Browse Articles

miRNA-328-3p regulates ZO-1 expression and inhibits PEDV proliferation via the PLC-β1-PKC pathway

Porcine epidemic diarrhea virus (PEDV) is a significant pathogen affecting swine, causing severe economic losses worldwide. This study explores the regulatory role of miRNA-328-3p to ZO-1 expression and its impact on PEDV proliferation via the PLC-β1-PKC pathway in IPEC-J2 cells. We found that miRNA-328-3p can target ZO-1, influencing its expression and subsequently affecting the integrity of tight junctions in the cells. Overexpression of PLC-β1, combined with miRNA-328-3p silencing, enhanced ZO-1 expression, while PLC-β1 knockdown combined with miRNA-328-3p overexpression inhibited ZO-1 expression. Furthermore, PLC-β1 overexpression increased both viral genome expression and PEDV titers, whereas its silencing had the opposite effect. Notably, our data indicated a negative correlation between PLC-β1 and PKC expression, and PKC silencing attenuated the upregulatory effect of PLC-β1 on ZO-1. These findings suggest that PLC-β1 modulates ZO-1 expression through the PKC pathway, providing new insights into the molecular mechanisms of PEDV infection and potential therapeutic targets.

Transcriptomic profiling and machine learning reveal novel RNA signatures for enhanced molecular characterization of Hashimoto’s thyroiditis

Research on the mechanism by which digital transformation peer effects influence innovation performance in emerging industries: A case study of China’s photovoltaic industry

The exploration of digital transformation peer effects on the innovation performance of emerging industries is crucial for analyzing the underlying mechanisms of digital transformation, optimizing resource allocation among peer enterprises, and enhancing industrial competitiveness. This study empirically examines the influence of digital transformation peer effects on the innovation performance of the photovoltaic industry, using data from 150 photovoltaic companies listed in Shanghai and Shenzhen between 2011 and 2022. The study found that: (1) The digital transformation of the photovoltaic industry is influenced by regional and industry-specific peer effects. Regional peer effects in digital transformation have a positive impact on the innovation performance of the photovoltaic industry, while industry-specific peer effects exert a negative impact on innovation performance. Moreover, these effects exhibit dynamic persistence; (2) Further analysis of the transmission mechanism reveals that the digital transformation peer effect positively influences the innovation performance of the photovoltaic industry, primarily through the mediating role of enhanced absorptive capacity. Additionally, the level of marketization and executive tenure significantly moderate this relationship; (3) The study further investigates the photovoltaic industry within the context of subsidy policy implementation, firm types, and strategic pacing. The results indicate that the digital transformation peer effect on innovation performance is most pronounced for technology-intensive firms adopting an analytical strategy after the withdrawal of photovoltaic subsidies. For labor-intensive firms employing a defensive strategy, the peer effect is more significant before the withdrawal of subsidies. In contrast, the negative impact of industry-specific digital transformation peer effects on innovation performance is more evident in photovoltaic companies that pursue an offensive strategy; (4) The heterogeneity analysis reveals that the digital transformation peer effect on innovation performance is more significant for small-scale photovoltaic enterprises with state-owned property rights. In contrast, the peer effect negatively impacts innovation performance in large-scale photovoltaic enterprises. These findings provide theoretical insights and practical guidance for governments and enterprises in formulating digital transformation strategies for emerging industries.

Perennial disaster patterns in Central Europe since 2000 and implications for hospital preparedness planning – a cross-sectional analysis

