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ObjectiveThis study investigated the positive rate and related influencing factors of anxiety screening in pregnant women during the first fetal magnetic resonance examination.MethodsA total of 303 pregnant women who met the criteria for magnetic resonance pregnancy examination in a Grade III maternity hospital from December 2021 to December 2022 were included by the convenience sampling method. A cross-sectional survey was conducted before the examination using the General Situation Questionnaire and Self-rating Anxiety Scale (SAS).ResultsThe positive rate of anxiety was 31.02% (94/303), and the average score of anxiety was 45.71±9.84. Univariate analysis results showed that age, educational level, occupation, place of residence, per capita monthly income, and number of pregnancies were related to the anxiety status of pregnant women in the fetal magnetic resonance examination (PConclusionsThe positive rate of anxiety screening of pregnant women before the first prenatal magnetic resonance examination is high. A low education level and living in the countryside will increase the probability of anxiety in pregnant women during magnetic resonance examination. Based on the above research results, it is suggested that medical institutions pay attention to the mental health of pregnant women, improve mental health care services, and reduce the adverse psychological problems caused by prenatal examination.

The leading role of the media is very important in the new media era to build the reporting system and framework of sexual violence crimes, guide people's awareness and public opinion, and improve society's vigilance on sexual crimes. This study took People's Daily Online, a representative online media in China, as a research object to analyse the reporting of sexual crimes over the past 15 years. We conducted relevant searches for specific keywords set in the Python crawler and used IBM SPSS Statistics 19 software to analyse the frequency of relevant content. The results of the research show that, firstly, there have been significant changes in the number of news stories about sexual crimes. Second, the majority of sexual crime news stories are from mainland China. Third, the focus of the news stories and people is relatively concentrated on the perpetrators. Fourth, the People's Daily Online's coverage of sexual crimes focuses on blaming the perpetrators. Fifth, sexual crimes show that the framework is more episodic. This paper examines changes in the coverage of sexual crimes in China and captures how the media cover socially relevant issues, providing important insights for future social health, psychological awareness and diversion, and media policy.

Amidst growing skepticism towards globalization and rising digital trade, this study investigates the impact of Restrictions on Cross-Border Data Flows (RCDF) on Domestic Value Chains (DVCs) stability. As global value chains participation declines, the stability of DVCs-integral to internal economic dynamics-becomes crucial. This study situates within a framework exploring the role of innovation and RCDF in the increasingly interconnected global trade. Using a panel data fixed effect model, our analysis provides insights into the varying effects of RCDF on DVCs stability across countries with diverse economic structures and technological advancement levels. This approach allows for a nuanced understanding of the interplay between digital trade policies, value chain stability, and innovation. RCDF tend to disrupt DVCs by negatively impacting innovation, which necessitates proactive policy measures to mitigate these effects. In contrast, low-income countries experience a less detrimental impact; RCDF may even aid in integrating their DVCs into Global Value Chains, enhancing economic stability. It underscores the need for dynamic, adaptable policies and global collaboration to harmonize digital trade standards, thus offering guidance for policy-making in the context of an interconnected global economy.

IntroductionIndividualized treatment of spinal deformity is needed for adolescent idiopathic scoliosis (AIS), and the integration of pelvic rotation correction based on proprioceptive neuromuscular facilitation (PNF) into regular physiotherapy may be a promising approach. However, few high-quality studies have investigated its effects. This study aimed to evaluate the efficacy of pelvic rotation correction combined with Schroth exercises in the treatment of mild AIS.MethodsThis was a randomized controlled trial. Forty-two AIS patients were randomly divided into experimental and control groups. Both groups underwent 20 therapeutic sessions over 24 weeks. All patients (n = 42) performed Schroth exercises at each session. In addition, the experimental group (n = 21) also participated in a pelvic rotation correction program based on PNF at each session. The primary outcome was the concave/convex ratio of hipbone widths, and the secondary outcomes included the Cobb angle, trunk rotation angle, self-perception, apical vertebral translation, and apical vertebral rotation. Patients were evaluated before and after 24 weeks of intervention.ResultsThere was a significant between-group difference in the change from baseline between the experimental and control groups for the following parameters: concave/convex ratio 2.89% (95% confidence interval [CI], 1.58 to 4.20, PConclusionsPelvic rotation correction combined with Schroth exercises more effectively improved pelvic axial rotation and other spinal deformities, including trunk rotation and apical vertebral rotation, than Schroth exercises alone in the treatment of mild AIS.

[This corrects the article DOI: 10.1371/journal.pone.0298917.].

ObjectiveMinimally invasive surgery for spontaneous intracerebral hemorrhage is impeded by inadequate lysis of the target blood clot. Ultrasound is thought to expedite intravascular thrombolysis, thereby facilitating vascular recanalization. However, the impact of ultrasound on intracerebral blood clot lysis remains uncertain. This study aimed to explore the feasibility of combining ultrasound with urokinase to enhance blood clot lysis in an in vitro model of spontaneous intracerebral hemorrhage.MethodsThe blood clots were divided into four groups: control group, ultrasound group, urokinase group, and ultrasound + urokinase group. Using our experimental setup, which included a key-shaped bone window, we simulated a minimally invasive puncture and drainage procedure for spontaneous intracerebral hemorrhage. The blood clot was then irradiated using ultrasound. Blood clot lysis was assessed by weighing the blood clot before and after the experiment. Potential adverse effects were evaluated by measuring the temperature variation around the blood clot in the ultrasound + urokinase group.ResultsA total of 40 blood clots were observed, with 10 in each experimental group. The blood clot lysis rate in the ultrasound group, urokinase group, and ultrasound + urokinase group (24.83 ± 4.67%, 47.85 ± 7.09%, 61.13 ± 4.06%) was significantly higher than that in the control group (16.11 ± 3.42%) (p = 0.02, p < 0.001, p < 0.001). The blood clot lysis rate in the ultrasound + urokinase group (61.13 ± 4.06%) was significantly higher than that in the ultrasound group (24.83 ± 4.67%) (p < 0.001) or urokinase group (47.85 ± 7.09%) (p < 0.001). In the ultrasound + urokinase group, the mean increase in temperature around the blood clot was 0.26 ± 0.15°C, with a maximum increase of 0.38 ± 0.09°C. There was no significant difference in the increase in temperature regarding the main effect of time interval (F = 0.705, p = 0.620), the main effect of distance (F = 0.788, p = 0.563), or the multiplication interaction between time interval and distance (F = 1.100, p = 0.342).ConclusionsOur study provides evidence supporting the enhancement of blood clot lysis in an in vitro model of spontaneous intracerebral hemorrhage through the combined use of ultrasound and urokinase. Further animal experiments are necessary to validate the experimental methods and results.

