effective identification of potential GSRs in eukaryotic genomes. AVAILABILITY AND IMPLEMENTATION: The webserver and source code are freely available at http://bigdata.biocie.cn/deepgengrep/home and Github (https://github.com/wx-cie/DeepGenGrep/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Relationship between chronotype and mental behavioural health among adolescents: a cross-sectional study based on the social ecological system.

BACKGROUND: Health risk behaviors (HRBs) is a kind of phenomenon behavior that often occurs in adolescence, and also often appears in clusters. Previous studies suggested an association between social ecological risk factors (SERFs) and HRBs. This study explored 1) whether chronotype moderates the risk of HRBs associated with SERFs and 2) whether mental health is a mediator in this relationship. METHODS: Adolescents were recruited from 39 junior or senior schools (three cities, 13 schools per city) using a multistage cluster sampling method conducted between October, 2020 and June, 2021. The Social Ecological System, Morningness-Eveningness Questionnaire, Brief Instrument on Psychological Health Youths, and Youth Risk Behavior Surveillance questionnaires were used to measure the SERFs, chronotype, mental health and HRBs. Latent category analysis was used to explore the clustering mode of HRBs. The primary exposure was SERFs, and the primary outcome was HRBs; chronotype was a moderator, and mental health was a mediator. The multivariable logistic regression model was used to determine the relationship between SERFs and chronotype and mental behavioral health status. Mediation moderate analysis using the PROCESS method was used to explore the relationship between these variables. Sensitivity analysis was conducted to evaluate the robustness of the model. RESULTS: In total, 17,800 individuals were initially enrolled. After excluding 947 individuals with invalid questionnaires, 16,853 participants were finally included in the analysis. The mean age of participants was 15.33 ± 1.08 years. After adjusting for covariates, multivariable logistic regression found that high levels of SERFs (odds ratio [OR] = 10.10, 95% confidence interval [CI]: 8.88-11.43, P < 0.01), intermediate chronotype (OR = 5.24, 95% CI: 4.57-6.01, P < 0.01), and eveningness (OR = 1.83, 95% CI: 1.64-2.05, P < 0.01) were associated with higher HRBs frequency. This study also assessed the interaction between chronotype, SERFs and HRBs (OR = 27.84, 95% CI: 22.03-35.19, P < 0.01) and mental health (OR = 18.46, 95% CI: 13.16-25.88, P < 0.01). The moderated mediation analyses examined the relationship between chronotype, SERFs, mental health and HRBs. CONCLUSIONS: SERFs may be important variables in measuring the effect of the adolescent psychosocial environment on HRBs; this effect is mediated by mental health and moderated by chronotype.

Gender-based differences in interaction effects between childhood maltreatment and problematic mobile phone use on college students' depression and anxiety symptoms.

BACKGROUND: Childhood maltreatment and problematic mobile phone use are risk factors for depression and anxiety symptoms among college students. However, how the interaction between the two factors affects depression and anxiety has yet to be validated. This study aimed to investigate the independent and interaction effects of childhood maltreatment and problematic mobile phone use on depression and anxiety among college students and explored gender-based differences in these associations. METHOD: A cross-sectional study was conducted from October to December 2019. We collected data from 7623 students at two colleges in Hefei and Anqing cities in Anhui Province, China. Multinomial logistic regression models were performed to explore the associations of childhood maltreatment and problematic mobile phone use with depression and anxiety symptoms and their interaction effects on depression and anxiety symptoms. RESULTS: Childhood maltreatment and problematic mobile phone use were significantly associated with increased risk of depression and anxiety symptoms (P < 0.001). Moreover, following adjustments for covariates, there was a multiplicative interaction between childhood maltreatment and problematic mobile phone use on depression and anxiety symptoms (P < 0.001). Gender-based differences were also observed in the associations. For instance, depression was more common in males and male students with childhood maltreatment were at higher risk of depression-only symptoms. CONCLUSION: Focusing on childhood maltreatment and problematic mobile phone use could facilitate a reduction in the occurrence of depression and anxiety symptoms in college students. Furthermore, it is necessary to develop gender-targeted intervention strategies.

Role of polygenic risk scores in the association between chronotype and health risk behaviors.

BACKGROUND: This study explores the association between chronotypes and adolescent health risk behaviors (HRBs) by testing how genetic background moderates these associations and clarifies the influence of chronotypes and polygenic risk score (PRS) on adolescent HRBs. METHODS: Using VOS-viewer software to select the corresponding data, this study used knowledge domain mapping to identify and develop the research direction with respect to adolescent risk factor type. Next, DNA samples from 264 students were collected for low-depth whole-genome sequencing. The sequencing detected HRB risk loci, 49 single nucleotide polymorphisms based to significant SNP. Subsequently, PRSs were assessed and divided into low, moderate, and high genetic risk according to the tertiles and chronotypes and interaction models were constructed to evaluate the association of interaction effect and clustering of adolescent HRBs. The chronotypes and the association between CLOCK-PRS and HRBs were examined to explore the association between chronotypes and mental health and circadian CLOCK-PRS and HRBs. RESULTS: Four prominent areas were displayed by clustering information fields in network and density visualization modes in VOS-viewer. The total score of evening chronotypes correlated with high-level clustering of HRBs in adolescents, co-occurrence, and mental health, and the difference was statistically significant. After controlling covariates, the results remained consistent. Three-way interactions between chronotype, age, and mental health were observed, and the differences were statistically significant. CLOCK-PRS was constructed to identify genetic susceptibility to the clustering of HRBs. The interaction of evening chronotypes and high genetic risk CLOCK-PRS was positively correlated with high-level clustering of HRBs and HRB co-occurrence in adolescents, and the difference was statistically significant. The interaction between the sub-dimensions of evening chronotypes and the high genetic CLOCK-PRS risk correlated with the outcome of the clustering of HRBs and HRB co-occurrence. CONCLUSIONS: The interaction of PRS and chronotype and the HRBs in adolescents appear to have an association, and the three-way interaction between the CLOCK-PRS, chronotype, and mental health plays important roles for HRBs in adolescents.