AbstractThe goal of this analysis is to describe seasonal disaster patterns in Central Europe in order to raise awareness and improve hospital disaster planning and resilience, particularly during peak events. Hospitals are essential pillars of a country’s critical infrastructure, vital for sustaining healthcare services and supporting public well-being—a key issue of national security. Disaster planning for hospitals is crucial to ensure their functionality under special circumstances. But the impact of climate change and seasonal variations in the utilization of hospital services are raising challenges. Therefore, the knowledge of perennial disaster patterns could help strengthen the resilience of hospitals. We conducted a cross-sectional analysis of the Emergency Events Database EM-DAT for disasters in Central Europe (Germany, France, Denmark, The Netherlands, Belgium, Luxembourg, Switzerland, Austria, Czech Republic, and Poland) between January 2000 and December 2023. Time distribution of disasters, patterns and longitudinal trends, were analyzed to discuss impact on disaster preparedness in hospitals. Out of 474 events, 83% were associated with a natural hazard and only 80 events (17%) were of technological cause. While technological disasters were spread equally over the whole year, the vast majority of disasters related to natural hazards (n = 394), i.e. storms (n = 178, 45%), floods (n = 101, 26%), and extreme temperatures (n = 93, 24%) peaked during summer and winter months. Fewer disasters were registered during autumn and especially spring seasons. More than 50% of the technological disasters were categorized in the transport accident subgroup. Technological disasters were spread equally over the whole year. Looking at the three most common disaster types, extreme temperatures, floods, and storms are clearly dominating and cause over 90% of the disasters due to natural hazards in central Europe. Overall, the number of events per year fluctuates without a clear trend, only the technological events appear to become less frequent with 70% (n = 56) of the registered disasters occurring in the first half of the study period (2000–2011). An overlap of hospital admissions due to seasonal effects and catastrophic events, mainly triggered by disasters of natural cause in vulnerable periods may lead to a partial collapse of the health care system. To close knowledge gaps, future comprehensive data collection is vital for informed decision-making. Awareness and preparedness are key: an "all-hazards" approach to manage diverse, potentially simultaneous seasonal threats is often the most versatile strategy for hospital emergency planning.

Does music counteract mental fatigue? A systematic review

Introduction Mental fatigue, a psychobiological state induced by prolonged and sustained cognitive tasks, impairs both cognitive and physical performance. Several studies have investigated strategies to counteract mental fatigue. However, potential health risks and contextual restrictions often limit these strategies, which hinder their practical application. Due to its noninvasive and portable nature, music has been proposed as a promising strategy to counteract mental fatigue. However, the effects of music on performance decrements vary with different music styles. Synthesizing studies that systematically report music style and its impact on counteracting performance decrements is crucial for theoretical and practical applications. Objectives This review aims to provide a comprehensive systematic analysis of different music styles in counteracting mental fatigue and their effects on performance decrements induced by mental fatigue. Additionally, the mechanisms by which music counteracts mental fatigue will be discussed. Methods A comprehensive search was conducted across five databases—Web of Science, PubMed, SCOPUS, SPORTDiscus via EBSCOhost, and the Psychological and Behavioral Sciences Collection via EBSCOhost—up to November 18, 2023. The selected studies focused solely on music interventions, with outcomes including subjective feelings of mental fatigue, physiological markers, and both cognitive and behavioral performance. Results Nine studies met the predetermined criteria for inclusion in this review. The types of music interventions that counteract mental fatigue include relaxing, exciting, and personal preference music, all of which were associated with decreased subjective feelings of mental fatigue and changes in objective physiological markers. Cognitive performance, particularly in inhibition and working memory tasks impaired by mental fatigue, was countered by both relaxing and exciting music. Exciting music was found to decrease reaction time more effectively than relaxing music in working memory tasks. The physiological marker of steady-state visually evoked potential-based brain-computer interface (SSVEP-BCI) amplitude increased, confirming that exciting music counteracts mental fatigue more effectively than relaxing music. Behavioral performance in tasks such as arm-pointing, the Yo-Yo intermittent test, and the 5 km time-trial, which were impaired by mental fatigue, were counteracted by personal preference music. Conclusion Relaxing music, exciting music, and personal preference music effectively counteract mental fatigue by reducing feelings of fatigue and mitigating performance decrements. Individuals engaged in mentally demanding tasks can effectively counteract concurrent or subsequent cognitive performance decrements by simultaneously listening to relaxing or exciting music without lyrics or by using music during recovery from mental fatigue. Exciting music is more effective than relaxing music in counteracting mental fatigue. Personal preference music is effective in counteracting behavioral performance decrements in motor control and endurance tasks. Mentally fatigued individuals could apply personal preference music to counteract subsequent motor control performance decrements or simultaneously listen to it to counteract endurance performance decrements. Future studies should specify and examine the effects of different music genres, tempos, and intensities in counteracting mental fatigue. Additionally, the role of music in counteracting mental fatigue in contexts such as work productivity, traffic accident risk, and sports requires further investigation, along with the underlying mechanisms.