ObjectiveThe study aimed to analyze the independent and joint associations of physical activity (PA) and sedentary behavior (SB) with self-rated health (SRH) among Chinese children and adolescents.MethodsCross-sectional data on moderate-to-vigorous physical activity (MVPA), school-based PA, extracurricular physical activity (EPA), screen time (ST), homework time, and SRH were assessed through a self-report questionnaire in the sample of 4227 Chinese children and adolescents aged 13.04 ± 2.62 years. Binary logistic regression was used to compare gender differences in PA, SB, and SRH among children and adolescents, and analyses were adjusted for age and ethnicity.ResultsIn independent associations, boys and girls engaging in ≥60 min/day of MVPA and >1 hour/day of EPA reported optimal SRH. Only boys who participated in >1 hour/day of school-based PA were significantly more likely to have optimal SRH (OR = 1.49, 95%CI = 1.19-1.86). Only girls who had ≤2 hours/day of ST were significantly associated with optimal SRH (weekdays: OR = 1.38, 95%CI = 1.10-1.74; weekends: OR = 1.40, 95%CI = 1.14-1.71; whole week: OR = 1.42, 95%CI = 1.16-1.73). In joint associations, regardless of SB recommendation, meeting PA recommendation was significantly associated with optimal SRH in both boys (meet PA and SB recommendations, OR = 1.61, 95%CI = 1.03-2.50; meet PA but not SB recommendations, OR = 2.40, 95%CI = 1.57-3.65) and girls (meet PA and SB recommendations, OR = 3.72, 95%CI = 2.08-6.65; meet PA but not SB recommendation, OR = 4.27, 95%CI = 2.09-8.75).ConclusionIncreased PA and reduced SB were positively associated with optimal SRH in Chinese children and adolescents. Notably, lower ST positively influenced only girls' SRH. Meeting PA recommendation is more impactful than meeting SB recommendation for improving SRH in Chinese children and adolescents. Future studies could explore these associations using objective measures of PA and SB in China.

Mantle cell lymphoma (MCL) has a poor prognosis and high relapse rates despite current therapies, necessitating novel treatment regimens. Inhibition of SRC-3 show effectiveness in vivo and in vitro in other B cell lymphomas. Additionally, previous studies have shown that SRC-3 is highly expressed in the lymph nodes of B cell non-Hodgkin's lymphoma patients, suggesting SRC-3 may play a role in the progression of B cell lymphoma. This study aimed to investigate novel SRC-3 inhibitors, SI-10 and SI-12, in mantle cell lymphoma. The cytotoxic effects of SI-10 and SI-12 were evaluated in vitro and demonstrated dose-dependent cytotoxicity in a panel of MCL cell lines. The in vivo efficacy of SI-10 was confirmed in two ibrutinib-resistant models: an immunocompetent disseminated A20 mouse model of B-cell lymphoma and a human PDX model of MCL. Notably, SI-10 treatment also resulted in a significant extension of survival in vivo with low toxicity in both ibrutinib-resistant murine models. We have investigated SI-10 as a novel anti-lymphoma compound via the inhibition of SRC-3 activity. These findings indicate that targeting SRC-3 should be investigated in combination with current clinical therapeutics as a novel strategy to expand the therapeutic index and to improve lymphoma outcomes.

Advanced nighttime light (NTL) remote sensing techniques enable the large-scope epidemiological investigations of people's exposure to outdoor artificial light at night (ALAN) and its health effects. However, multiple uncertainties remain in the measurements of people's exposure to outdoor ALAN, including the representations of outdoor ALAN, the contextual settings of exposure measurements, and measurement approaches. Non-exposed but included outdoor ALAN and causally irrelevant outdoor ALAN may manifest as contextual errors, and these uncertain contextual errors may lead to biased measurements and erroneous interpretations when modeling people's health outcomes. In this study, we systematically investigated outdoor ALAN exposure measurements in different geographic contexts using either residence-based or mobility-oriented measurements, different spatial scales, and multiple NTL data sources. Based on the GPS data collected from 208 participants in Hong Kong, outdoor ALAN exposures were measured from NTL imagery at 10 m, 130 m, and 500 m spatial resolutions using in-situ methods or 100 m, 300 m, and 500 m buffer zone averaging. Descriptive analysis, multiple t-tests, and logistic regression were employed to examine the differences between outdoor ALAN exposure measurements using various contextual settings and their effects on modeling people's overall health. Our results confirmed that different contextual settings may lead to significantly different outdoor ALAN exposure measurements. Our results also confirmed that contextual errors may lead to erroneous conclusions when using improper contextual settings to model people's overall health. Consequentially, we suggest measuring people's exposure to outdoor ALAN using the mobility-oriented approach, NTL representation with the high spatial resolution, and a very small buffer zone as a contextual unit to derive outdoor ALAN exposure. This study articulates essential methodological issues induced by uncertainties in outdoor ALAN exposure measurements and can provide essential implications and suggestions for a broad scope of studies that need accurate outdoor ALAN exposure measurements.

Although deep-learning methods can achieve human-level performance in boundary detection, their improvements mostly rely on larger models and specific datasets, leading to significant computational power consumption. As a fundamental low-level vision task, a single model with fewer parameters to achieve cross-dataset boundary detection merits further investigation. In this study, a lightweight universal boundary detection method was developed based on convolution and a transformer. The network is called a "transformer with difference convolutional network" (TDCN), which implies the introduction of a difference convolutional network rather than a pure transformer. The TDCN structure consists of three parts: convolution, transformer, and head function. First, a convolution network fused with edge operators is used to extract multiscale difference features. These pixel difference features are then fed to the hierarchical transformer as tokens. Considering the intrinsic characteristics of the boundary detection task, a new boundary-aware self-attention structure was designed in the transformer to provide inductive bias. By incorporating the proposed attention loss function, it introduces the direction of the boundary as strongly supervised information to improve the detection ability of the model. Finally, several head functions with multiscale feature inputs were trained using a bidirectional additive strategy. In the experiments, the proposed method achieved competitive performance on multiple public datasets with fewer model parameters. A single model was obtained to realize universal prediction even for different datasets without retraining, demonstrating the effectiveness of the method. The code is available at https://github.com/neulmc/TDCN.

ObjectivesTo systematically assess the quality of clinical practice guidelines (CPGs) for Helicobacter pylori (HP) infection and identify gaps that limit their development.Study design and settingCPGs for HP infection were systematically collected from PubMed, Embase, the Cochrane Library, the Cumulative Index to Nursing and Allied Health Literature, and six online guideline repositories. Three researchers independently used the AGREE Ⅱ tool to evaluate the methodological quality of the eligible CPGs. In addition, the reporting and recommendation qualities were appraised by using the RIGHT and AGREE-REX tools, respectively. The distribution of the level of evidence and strength of recommendation among evidence-based CPGs was determined.ResultsA total of 7,019 records were identified, and 24 CPGs met the eligibility criteria. Of the eligible CPGs, 19 were evidence-based and 5 were consensus-based. The mean overall rating score of AGREE II was 50.7% (SD = 17.2%). Among six domains, the highest mean score was for scope and purpose (74.4%, SD = 17.7%) and the lowest mean score was for applicability (24.3%, SD = 8.9). Only three of 24 CPGs were high-quality. The mean overall score of recommendation quality was 35.5% (SD = 12.2%), and the mean scores in each domain of AGREE-REX and RIGHT were all ≤ 60%, with values and preferences scoring the lowest (16.6%, SD = 11.9%). A total of 505 recommendations were identified. Strong recommendations accounted for 64.1%, and only 34.3% of strong recommendations were based on high-quality evidence.ConclusionThe overall quality of CPGs for HP infection is poor, and CPG developers tend to neglect some domains, resulting in a wide variability in the quality of the CPGs. Additionally, CPGs for HP infection lack sufficient high-quality evidence, and the grading of recommendation strength should be based on the quality of evidence. The CPGs for HP infection have much room for improvement and further researches are required to minimize the evidence gap.