Clinical value of O-RADS combined with serum CA125 and HE4 for the diagnosis of ovarian tumours.

BACKGROUND: Ovarian tumors (OTs) are common gynecological tumors in women. It is very important to correctly distinguish benign and malignant OTs. PURPOSE: To assess the diagnostic performance of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) and evaluate the clinical value of O-RADS combined with serum carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) in differentiating benign from malignant OTs. MATERIAL AND METHODS: A retrospective analysis was performed on 431 cases including pathology and clinical data. The receiver operating characteristic (ROC) curve was drawn, and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. RESULTS: In premenopausal women, O-RADS and O-RADS combined with serum CA125 and HE4 showed sensitivity at 92.2% and 94.8%, specificity at 91.8% and 93.4%, and accuracy at 91.9% and 93.8%, respectively. In postmenopausal women, the sensitivity of O-RADS, O-RADS combined with serum CA125 and HE4 was 94.8% and 95.8%, specificity was 83.9% and 93.6%, and accuracy was 90.5% and 95.6%, respectively. The sensitivity, specificity, and accuracy of O-RADS combined with CA125 and HE4 in premenopausal and postmenopausal women were higher than that of O-RADS (P<0.05). CONCLUSION: O-RADS has high diagnostic performance in OTs. When O-RADS is combined with CA125 and HE4 in the diagnosis of OTs, the sensitivity and specificity are improved, which is helpful to improve the diagnostic efficiency of OTs and has high clinical application value.

Leaching of heavy metal(loid)s from historical Pb-Zn mining tailing in abandoned tailing deposit: Up-flow column and batch tests.

This study aims to investigate the water-leaching characteristics of heavy metal(loid)s (HMs) from historical Pb-Zn mine tailing of an abandoned tailing deposit in eastern China. Up-flow column and batch leaching tests were conducted at different liquid-to-solid (L/S) ratios to estimate the releases of HMs and investigate the controlling mechanisms. Calcite and silicate were the dominant minerals in the tailing and the HMs contents followed the order of Zn (2371 mg/kg) > Pb (2061 mg/kg) > Cu (109 mg/kg) > Cr (47.8 mg/kg) > As (15.9 mg/kg) > Cd (5.1 mg/kg). Moreover, considerable fractions of Pb, Zn, and Cd existed in the acid-soluble forms (41-47%). Column and batch leaching tests consistently showed that limited quantities (<0.002%) of HMs could be leached from this historical tailing. In particular, variations in column conditions (e.g., length, flow rate, and initial saturation) significantly affected the release fluxes from the columns but had a relatively limited effect on the leaching mechanisms. The estimated results of HM release suggested that the leaching process was predominantly solubility-controlled and the dissolution of Ca-bearing minerals (e.g., calcite) primarily controlled the release of HMs. The studied tailing had a limited impact on the quality of the surrounding aquatic environments because the water-leaching concentrations of HMs were generally lower than the Chinese standards for drinking water. Only for Pb, the leaching results in column tests were significantly lower than those in batch tests; whereas the results in column tests for other HMs were comparable to those in batch tests to a certain extent. Based on the column test results, the amounts of HMs potentially released from the abandoned tailing deposit (height, 10 m; footprint area, 30,000 m2; tailing dry density, 1.9 × 103 kg/m3) followed a decreasing order of Zn (4.2 × 105 kg) > Cu (2.3 × 104 kg) > Pb (1.4 × 104 kg) > Cr (2.3 × 104 kg) > Cd (1.6 × 103 kg) > As (1.2 × 103 kg) over the 75-year assessment period (corresponding to an L/S ratio of 10 L/kg with an annual precipitation of 1500 mm).

Characterization of the Physical Chemistry Properties of Iron-Tailing-Based Ceramsite.

In order to deal with the problems of resource waste and environmental pollution caused by solid waste, iron tailings (mainly SiO2, Al2O3 and Fe2O3) were used as the main raw material to create a type of lightweight and high-strength ceramsite. Iron tailings, dolomite (industrial grade, purity 98%) and a small amount of clay were combined in a N2 atmosphere at 1150 °C. X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and a themogravimetric analysis (TGA) were performed and the specific surface area was analyzed to determine the strength and adsorption of the ceramsite. The results of the XRF showed that SiO2, CaO and Al2O3 were the main components of the ceramsite, with MgO and Fe2O3 also included. The results of the XRD and SEM-EDS showed that the ceramsite contained several kinds of minerals and was mainly composed of akermanite, gehlenite and diopside, and that the morphology of the internal structure of the ceramsite was mainly massive and contained a small number of particles. The ceramsite could be used in engineering practice to improve the mechanical properties of materials and meet the requirements of actual engineering for the strength of materials. The results of the specific surface area analysis showed that the inner structure of the ceramsite was compact and that there were no large voids. The voids were mainly medium and large, with a high stability and strong adsorption ability. The TGA results showed that the quality of the ceramsite samples will continue to increase within a certain range. According to the XRD experimental results and experimental conditions, it was speculated that in the part of the ore phase containing Al, Mg or Ca in the ceramsite, the elements underwent relatively complex chemical reactions with each other, resulting in the formation of an ore phase with a higher molecular weight. This research provides the basis of characterization and analysis for the preparation of high-adsorption ceramsite from iron tailings and promotes the high-value utilization of iron tailings for waste pollution control.