The anthelmintic activity of the white wormwood (Artemisia herba Alba) against Haemonchus contortus in beef cattle

Networks of care for optimizing Primary Health Care Service Delivery in Ethiopia: Enhancing relational linkages and care coordination

Introduction Ethiopia has made notable progress in reducing maternal and perinatal mortality, yet challenges remain in meeting the 2030 Sustainable Development Goals. Persistent issues such as low service utilization, coupled with poor quality, fragmented care, and ineffective referral systems hinder progress. The "Improve Primary Health Care Service Delivery (IPHCSD)" project, implemented by JSI and Amref Health Africa since April 2022, seeks to address these gaps through a Networks of Care (NoCs) approach. This paper describes the lessons learned from implementing the NoCs approach to optimize primary health care in Ethiopia. Methods The project incorporates embedded implementation science, guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework. Key implementation strategies co-designed included strengthening community engagement, establishing NoCs, and introducing quality improvement initiatives using the Model for Improvement. Routine program monitoring data, NoCs process evaluation, and facility service statistics were utilized for this study. Service statistics were analyzed using Student’s t-test and interrupted time-series analysis to compare maternal and child care outcomes before and after the NoCs intervention, with counterfactual estimates generated to assess the intervention’s impact. Qualitative data from key informant interviews were transcribed, coded, and analyzed to identify themes and patterns using Atlas.ti. Results The NoCs approach has significantly enhanced relational linkages between primary health care facilities and health care providers, fostering stronger collaboration and communication. This has fostered trust, improved care coordination, optimized primary health care performance, and increased health service utilization within woreda health systems. The interrupted time series analysis indicated that the rate of ANC 8+ visits was 29.8% per month higher than expected without the NoCs strategy (Coef: 2.39; p-value < 0.01) and an 18.4% increase in obstetric complications managed (Coef: 1.71; p-value = 0.050), with a 43% overall increase. Perinatal mortality decreased by 34%, from 31.3 to 20.1 per 1,000 births [t-test: 2.12; p-value: 0.040)]. Conclusion The NoCs approach in Ethiopia has proven effective in enhancing the relational elements, care coordination, and quality of primary health care services, leading to better maternal and child health outcomes. The findings expand the existing body of research on NoCs implementation best practices and further confirm that it provides a scalable model for strengthening health services in low-resource settings.

Aboveground and belowground trait coordination across twelve boreal forest tree species

AbstractThe existence of trait coordination in roots and leaves has recently been debated, with studies reaching opposing conclusions. Here, we assessed trait coordination across twelve boreal tree species. We show that there is only partial evidence for above-belowground coordination for “fast-slow” economic traits across boreal tree species, i.e., while N content in leaves and roots were positively correlated, as well as dry matter content, root dry matter content and leaf N had no significant relationship. For resource acquisition traits (i.e. related to light capture and nutrient uptake) we did not find strong evidence for trait coordination, as specific root length and specific leaf area were not positively correlated. We further show that site only explained between 0 and 7% of the total trait variation, while within-site variation contributed substantially to the total trait variation for a large number of traits (1.6–96%), and more so for morphological root traits than leaf traits. This likely influences the strength of above-belowground trait coordination found across species in our study. Understanding sources of trait variation and above-belowground trait relationships can contribute to improving global and regional C cycling models. However, fine-scale environmental variability should be accounted for given its importance for driving trait variation.