The future of communication systems is undergoing a transformative shift towards intelligence, efficiency, and flexibility. Presently, the amalgamation of blockchain technology and the sixth-generation mobile communication network (6G) has garnered significant attention, as their fusion is poised to profoundly impact the digital economy and society at large. However, the convergence of blockchain and 6G networks poses challenges pertaining to security and performance. In this article, we propose an approach based on the design of secure mechanisms and performance optimization to delve into the key issues surrounding the integration of blockchain and 6G networks from both security and performance perspectives. Specifically, we first introduce the application scenarios of 6G networks and blockchain's empowerment of them to highlight the necessity of combining blockchain technology with 6G. Subsequently, in order to ensure the security of communication and data transmission between blockchain and 6G networks, we have investigated the design requirements for security mechanisms. Furthermore, we discuss the efficient realization of the amalgamation between blockchain and 6G networks by proposing a solution based on Directed Acyclic Graph (DAG) for blockchain's asynchronous consensus protocol, alongside optimization strategies for storage and communication to meet the desired characteristics and requirements of 6G networks. Lastly, we provide valuable research directions that serve as references and guidance for the future development of the integration between blockchain and 6G networks.

Triterpenoid saponins and flavonoids have several pharmacological activities against P. tenuifolia. The 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) and chalcone synthase (CHS) are the rate-limiting enzymes of triterpenoid saponin and flavonoid biosynthesis, respectively. In this study, HMGR and CHS genes were cloned from P. tenuifolia, and their bioinformatics analyses and tissue-specific expression were investigated. The results showed that the HMGR and CHS genes were successfully cloned, separately named the PtHMGR gene (NCBI accession: MK424118) and PtCHS gene (NCBI accession: MK424117). The PtHMGR gene is 2323 bp long, has an open reading frame (ORF) of 1782 bp, and encods 593 amino acids. The PtCHS gene is 1633 bp long with an ORF of 1170 bp, encoding 389 amino acids. PtHMGR and PtCHS were both hydrophobic, not signal peptides or secreted proteins, containing 10 conserved motifs. PtHMGR and PtCHS separately showed high homology with HMGR and CHS proteins from other species, and their secondary structures mainly included α-helix and random curl. The tertiary structure of PtHMGR was highly similarity to that the template 7ULI in RCSB PDB with 92.0% coverage rate. The HMG-CoA-binding domain of PtHMGR is located at 173-572 amino acid residues, including five bound sites. The tertiary structure of PtCHS showed high consistency with the template 1I86 in RCSB PDB with 100% coverage rate, contained malonyl CoA and 4-coumaroyl-CoA linkers. The expression of PtHMGR and PtCHS is tissue-specific. PtHMGR transcripts were mainly accumulated in roots, followed by leaves, and least in stems, and were significantly positively correlated with the contents of total saponin and tenuifolin. PtCHS was highly expressed in the stems, followed by the leaves, with low expression in the roots. PtCHS transcripts showed a significant positive correlation with total flavonoids content, however, they were significantly negatively correlated with the content of polygalaxanthone III (a type of flavonoids). This study provided insight for further revealing the roles of PtHMGR and PtCHS.

ObjectiveTo investigate intestinal toxicity in rats and the effects of Nano-cerium dioxide on intestinal flora in rats after oral sub-chronic exposure.MethodForty healthy male SD rats were randomly divided into four groups: a control group (deionized water) and three groups treated with different doses of Nano-ceria (e.g., 20 mg/kg, 100 mg/kg, and 500 mg/kg), with 10 rats in each group. The rats were given intragastric administrations (every other day) for 90 days. After the last intragastric administration, fresh fecal samples were collected by pressing the abdomen, and the animals were sacrificed. Jejunum, ileum and cecum tissues were retained for pathological analysis by Hematoxylin-eosin staining. The stool samples of rats were sequenced by the Illumina NovaSeq sequencing platform, and the sequencing results were further analyzed by QIIME2 software.ResultsThe histopathology results show that compared with the control group, in the middle- and high-dose groups, epithelial tissue was shed, lamina propria glandular structures were damaged or disappeared, and large numbers of inflammatory cells were distributed in the mucosa. The intestinal flora results show that there were no significant differences in the α-/β-diversities in each Nano-ceria-treated group compared with the control group (P>0.05). Compared with the control group, the intestinal pathogenic bacteria, Mucispirillum and Streptococcus increased significantly after Nano-cerium dioxide ingestion, while Weissella decreased. The abundances of Akkermansia in all Nano-ceria-treated groups were higher than those in the control group, but the abundances decreased with increasing dose. MetagenomesSeq analysis show that, compared with the control group, the abundances of S24-7, Lactobacillus and Clostridiales in all experimental groups significantly decreased.ConclusionsThe sub-chronic toxicity of Nano-cerium dioxide to rats can affect the structure and abundance of intestinal microflora, long-term exposure to high doses (>100 mg/kg) causes enteritis, but there was no significant difference in the diversity of gut microbiota. Therefore, we infer that the enteritis in rats may be associated with the relative ratios of the pathogenic bacteria and intestinal probiotics, and increased of the intestinal pathogenic bacteria can disrupted intestinal homeostasis.

BackgroundFew studies on molecular epidemiology have studied people with newly diagnosed HIV infection and ART Failure Patients at the same time in rural China. With more serious HIV epidemic than in other provinces in China, Sichuan is an area suitable for this study.ObjectiveTo analyze the characteristics of HIV-1 molecular networks and factors related to network entry among newly diagnosed HIV infection and ART Failure Patients in three county-level cities (A, B, C) in Sichuan Province, to provide scientific basis for accurate prevention and control.MethodsNested PCR amplification method was used to amplify HIV-1 pol gene region of 530 blood samples, Sequencer 4.9 was used to edit, clean and splice the gene sequence, Bioedit correction, Fastree 2.1.8 and Figtree 1.4.2 to construct evolutionary tree and determine genotype. HyPhy2.2.4 and Cytoscape 3.6.1 software were used to construct molecular network. Logistic regression analysis was applied.Results523(98.68%) pol sequences were obtained, and a total of 518 valid sequences with basic information came into the final analyses. A total of 6 genotypes were detected, namely CRF01_AE (320,61.78%), CRF07_BC (149,28.76%), B (30,5.79%), CRF08_BC (11, 2.12%), CRF55_01B (6, 1.16%) and C (2, 0.39%). 186 of 518(35.91%) sequences entered the network at a genetic distance of 0.8%, forming 42 propagation clusters. "High-risk transmitters"(connected with two and more) accounted for 21.62%. Logistic regression showed that≥50 years old (OR = 2.474) were more risky than 18-49 years old, CRF07_BC sub-type (OR = 0.174) were less risky than CRF01_AE sub-type, B sub-type (OR = 6.698) is higher risky than CRF01_AE sub-type, and District B (OR = 0.077) less risky than that of A city.ConclusionThe sources of HIV infection in rural Sichuan are diversified and complicated. The prevention and control of HIV infection in Sichuan Province should focus on strengthening the long-term dynamic detection of elderly population, B strain sub-type, and in City A.

The time and space of the support structure applying is related to the overall stability of the roadway after excavation directly. Designed twenty-four groups of roadway support schemes with time and space dimensions, and studied the stability characteristics of roadway in different schemes by using Fast Lagrangian Analysis of Continua in Three Dimensions. The main conclusions are as follows: the influence of energy dissipation (time) and support position (space) on the stability of the roadway is not a linear relationship, and supporting at the appropriate opportunity can be beneficial. Established the "displacement-dissipation energy" curve, founding that there is an obvious "jump" phenomenon in the dissipation energy of surrounding rock during the process of gradually increasing displacement. A novel method for determining the optimum supporting opportunity of roadway based on energy dissipation was proposed, based on the above finding. This study can provide an original idea for the determination of roadway supporting opportunity.

BackgroundSepsis is characterized by upregulated lipolysis in adipose tissue and a high blood triglyceride (TG) level. It is still debated whether serum TG level is related to mortality in septic patients. The aim of this study is to investigate the association between serum TG level and mortality in septic patients admitted to the intensive care unit (ICU).MethodsData from adult septic patients (≥18 years) admitted to the ICU for the first time were obtained from the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database. The patients' serum TG levels that were measured within the first week after ICU admission were extracted for statistical analysis. The endpoints were 28-day, ICU and in-hospital mortality.ResultsA total of 2,782 septic patients were included. Univariate analysis indicated that the relationship between serum TG levels and the risk of mortality was significantly nonlinear. Both the Lowess smoothing technique and restricted cubic spline analyses revealed a U-shaped association between serum TG levels and mortality among septic patients. The lowest mortality rate was associated with a serum TG level of 300-500 mg/dL. Using 300∼500 mg/dL as the reference range, we found that both hypo-TG (ConclusionsThere was a U-shaped association between serum TG and mortality in septic ICU patients. The optimal concentration of serum TG levels in septic ICU patients is 300-500 mg/dL.

Using information technology to extract emergency decision-making knowledge from emergency plan documents is an essential means to enhance the efficiency and capacity of emergency management. To address the problems of numerous terminologies and complex relationships faced by emergency knowledge extraction of water diversion project, a multi-feature graph convolutional network (PTM-MFGCN) based on pre-trained model is proposed. Initially, through the utilization of random masking of domain-specific terminologies during pre-training, the model's comprehension of the meaning and application of such terminologies within specific fields is enhanced, thereby augmenting the network's proficiency in extracting professional terminologies. Furthermore, by introducing a multi-feature adjacency matrix to capture a broader range of neighboring node information, thereby enhancing the network's ability to handle complex relationships. Lastly, we utilize the PTM-MFGCN to achieve the extraction of emergency entity relationships in water diversion project, thus constructing a knowledge graph for water diversion emergency management. The experimental results demonstrate that PTM-MFGCN exhibits improvements of 2.84% in accuracy, 4.87% in recall, and 5.18% in F1 score, compared to the baseline model. Relevant studies can effectively enhance the efficiency and capability of emergency management, mitigating the impact of unforeseen events on engineering safety.

AimTo provide an overview of the evidence on the effect of light therapy on sleep disturbance and depression, identify the light-active neural and hormonal correlates of the effect of light therapy on sleep disturbance comorbid depression (SDCD), and construct the mechanism by which light therapy alleviates SDCD.MethodsArticles published between 1981 and 2021 in English were accessed using Science Direct, Elsevier, and Google Scholar following a three-step searching process via evolved keywords. The evidence level, reliability, and credibility of the literature were evaluated using the evidence pyramid method, which considers the article type, impact factor, and journal citation report (JCR) partition.ResultsA total of 372 articles were collected, of which 129 articles fit the inclusion criteria and 44% were at the top of the evidence pyramid hierarchy; 50% were in the first quarter of the JCR partitions. 114 articles provided specific neural and hormonal evidence of light therapy and were further divided into three groups: 37% were related to circadian regulation circuits, 27% were related to emotional regulation circuits, and 36% were related to hormones.ConclusionsFirst, neural and hormonal light-active pathways for alleviating sleep disturbance or depression were identified, based on which the neural correlates of SDCD were located. Second, the light responses and interactions of hormones were reviewed and summarized, which also provided a way to alleviate SDCD. Finally, the light-active LHb and SCN exert extensive regulation impacts on the circadian and emotional circuits and hormones, forming a dual-core system for alleviating SDCD.

ObjectiveSuccessful prognosis is crucial for the management and treatment of osteosarcoma (OSC). This study aimed to predict the cancer-specific survival rate in patients with OSC using deep learning algorithms and classical Cox proportional hazard models to provide data to support individualized treatment of patients with OSC.MethodsData on patients diagnosed with OSC from 2004 to 2017 were obtained from the Surveillance, Epidemiology, and End Results database. The study sample was then divided randomly into a training cohort and a validation cohort in the proportion of 7:3. The DeepSurv algorithm and the Cox proportional hazard model were chosen to construct prognostic models for patients with OSC. The prediction efficacy of the model was estimated using the concordance index (C-index), the integrated Brier score (IBS), the root mean square error (RMSE), and the mean absolute error (SME).ResultsA total of 3218 patients were randomized into training and validation groups (n = 2252 and 966, respectively). Both DeepSurv and Cox models had better efficacy in predicting cancer-specific survival (CSS) in OSC patients (C-index >0.74). In the validation of other metrics, DeepSurv did not have superiority over the Cox model in predicting survival in OSC patients.ConclusionsAfter validation, our CSS prediction model for patients with OSC based on the DeepSurv algorithm demonstrated satisfactory prediction efficacy and provided a convenient webpage calculator.

The vibration signals measured in practical engineering are usually complex and noisy, which brings challenges to fault diagnosis. In addition, industrial scenarios also put forward higher requirements for the accuracy and computational efficiency of diagnostic models. Aiming at these problems, an improved multiscale branching convolutional neural network is proposed for rolling bearing fault diagnosis. The proposed method first applies the multiscale feature learning strategy to extract rich and compelling fault information from diverse and complex vibration signals. Further, the lightweight dynamic separable convolution is elaborated and coupled into the feature extractor to "slim down" the model, reduce the computational loss on the one hand, and further improve the model's adaptive learning ability for different inputs hand. Extensive experiments indicate that the proposed method is significantly improved compared with existing multi-scale neural networks.

Revealing the influence of sports sports venues on the population in the built-up areas of cities contributes to the high-quality development of cities and the well-being of people. This study applies kernel density estimation to characterize the distribution of sports venues using reclassified POI (Point of Information) data, visualizes the distribution of intra-city population using population raster data from the WorldPop database, and analyses the distribution of sports venues and the urban population in Xi'an and Zhengzhou cities in 2020 from both the general and local perspectives based on various regression methods, such as MGWR, GWR, and linear fitting. The results show that the distribution of sports venues in Xi'an and Zhengzhou cities in 2020 was a good indicator of the population. The spatial distribution of sports venues and the population within the cities have a centre-periphery structure. From the global perspective, the distribution of sports venues is positively correlated with the intra-city population, and the promoting effect is significant. From the local perspective, the effect is spatially heterogeneous. Finally, this study explores the rationality of the complex impact and indicates that the research methodology can provide a reliable reference for other cities.

Nitrate content is an essential indicator of the quality of vegetables but can cause stress at high levels. This study aimed to elucidate the regulatory mechanisms of nitrate stress tolerance in spinach (Spinacia oleracea L.). We studied the effects of exogenous application of 15 (control), 50, 100, 150, 200, and 250 mM NO3- on spinach growth, physiology, and photosynthesis. The results showed that all the nitrate treatments inhibited the growth of the aerial parts of spinach compared to the control. In contrast, low nitrate levels (50 and 100 mM) promoted spinach root formation, but this effect was inhibited at high levels (150, 200, and 250 mM). Treatment with 150 mM NO3- significantly decreased the root growth vigor. Low nitrate levels increased the chlorophyll content in spinach leaves, whereas high levels had the opposite effect. High nitrate levels also weakened the net photosynthetic rate (Pn), the actual photochemical efficiency of PSII Y(II), and increased non-photochemical quenching (NPQ), reducing photosynthetic performance. Nitrate stress increased the activity of nitrate reductase (NR) and promoted the accumulation of nitrate in spinach leaves, exceeding the health-tolerance limit for nitrate in vegetables, highlighting the necessity of mitigating nitrate stress to ensure food safety. Starting with the 150 mM NO3- treatment, the proline and malondialdehyde content in spinach leaves and roots increased significantly as the nitrate levels increased. Treatment with 150 mM NO3- significantly increased soluble protein and flavonoid contents, while the activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) were significantly reduced in leaves. However, spinach could resist nitrate stress by regulating the synthesis of osmoregulatory substances such as proline, thus showing some nitrate tolerance. These results provide insights into the physiological regulatory mechanisms of nitrate stress tolerance and its mitigation in spinach, an essential vegetable crop.