Disability and depression among stroke survivors attending rehabilitation facilities at three designated tertiary care hospitals in Bangladesh: A cross-sectional study

Background Poststroke depression (PSD) is a highly prevalent and serious mental health condition affecting a significant proportion of stroke survivors worldwide. While its exact causes remain under investigation, managing PSD presents a significant challenge. Aim This study aimed to evaluate the prevalence and predictors of depression among Bangladeshi stroke victims. Methods A cross-sectional study was carried out with 725 stroke victims who were receiving medical care at three designated tertiary care hospitals in Sylhet from January to December 2023. Depression and disability were measured using the Patient Health Questionnaire-9 and the Modified Rankin Scale. Logistic regression analysis was employed to examine the predictors linked to depression. Results According to the study, 80.8% of individuals had moderate to severe disability, and 58.1% of them experienced a moderate to severe level of depression. Individuals who had hemorrhagic stroke (AOR 1.31, 95% CI: 0.77–2.25), repeated episodes (AOR 3.41, 95% CI: 1.89–6.14), tobacco use (AOR 1.76, 95% CI: 1.16–2.67), or coexisting health conditions (AOR 1.68, 95% CI: 1.00–2.82) exhibited elevated levels of depression. Participants whose medical expenses covered by relatives or others were six times more likely to experience depressive symptoms (AOR 6.32, 95% CI: 1.61–24.76). Individuals who did not receive rehabilitation services had two times greater odds of being depressed (OR 1.85, 95% CI: 1.23–2.77, p = 0.003). Consequently, individuals with low functional status had eleven times greater levels of depression (AOR 11.03, 95% CI: 7.14–17.04). Conclusion More than half of the participants in this present study reported moderate to extreme levels of depression which is a serious health issue among Bangladeshi stroke survivors. Understanding the predictors of depression linked to stroke could enhance the effectiveness of therapeutic interventions for this condition. In addition, multidisciplinary teams should work collaboratively to address this serious issue.

Salvia pratensis L. extracts as potential eco-friendly herbicides for sustainable agricultural applications

Seizures elicited by transcorneal 6 Hz stimulation in developing rats

Seizures elicited by corneal 6-Hz stimulation are widely acknowledged as a model of temporal lobe seizures. Despite the intensive research in rodents, no studies hint at this model in developing animals. We focused on seven age groups of both male and female rats. Biphasic pulses with 0.3 ms duration and current intensities from 20 to 80 mA were applied transcorneally for 3 s to calculate threshold intensities for individual age groups. Threshold stimulation intensity necessary for elicitation of clonic seizures was highly age- and sex-dependent. The highest threshold was observed in the youngest (15-day-old) group then it decreased to the age of 25 days and increased again up to adulthood. The threshold current tended to be lower in females of all age groups. The incidence of convulsive seizures increased with stimulation intensity up to postnatal day 25 in either sex. In rats of 31 days old and older convulsions occurred irregularly regardless of the stimulation current and sex. For subsequent analysis, the animals were categorized into two groups: juveniles, aged 15 to 25 days, and adolescents/adults, aged 31 days and older. Our statistical analyses revealed an increased risk of convulsions after the stimulation with higher intensities in juvenile but not adolescent/adult rats. Females tended to be more sensitive to the stimulation with lower currents than males. Seizure severity was higher in females 18- to 25-day old compared to males of the same age and the seizure duration increased with stimulation intensities in juvenile but not adolescent/adult animals. The data extend the use of the rat 6 Hz model to immature animals and may be useful as a model of pediatric temporal lobe seizures.

Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment

Multi-feature fusion-based consumer perceived risk prediction and its interpretability study

E-commerce faces challenges such as content homogenization and high perceived risk among users. This paper aims to predict perceived risk in different contexts by analyzing review content and website information. Based on a dataset containing 262,752 online reviews, we employ the KeyBERT-TextCNN model to extract thematic features from the review content. Subsequently, we combine these thematic features with product and merchant characteristics. Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. In the feature extraction phase, we identified 11 key features that influence perceived risk in online shopping. During the prediction phase, the model performs excellently across different sample types in the test set, achieving a precision (P) of 84%, a recall (R) of 86%, and an F1 score of 85%. Through the model’s interpretability analysis, we find that quality, functionality, and price are key features affecting perceived risk for electronic products. In the case of skincare products, skin safety is the most critical feature. Additionally, there are significant differences in feature characteristics between high-risk samples and normal samples.

Adaptive average arterial pressure control by multi-agent on-policy reinforcement learning

Forward-backward translation, content validity, face validity, construct validity, criterion validity, test-retest reliability, and internal consistency of a questionnaire on patient acceptance of orthodontic retainer

This study aimed to assess the validity and reliability of a questionnaire on patient acceptance of orthodontic retainers. The original questionnaire was forward- and backward-translated, followed by four validity tests (content validity, face validity, construct validity, criterion validity) and two reliability tests (test-retest reliability, internal consistency). Content validity was assessed by nine orthodontists who appraised the questionnaire’s representativeness, relevance, clarity, and necessity. Face validity was established through semi-structured in-depth interviews with 35 English-literate participants currently wearing orthodontic retainers. Construct validity was established through Exploratory Factor Analysis (EFA). For criterion validity, 107 participants concurrently answered the questionnaire and the Retainer-modified Malaysian Oral Health Impact Profile questionnaire. Test-retest reliability was verified by 34 subjects who responded to the questionnaire again after a two-week interval. Six revised items passed the threshold value of 0.78 for Item-Content Validity Index and Content Validity Ratio and were revised based on findings from the face validity test. Principal Component Analysis of EFA extracted information on only one component, and all items were positively correlated with the component matrix. Spearman’s rho value (rs = 0.490 and rs = 0.416) indicated a moderate correlation between the two questionnaires for criterion validity. Intraclass Correlation Coefficient ranged from 0.687 to 0.913, indicating moderate to excellent test-retest reliability. Cronbach’s alpha ranged from 0.687 to 0.913 indicating that none of the questionnaire items showed unacceptable or poor internal consistency. The questionnaire on patient acceptance of orthodontic retainers has been validated and can be used in both clinical and research settings.

Vessel strike encounter risk model informs mortality risk for endangered North Atlantic right whales along the United States east coast

AbstractVessel strikes are a critical threat to endangered North Atlantic right whales (Eubalaena glacialis), significantly contributing to their elevated mortality. Accurate estimates of these mortality rates are essential for developing effective management strategies to aid in the species’ recovery. This study enhances existing vessel strike models by incorporating detailed regional data on vessel traffic characteristics as well as whale distribution and behavior. Our model assesses the spatial and temporal variability in vessel strike risk along the U.S. east coast apportioned into three vessel length classes (26–65 feet, 65–350 feet, > 350 feet). By including regional right whale depth distributions and parameterizing potential whale avoidance based on factors such as descent rate, bottom depth, and vessel speed and size, the model provides a refined estimation of mortality risk. We also address the underrepresentation of smaller vessel activity via a correction factor, offering a more accurate annual mortality risk estimate for each vessel size class. These findings highlight that vessels > 350 feet in length pose the greatest risk to right whales. Simulations of reduced vessel speeds indicate that speed measures can mitigate mortality rates; however, residual risk remains even at speeds of 10 knots or less suggesting limitations to this mitigation approach.