BackgroundInternet addiction has emerged as a major global concern as a potential adverse impact of internet exposure on adolescents. Internet addiction is associated with many demographic variables; however, there is a lack of consensus on its relationship with health literacy. Therefore, the aim of the present study was to assess the rates of internet addiction and health literacy level among middle school students (grades 7 to 12) in Chongqing, China, as well as to investigate the association between them.MethodsA cross-sectional, questionnaire-based study was conducted among 8971 students who were randomly selected by using stratified cluster sampling between November and December 2019. The Internet Addiction Diagnostic Questionnaire, Adolescent Health Literacy Scale and a self-designed basic information questionnaire were used to collect data. Chi-square tests were performed to compare the differences in the distribution of internet addiction across health literacy levels as well as some sociodemographic characteristics. Multivariate logistic regression analyses were conducted to identify the association between health literacy and internet addiction.ResultsThe prevalence of internet addiction among middle school students in Chongqing was 6.1%. The percentage of the students who spent more than 4 hours online every day in the past week was 14.3%. In addition, 26.7%, 26.0%, 28.3% and 26.3% of the participants reported low functional, interactive, critical and total health literacy, respectively. After adjusting for the confounding effects of demographics, multivariate regression analysis showed that critical health literacy was a protective variable for internet addiction, while functional, and interactive health literacy were the risk variable (PConclusionsThe prevalence of internet addiction among middle school students in Chongqing is relatively high. Internet addiction is strongly negatively associated with critical health literacy, but it is positively associated with functional and interactive health literacy but not total health literacy. This study provides preliminary evidence for the predictive role of health literacy in internet addiction of adolescents.

BackgroundSocioeconomic status (SES) is an important determinant of screen time (ST) in children and adolescents, however, the association between SES and ST is not fully understood in China. This study aimed to investigate the association between SES and ST (operationalized as meeting the ST guidelines; no more than 2 hours per day) in Chinese children and adolescents.MethodsCross-sectional data of 2,955 Chinese children and adolescents aged 8 to 17(53.4% girls) were used. SES was measured using indicators of parental education and perceived family wealth. ST was assessed with detailed items from the Health Behaviour School-aged Children survey questionnaires. Descriptive statistics and a Chi-square test were used to report the sample characteristics and analyse ST differences across different sociodemographic groups. A binary logistic regression was then applied to analyse the association of SES indicators with ST in children and adolescents.ResultsOverall, 25.3% of children and adolescents met the ST guidelines. Children and adolescents with higher parental education levels were 1.84 [95% CI 1.31-2.57; father] and 1.42 [95% CI 1.02-1.98; mother] times more likely to meet the ST guidelines than those with lower parental education levels. Associations between SES and ST varied across sex and grade groups. Moreover, the associations of SES with ST on weekdays and weekends were different.ConclusionsThis study demonstrated the association between SES and ST in children and adolescents, highlighting the importance of targeting children and adolescents with low SES levels as an intervention priority. Based on our findings, specific interventions can be tailored to effectively reduce ST. Future studies are encouraged to use longitudinal or interventional designs to further determine the association between SES and ST.

This paper constructs a double difference model (DID) based on the China Private Enterprise Survey (CPES) data over the period 1995–2019, combined with the 2005 national census data and considering the policy shock of the implementation of the Chinese government’s Minimum Wage Regulation in March 2004, to investigate whether rising labor costs promote private firms’ innovation investment. Robustness tests are conducted using placebo tests and event study methods. The study finds that (1) rising labor costs significantly increase private firms’ R&D investment and that this effect has significant lag and cumulative effects; (2) private industrial firms (especially above-scale private industrial firms) are more affected by rising labor costs than other private firms and have more incentives to increase innovation investment; and (3) innovation investment of below-scale private industrial firms is not significantly affected by rising labor costs.

As countries underwent the initiation, peak, post-peak, and early vaccination stages of COVID-19, the changing risk perception, coping behaviors and corresponding psychological stress experienced by the public over time was rarely reported. We conducted a national scale panel study using social-psychological data collected from 5,983 questionnaires to investigate the interactions between anxiety level, risk perception and coping behavior during different stages of COVID-19 in China. We found that sustained perceiving worries of being infected, first due to domestic and then global pandemic, contributed to the persistent high proportion of respondents with anxiety disorders which even gradually increased over time (56.1% during initiation to 60.4% during early vaccination). Gender was the strongest predictor of anxiety at all stages, with females having less confidence in COVID-19 control and always suffering from much higher anxiety levels than males even during the post peak stage. Excessive protective behavior and frequency of access to COVID-related news also contributed to public anxiety. Additionally, public risk perception was significantly associated with their willingness to vaccinate. The findings verify the feasibility of taking stage-specific and gender-based risk communication strategies to alleviate the pandemic-related public anxiety and promote vaccination by influencing public risk perception and guiding coping behaviors.

The Wnt/β-catenin signaling regulates cell renewal and repair and is closely associated with inflammation. Astragalus polysaccharides (APS) and astragaloside IV (AS-IV), which are the main active substances extracted from Radix Astragali, protect cells by regulating Wnt signaling in cells, exerting antiinflammatory, antioxidant, and antistress effects. However, the mechanisms by which APS and AS-IV interact with Wnt signaling to achieve their therapeutic effects in bovine mammary epithelial cells (BMECs) are not understood. In this study, we used lipopolysaccharide (LPS)-stimulated BMECs as an in vitro model of inflammation to investigate the effects of APS and AS-IV on Wnt signaling in inflamed BMECs. Drug concentrations were screened using the CCK-8 method, the effect on protein expression was analyzed using immunoblotting, the effect on inflammatory factors using enzyme-linked immunosorbent assay, and the effect on oxidative factors using enzyme labeling and flow cytometry. LPS activated the expression of inflammatory and oxidative factors in cells and inhibited Wnt/β-catenin signaling. APS and AS-IV antagonized the inhibitory effect of LPS, protecting BMECs. They inhibited the expression of the IL-6, IL-8, and TNF-α inflammatory factors, and that of the MDA oxidative factor, and activated Wnt signaling in LPS-stimulated BMECs. Silencing of β-catenin abolished the protective effect of APS and AS-IV against LPS-stimulated BMECs. Thus, APS and AS-IV mediate protective effects in inflammatory BMECs model through activation of the Wnt signaling pathway. Wnt signaling pathway is one of the targets of the inhibitory effects of APS and AS-IV on inflammation.

Ursolic acid (UA), a natural pentacyclic triterpenoid obtained from fruit and several traditional Chinese medicinal plants, exhibits anti-inflammatory and hypoglycemic properties. However, its protective effects against type 1 diabetes mellitus (T1DM) have not been explored. In this study, streptozotocin-induced T1DM rat models were established and treated with UA for six weeks. T1DM rats treated with UA were used to observe the effects of UA on body weight and fasting blood glucose (FBG) levels. Pathological changes in the pancreas were observed using immunohistochemical staining. The gut microbiota distribution was measured using 16S rDNA high-throughput sequencing. The proportions of Th17 and Treg cells were examined using flow cytometry. Protein and mRNA expression of molecules involved in Th17/Treg cell differentiation were assessed by quantitative real-time PCR and western blotting. The correlation between gut microbiota and Th17/Treg cell differentiation in T1DM was analyzed using redundancy analysis (RDA) analysis. Compared with the model group, FBG levels declined, and the progressive destruction of pancreatic β cells was alleviated. The diversity and uniformity of gut microbiota in T1DM rats treated with UA increased significantly. Interestingly, the Th17/Treg cell differentiation imbalance was corrected and positively correlated with the expression of Foxp3 and IL-10, and negatively correlated with the expression of RORγt, IL-17A, and TNF-α. These findings suggest that UA can lower FBG levels in T1DM rats, delay the progressive destruction of pancreatic β-cells, and modulate gut microbiota homeostasis and immune function in streptozotocin-induced T1DM rats.

BackgroundThe global epidemic of novel coronavirus pneumonia (COVID-19) has resulted in substantial healthcare resource consumption. Since patients' hospital length of stay (LoS) is at stake in the process, an investigation of COVID-19 patients' LoS and its risk factors becomes urgent for a better understanding of regional capabilities to cope with COVID-19 outbreaks.MethodsFirst, we obtained retrospective data of confirmed COVID-19 patients in Sichuan province via National Notifiable Diseases Reporting System (NNDRS) and field surveys, including their demographic, epidemiological, clinical characteristics and LoS. Then we estimated the relationship between LoS and the possibly determinant factors, including demographic characteristics of confirmed patients, individual treatment behavior, local medical resources and hospital grade. The Kaplan-Meier method and the Cox Proportional Hazards Model were applied for single factor and multi-factor survival analysis.ResultsFrom January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment, including 271 (50%) patients aged ≥ 45, 285 (53%) males, and 450 patients (84%) with mild symptoms. The median LoS was 19 (interquartile range (IQR): 14-23, range: 3-41) days. Univariate analysis showed that age and clinical grade were strongly related to LoS (PConclusionsUnderstanding COVID-19 patients' hospital LoS and its risk factors is critical for governments' efficient allocation of resources in respective regions. In areas with older and more vulnerable population and in want of primary medical resources, early reserving and strengthening of the construction of multi-level medical institutions are strongly suggested to cope with COVID-19 outbreaks.

BackgroundDiabetic nephropathy is associated with endothelial dysfunction and oxidative stress, in which the nitric oxide-soluble guanylate cyclase-cyclic guanosine monophosphate (NO-sGC-cGMP) signaling pathway is impaired. We hypothesize that sGC stimulator Compound 1 can enhance NO signaling, reduce proteinuria in a diabetic nephropathy preclinical model with diminished NO bioavailability and increased oxidized sGC. Therefore, we evaluated the effect of sGC stimulator Compound 1 on the renal effect in obese ZSF1 (ZSF1 OB) rats.Materials and methodsThe sGC stimulator Compound 1, the standard of care agent Enalapril, and a combination of Compound 1 and Enalapril were administered chronically to obese ZSF1 rats for 6 months. Mean arterial pressure, heart rate, creatinine clearance for glomerular filtration rate (eGFR), urinary protein excretion to creatinine ratio (UPCR), and urinary albumin excretion ratio (UACR) were determined during the study. The histopathology of glomerular and interstitial lesions was assessed at the completion of the study.ResultsWhile both Compound 1 and Enalapril significantly reduced blood pressure, the combination of Compound 1 and Enalapril normalized blood pressure levels. Compound 1 improved eGFR and reduced UPCR and UACR. A combination of Enalapril and Compound 1 resulted in a marked reduction in UPCR and UACR and improved GFR.ConclusionThe sGC stimulator Compound 1 as a monotherapy slowed renal disease progression, and a combination of the sGC stimulator with Enalapril provided greater renal protection in a rodent model of diabetic nephropathy.

To overcome the low accuracy, poor reliability, and delay in the current drought prediction models, we propose a new extreme learning machine (ELM) based on an improved variational mode decomposition (VMD). The model first redefines the output of the hidden layer of the ELM model with orthogonal triangular matrix decomposition (QR) to construct an orthogonal triangular ELM (QR-ELM), and then introduces an online sequence learning mechanism (OS) into the QR-ELM to construct an online sequence OR-ELM (OS-QR-ELM), which effectively improves the efficiency of the ELM model. The mutual information extension method was then used to extend both ends of the original signal to improve the VMD end effect. Finally, VMD and OS-QR-ELM were combined to construct a drought prediction method based on the VMD-OS-QR-ELM. The reliability and accuracy of the VMD-OS-QR-ELM model were improved by 86.19% and 93.20%, respectively, compared with those of the support vector regression model combined with empirical mode decomposition. Furthermore, the calculation efficiency of the OS-QR-ELM model was increased by 88.65% and 85.32% compared with that of the ELM and QR-ELM models, respectively.

Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.

In the context of the Belt and Road Initiative, China Railway Express achieved rapid development. Determining how to achieve effective marking and determining how to adopt the optimal competitive strategy are the main challenges for CR Express operators. By choosing long-distance transportation as the research object, this research established a competitive model between CR Express and maritime transportation based on game theory. First, we determined the participants of this competition. By dividing common goods into the categories of high-value and high-time-sensitiveness, high-value and low-time-sensitiveness, low-value and high-time-sensitiveness, and low-value and low-time-sensitiveness, the model was used to simulate four situations and to obtain optimal strategies for operators. For CR Express, it was always effective to adopt a service optimizing strategy to improve the service level and earn market share. For maritime transportation, this strategy was effective only for high-value and low-time-sensitiveness goods as well as low value and low-time-sensitiveness goods. Therefore, transportation service suppliers should make competitive strategies based on different good types, and it is effective to use differentiation strategies to earn market share and improve competitiveness only for suitable types of goods.

MotivationNext generation sequencing (NGS) technology has been widely used in biomedical research, particularly on those genomics-related studies. One of NGS applications is the high-throughput mRNA sequencing (RNA-seq), which is usually applied to evaluate gene expression level (i.e. copies of isoforms), to identify differentially expressed genes, and to discover potential alternative splicing events. Popular tools for differential expression (DE) analysis using RNA-seq data include edgeR and DESeq. These methods tend to identify DE genes at the gene-level, which only allows them to compare the total size of isoforms, that is, sum of an isoform's copy number times its length over all isoforms. Naturally, these methods may fail to detect DE genes when the total size of isoforms remains similar but isoform-wise expression levels change dramatically. Other tools can perform isoform-level DE analysis only if isoform structures are known but would still fail for many non-model species whose isoform information are missing. To overcome these disadvantages, we developed an isoform-free (without need to pre-specify isoform structures) splicing-graph based negative binomial (SGNB) model for differential expression analysis at isoform level. Our model detects not only the change in the total size of isoforms but also the change in the isoform-wise expression level and hence is more powerful.ResultsWe performed extensive simulations to compare our method with edgeR and DESeq. Under various scenarios, our method consistently achieved a higher detection power, while controlling pre-specified type I error. We also applied our method to a real data set to illustrate its applicability in practice.