An exploratory review of resiliency assessments after brain injury

Background People with brain injury can have lower resiliency compared to the general public. Yet, resiliency facilitates positive processes to negotiate adversity after brain injury. Therefore, measuring resiliency after a brain injury is important. Objective The review aimed to (1) identify self-report resiliency outcome measures for use with people after acquired brain injury, using the process-based Traumatic Brain Injury Resiliency Model as the guiding conceptual framework, and (2) summarize the psychometric properties of the identified outcome measures and the utility of these measures in clinical rehabilitation. Method The COSMIN guidelines for systematic reviews were followed to ensure appropriate reporting for each measure. Databases CINAHL, EMBASE, Medline, and PsychINFO were searched and independently reviewed by two people. Articles providing data on psychometric properties for measures of resilience for people with brain injury were retrieved. Psychometric properties and clinical utility (number of items, scoring details) were summarized. Results Thirty-two articles were retrieved, including nine measures of resiliency: Acceptance and Action Questionnaire–Acquired Brain Injury, Confidence after Stroke Measure, Connor-Davidson Resilience Scale, Daily Living Self-Efficacy Scale, General Self-Efficacy Scale, Participation Strategies Self-Efficacy Scale, Resilience Scale, Robson Self-Esteem Scale, and the Stroke Self-Efficacy Questionnaire. All measures have acceptable to excellent psychometric properties in accordance with the COSMIN guidelines. Conclusion There are established measures of resiliency in brain injury rehabilitation. Future work may explore use of these measures in a clinical context and implementation of rehabilitation goals for improving resiliency after brain injury.

Analysis of the interaction mechanism between straw soil rotary tillage blade during rotary tillage process

A weak edge estimation based multi-task neural network for OCT segmentation

Optical Coherence Tomography (OCT) offers high-resolution images of the eye’s fundus. This enables thorough analysis of retinal health by doctors, providing a solid basis for diagnosis and treatment. With the development of deep learning, deep learning-based methods are becoming more popular for fundus OCT image segmentation. Yet, these methods still encounter two primary challenges. Firstly, deep learning methods are sensitive to weak edges. Secondly, the high cost of annotating medical image data results in a lack of labeled data, leading to overfitting during model training. To tackle these challenges, we introduce the Multi-Task Attention Mechanism Network with Pruning (MTAMNP), consisting of a segmentation branch and a boundary regression branch. The boundary regression branch utilizes an adaptive weighted loss function derived from the Truncated Signed Distance Function(TSDF), improving the model’s capacity to preserve weak edge details. The Spatial Attention Based Dual-Branch Information Fusion Block links these branches, enabling mutual benefit. Furthermore, we present a structured pruning method grounded in channel attention to decrease parameter count, mitigate overfitting, and uphold segmentation accuracy. Our method surpasses other cutting-edge segmentation networks on two widely accessible datasets, achieving Dice scores of 84.09% and 93.84% on the HCMS and Duke datasets.

Microwave-induced degradation of Congo red dye in the presence of 2D Ti3C2Tx MXene as a catalyst

AbstractIn this research, the degradation of Congo red (CR) dye, as an organic pollutant in water, was investigated using microwave-induced reaction technology. This technology requires a microwave-absorbing catalyst and the 2D Ti3C2Tx MXene was synthesized for that purpose. The synthesized catalyst was characterized using XRD, SEM, TEM, EDX, BET, and XPS techniques. Results showed that the prepared 2D Ti3C2Tx MXene with a dosage of 50 mg degraded CR dye with an initial concentration of 25 ppm in an aqueous solution with a degradation percentage of approximately 99% in only 6 min. The parameters studied were catalyst dosage and initial CR dye concentration, which were found to have significant impacts on the degradation rate. When the catalyst dosage was increased significantly, the degradation rate increased significantly. On the other hand, when increasing the initial CR dye concentration, the degradation rate decreased. The degradation kinetics were studied, and the reaction followed the pseudo-first-order model. The rate constants obtained ranged from 0.04 to 0.83 min−1, varying according to the used catalyst dosage and initial CR dye concentration. The catalyst was stable and could be reused for up to five catalytic cycles without losing its degradation efficiency. The active species participating in the degradation process were determined using scavengers such as benzoquinone, Na-EDTA, and isopropyl alcohol. Optimization of the degradation parameters using a response surface methodology study concluded that a maximum degradation percentage could be reached when employing 35.30 mg of 2D Ti3C2Tx MXene and 29.07 ppm of CR dye solution.