The impact-induced fragmentation of rock is widely and frequently encountered when natural hazards occur in mountainous areas. This type of fragmentation is an important and complex natural process that should be described. In this study, laboratory impact tests under different impact velocities were first conducted using a novel gas-driven rock impact apparatus. The three-dimensional digital image correlation (3D DIC) technique was used to monitor the dynamic fragmentation process upon impact. Then, coupled 3D finite-discrete element method (FDEM) numerical simulations were performed to numerically investigate the energy and damage evolutions and fragmentation characteristics of the sample under different impact velocities. The laboratory test results show that as the impact velocity increases, the failure pattern of the rock sample gradually changes from shear failure to splitting failure, and the fragmentation intensity increases obviously. The strain localization area gradually increases as the impact velocity increases and as the location gradually deviates away from the impacting face. In the numerical simulation, the proposed model is validated by quasi-static uniaxial compression tests and impact tests. The numerical simulations clearly show the progressive fracture process of the samples, which agrees well with the experimental observations. The evolutions of energy and damage variables were also derived based on the simulation results, which are markedly affected by the impact velocity. The fragment size distributions based on mass and number can be well fitted using a generalized extreme value law. Finally, the distribution of the fragment flying velocity and angle are analyzed.

Inflammatory bowel disease (IBD) is a chronic immune-mediated disease of the gastrointestinal tract. While therapies exist, response can be limited within the patient population. Researchers have thus studied mouse models of colitis to further understand pathogenesis and identify new treatment targets. Flow cytometry and RNA-sequencing can phenotype immune populations with single-cell resolution but provide no spatial context. Spatial context may be particularly important in colitis mouse models, due to the simultaneous presence of colonic regions that are involved or uninvolved with disease. These regions can be identified on hematoxylin and eosin (H&E)-stained colonic tissue slides based on the presence of abnormal or normal histology. However, detection of such regions requires expert interpretation by pathologists. This can be a tedious process that may be difficult to perform consistently across experiments. To this end, we trained a deep learning model to detect 'Involved' and 'Uninvolved' regions from H&E-stained colonic tissue slides. Our model was trained on specimens from controls and three mouse models of colitis-the dextran sodium sulfate (DSS) chemical induction model, the recently established intestinal epithelium-specific, inducible Klf5ΔIND (Villin-CreERT2;Klf5fl/fl) genetic model, and one that combines both induction methods. Image patches predicted to be 'Involved' and 'Uninvolved' were extracted across mice to cluster and identify histological classes. We quantified the proportion of 'Uninvolved' patches and 'Involved' patch classes in murine swiss-rolled colons. Furthermore, we trained linear determinant analysis classifiers on these patch proportions to predict mouse model and clinical score bins in a prospectively treated cohort of mice. Such a pipeline has the potential to reveal histological links and improve synergy between various colitis mouse model studies to identify new therapeutic targets and pathophysiological mechanisms.

[This corrects the article DOI: 10.1371/journal.pone.0236648.].

The "Broadband Village" (B&V) initiative is a substantial investment in internet construction in rural areas in six western provinces implemented by the Chinese government since 2014. This study evaluates the effect this policy has had. Panel data of 1,049 counties in China from 2015 to 2019 are used for the regression discontinuity design (RD) to estimate the impact of B&V on the improvement of the income level of rural residents. The results show that, compared to the counties without the B&V policy, the income of rural residents in counties with B&V has increased by 1.468-1.518 times, which is nearly 1.3 times the sample mean of survey data, indicating that the income level of rural residents has been improved significantly by B&V. However, the quantile regression results show that the higher the income level of rural residents, the smaller the effect of this policy. From the dynamic effect of years, the influence curve of B&V on rural residents' income is an inverted U-shaped, first increasing and then decreasing, and the impact of this policy on the income level of highly-educated farmers is greater. Finally, three different methods are used to verify the robustness of the model.

Japanese encephalitis (JE) is an acute infectious disease caused by the Japanese encephalitis virus (JEV) and is transmitted by mosquitoes. Meteorological conditions are known to play a pivotal role in the spread of JEV. In this study, a zero-inflated generalised additive model and a long short-term memory model were used to assess the relationship between the meteorological factors and population density of Culex tritaeniorhynchus as well as the incidence of JE and to predict the prevalence dynamics of JE, respectively. The incidence of JE in the previous month, the mean air temperature and the average of relative humidity had positive effects on the outbreak risk and intensity. Meanwhile, the density of all mosquito species in livestock sheds (DMSL) only affected the outbreak risk. Moreover, the region-specific prediction model of JE was developed in Chongqing by used the Long Short-Term Memory Neural Network. Our study contributes to a better understanding of the JE dynamics and helps the local government establish precise prevention and control measures.

The present study aimed to explore the optimal zymogram of combination of 6 carbohydrases (glucoamylase, pullulanase, maltase, thermostable α-amylase, medium temperature α-amylase, and cold-active α-amylase) supplemented in corn-soybean based diet of broilers aged 1 to 3 wk for the maximum starch digestibility, by using in vitro simulated gastrointestinal digestion and response surface method. The third generation of simulated monogastric animal digestion system was used for in vitro digestion experiment. By using single factor completely random design, the optimal supplement levels of single carbohydras were determined by the reducing sugar release amount and improved dry matter digestibility, which were the parameters representing the starch digestibility of the diet. Additionally, Box-Behnken response surface method was used to predict the optimal combination of 6 carbohydrases. The results showed that the optimistic zymogram of 6 carbohydrases in corn-soybean based diet for broilers aged 1 to 3 wk were 297.39 U/g glucoamylase, 549.72 U/g pullulanase, 3.01 U/g maltase, 1,455.73 U/g thermostable α-amylase, 278.64 U/g medium temperature α-amylase, and 1,985.97 U/g cold-active α-amylase, and the associated reduced sugar release amount and improved dry matter digestibility were 215.98 mg/g, and 6.23%, respectively. Furthermore, we conducted in vitro digestion experiments with diets supplemented with the predicted optimistic zymogram and found that the experimental reduced sugar release amount and improved dry matter digestibility were 219.26 mg/g and 6.31% respectively, whose errors to the predicted optimistic reducing sugar release amount and the improved dry matter digestibility were 1.05% and 1.02%. To sum up, the predicted optimal zymogram of 6 carbohydrases in the present study were capable to improve the starch digestibility in diet for broilers aged 1 to 3 wk, which were represented by increased reduced sugar release amount and improved dry matter digestibility.

Mitochondrial genomes of vascular plants are well known for their liability in architecture evolution. However, the evolutionary features of mitogenomes at intra-generic level are seldom studied in vascular plants, especially among gymnosperms. Here we present the complete mitogenome of Cycas debaoensis, an endemic cycad species to the Guangxi region in southern China. In addition to assemblage of draft mitochondrial genome, we test the conservation of gene content and mitogenomic stability by comparing it to the previously published mitogenome of Cycas taitungensis. Furthermore, we explored the factors such as structural rearrangements and nuclear surveillance of double-strand break repair (DSBR) proteins in Cycas in comparison to other vascular plant groups. The C. debaoensis mitogenome is 413,715 bp in size and encodes 69 unique genes, including 40 protein coding genes, 26 tRNAs, and 3 rRNA genes, similar to that of C. taitungensis. Cycas mitogenomes maintained the ancestral intron content of seed plants (26 introns), which is reduced in other lineages of gymnosperms, such as Ginkgo biloba, Taxus cuspidata and Welwitschia mirabilis due to selective pressure or retroprocessing events. C. debaoensis mitogenome holds 1,569 repeated sequences (> 50 bp), which partially account for fairly large intron size (1200 bp in average) of Cycas mitogenome. The comparison of RNA-editing sites revealed 267 shared non-silent editing site among predicted vs. empirically observed editing events. Another 33 silent editing sites from empirical data increase the total number of editing sites in Cycas debaoensis mitochondrial protein coding genes to 300. Our study revealed unexpected conserved evolution between the two Cycas species. Furthermore, we found strict collinearity of the gene order along with the identical set of genomic content in Cycas mt genomes. The stability of Cycas mt genomes is surprising despite the existence of large number of repeats. This structural stability may be related to the relative expansion of three DSBR protein families (i.e., RecA, OSB, and RecG) in Cycas nuclear genome, which inhibit the homologous recombinations, by monitoring the accuracy of mitochondrial chromosome repair.

Mudstone interlayer is a weak layer in rock engineering. When it is subjected to continuous stress higher than its damage threshold, due to the dislocation of particles in mudstone crystals and the expansion of cracks, mudstone strength is gradually damaged and deteriorated and the strain gradually increases, thus accelerating the phenomenon of creep damage. In order to describe the characteristics of the whole process of mudstone aging deformation, based on the damage evolution of strength parameters (cohesion and internal friction coefficient) with stress and time in mudstone creep tests, a novel damage nonlinear viscoelastoplastic body (D-NVPB) is proposed through improving traditional plastic element. D-NVPB describes the nonlinear characteristics of the accelerated creep stage of mudstone. With the element combination method, D-NVPB is connected with the Burgers model in series to form a new nonlinear damage creep model (D-NVEP model). The analysis results of creep characteristics theoretically verified the rationality of the model in describing the instantaneous elasticity, viscoelasticity, and nonlinear viscoplastic characteristics of the complete creep curve of mudstone. With the data obtained in the uniaxial compression creep test of mudstone under the action of a stress level of 14 MPa, based on the Levenberg-Marquardt nonlinear least squares method, the fitting calculation was performed through piecewise fitting and overall fitting. The correlation coefficient was 0.9909, which verified the applicability of the model. The obtained model parameters by the identification were used to predict the mudstone creep curve under the stress levels of 13 MPa and 15 MPa. The good prediction results further verified the feasibility of the model. Compared with the traditional creep model, the D-NVEP model can better describe the nonlinear characteristics of the accelerated creep stage and quantitatively display the strength damage evolution process of rock in the creep failure process.

BackgroundThe population in Jiamusi has been reported to have the highest prevalence of colorectal cancer (CRC) in China. The genetic causal-effect for this occurrence among the residents remains unclear. Given the long cold seasons with people wearing more clothes and reduced UV exposure, we aimed to study the association between the vitamin D metabolism-related gene CYP24A1 polymorphism and CRC susceptibility.MethodA case-control study was conducted that included 168 patients with CRC and 710 age-matched healthy individuals as the control group. Plausible susceptible variations were sought and clinical phenotypic-genotype association analysis was performed.ResultsOverall, two CYP24A1 polymorphisms, rs6013905 AX (P = 0.02, OR = 1.89, 95%CI: 1.09-3.29) and rs2762939 GX (P = 0.02, OR = 1.52, 95%CI: 1.08-2.13) were significantly associated with CRC in the Jiamusi population. In the female group, three CYP24A1 polymorphisms, rs6013905 AX (P = 0.04, OR = 2.59, 95%CI: 1.03-6.49), rs2762939 GX (P = 0.01, OR = 2.35, 95%CI: 1.25-4.42), and rs6068816 GG (P = 0.05, OR = 1.89, 95%CI: 0.99-3.59) carriers were significantly associated with CRC. In clinical phenotypic-genotype analysis, rs6013905 GG (P = 0.05, OR = 4.00, 95%CI: 0.92-17.48) and rs2762939 GX (P = 0.03, OR = 4.87, 95%CI: 1.00-23.69) carriers were significantly associated with poorly differentiated CRC, while CYP24A1 rs6068816 AX was significantly associated with the tumor type (P = 0.02, OR = 2.08, 95%CI: 1.10-3.96) and location (P = 0.04, OR = 2.24, 95%CI: 1.05-4.77).ConclusionCYP24A1 gene polymorphism may be a genetic risk factor attributable to the highest prevalence of CRC in Jiamusi people. Individuals with CYP24A1 gene polymorphism may have an increased barrier for vitamin D absorption, thus contributing to the risk of CRC development.

Magnolol is a bioactive polyphenolic compound commonly found in Magnolia officinalis. The aim of this study is to clarify the contribution of the magnolol additive on the growth performance of Linwu ducklings aging from 7 to 28 d, comparing to the effects of antibiotic additive (colistin sulphate). A total of 325, 7-d-old ducklings were assigned to 5 groups. Each group had 5 cages with 13 ducklings in each cage. The ducklings in different groups were fed with diets supplemented with 0, 100, 200 and 300 mg/kg magnolol additive (MA) (Control, MA100, MA200 and MA300) and 30 mg/kg colistin sulphate (CS30) for 3 weeks, respectively. Parameters regarding to the growth performance, intestinal mucosal morphology, serum biochemical indices, antioxidant and peroxide biomarkers and the expression levels of antioxidant-related genes were evaluated by one way ANOVA analysis. The results showed that 30 mg/kg colistin sulphate, 200 and 300 mg/kg magnolol additive improved the average final weight (P = 0.045), average daily body weight gain (P = 0.038) and feed/gain ratios (P = 0.001) compared to the control group. 200 and 300 mg/kg magnolol additive significantly increased the villus height/crypt depth ratio of ileum, compared to the control and CS30 groups (P = 0.001). Increased serum level of glucose (P = 0.011) and total protein (P = 0.006) were found in MA200 or MA300 group. In addition, comparing to the control and CS30 groups, MA200 or MA300 significantly increased the levels of superoxide dismutase (P = 0.038), glutathione peroxidase (P = 0.048) and reduced glutathione (P = 0.039) in serum. Moreover, the serum and hepatic levels of 8-hydroxy-2’-deoxyguanosine (P = 0.043 and 0.007, respectively) were lower in all MA groups compared to those of the control and CS30 group. The hepatic mRNA expression levels of superoxide dismutase-1, catalase and nuclear factor erythroid-2-related factor 2/erythroid-derived CNC-homology factor were also increased significantly in MA200 and MA300 groups (P < 0.05). Taken together, these data demonstrated that MA was an effective feed additive enhancing the growth performance of Linwu ducklings at 7 to 28 d by improving the antioxidant and intestinal mucosal status. It suggested that MA could be a potential ingredient to replace the colistin sulphate in diets.

Wheat (Triticum aestivum L.) is one of the most important crops in the world, but the yield and quality of wheat are highly susceptible to heat stress, especially during the grain-filling stage. Therefore, it is crucial to select high-yield and high-temperature-resistant varieties for food cultivation. There is a positive correlation between the yield and photosynthetic rate of wheat during the entire grain-filling stage, but few studies have shown that lines with high photosynthetic rates can maintain higher thermotolerance at the same time. In this study, two pairs of wheat near isogenic lines (NILs) with different photosynthetic rates were used for all experiments. Our results indicated that under heat stress, lines with a high photosynthetic rate could maintain the activities of photosystem II (PSII) and key Calvin cycle enzymes in addition to their higher photosynthetic rates. The protein levels of D1 and HSP70 were significantly increased in the highly photosynthetic lines, which contributed to maintaining high photosynthetic rates and ensuring the stability of the Calvin cycle under heat stress. Furthermore, we found that lines with a high photosynthetic rate could maintain high antioxidant enzyme activity to scavenge reactive oxygen species (ROS) and reduce ROS accumulation better than lines with a low photosynthetic rate under high-temperature stress. These findings suggest that lines with high photosynthetic rates can maintain a higher photosynthetic rate despite heat stress and are more thermotolerant than lines with low photosynthetic rates.