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PURPOSE: To improve the quality of community health nursing practice, the learning outcomes of nursing students in community health nursing courses must be enhanced. Although the flipped classroom is considered an effective innovative teaching strategy, evidence of its application in community health nursing courses is limited. Therefore, this study aimed to examine the effects of a flipped classroom approach on community nursing competence, academic performance, course engagement, and learning satisfaction for a community health nursing course. DESIGN: A quasi-experimental study design was adopted between September 2021 and January 2022. METHODS: Two classes of nursing students (n = 92) from a 2-year nursing program at a university in Taiwan were recruited. The classes were randomly assigned to the intervention group (n = 50) that attended a flipped classroom and the control group (n = 42) that received traditional lecture-based instruction. FINDINGS: Compared with the control group, the intervention group demonstrated significantly greater improvements in community nursing competence (p = .012) and significantly higher academic performance (p = .005). In addition, the course engagement and learning satisfaction of the two groups were high, but not significantly different. CONCLUSIONS: A flipped classroom can be an important strategy to enhance community nursing competence and academic performance. CLINICAL EVIDENCE: The flipped classroom strategy can enhance community nursing competence of nursing students, which may improve the quality of population-based healthcare.
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This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) and three platforms (Bard, Bing, ChatGPT-3.5). Utilizing previously published cases, we asked identical questions to chatbots from each location within a 24-h window. Responses were evaluated in a double-blinded manner on relevance, clarity, depth, focus, and coherence by ten experts in endometrial cancer. Our analysis revealed significant variations across different countries/regions (p < 0.001). Interestingly, Bing's responses in Nigeria consistently outperformed others (p < 0.05), excelling in all evaluation criteria (p < 0.001). Bard also performed better in Nigeria compared to other regions (p < 0.05), consistently surpassing them across all categories (p < 0.001, with relevance reaching p < 0.01). Notably, Bard's overall scores were significantly higher than those of ChatGPT-3.5 and Bing in all locations (p < 0.001). These findings highlight disparities and opportunities in the quality of AI-powered healthcare information based on user location and platform. This emphasizes the necessity for more research and development to guarantee equal access to trustworthy medical information through AI technologies.
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Inteligencia Artificial , Humanos , Femenino , Nigeria , Taiwán , Estados UnidosRESUMEN
Autoantibodies against apolipoprotein A-I (ApoA-I) are associated with cardiovascular disease risks. We aimed to examine the 4-hydroxy-2-nonenal (HNE) modification of ApoA-I in coronary artery disease (CAD) and evaluate the potential risk of autoantibodies against their unmodified and HNE-modified peptides. We assessed plasma levels of ApoA-I, HNE-protein adducts, and autoantibodies against unmodified and HNE-peptide adducts, and significant correlations and odds ratios (ORs) were examined. Two novel CAD-specific HNE-peptide adducts, ApoA-I251-262 and ApoA-I70-83, were identified. Notably, immunoglobulin G (IgG) anti-ApoA-I251-262 HNE, IgM anti-ApoA-I70-83 HNE, IgG anti-ApoA-I251-262, IgG anti-ApoA-I70-83, and HNE-protein adducts were significantly correlated with triglycerides, creatinine, or high-density lipoprotein in CAD with various degrees of stenosis (<30% or >70%). The HNE-protein adduct (OR = 2.208-fold, p = 0.020) and IgM anti-ApoA-I251-262 HNE (2.046-fold, p = 0.035) showed an increased risk of progression from >30% stenosis in CAD. HNE-protein adducts and IgM anti-ApoA-I251-262 HNE may increase the severity of CAD at high and low levels, respectively.
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BACKGROUND: Previous studies show that using 12-lead electrocardiogram (ECG) or 24-h ECG monitor for the detection of cardiac arrhythmia events in patients with stroke or syncope is ineffective. HYPOTHESIS: The 14-day continuous ECG patch has higher detection rates of arrhythmias compared with conventional 24-h ECG monitoring in patients with ischemic stroke or syncope. METHODS: This cross-sectional study of patients with newly diagnosed ischemic stroke or syncope received a 24-h ECG monitoring and 14-day continuous cardiac monitoring patch and the arrhythmia events were measured. RESULTS: This study enrolled 83 patients with ischemic stroke or syncope. The detection rate of composite cardiac arrhythmias was significantly higher for the 14-day ECG patch than 24-h Holter monitor (69.9% vs. 21.7%, p = .006). In patients with ischemic stroke, the detection rates of cardiac arrhythmias were 63.4% for supraventricular tachycardia (SVT), 7% for ventricular tachycardia (VT), 5.6% for atrial fibrillation (AF), 4.2% for atrioventricular block (AVB), and 1.4% for pause by 14-day ECG patch, respectively. The significant difference in arrhythmic detection rates were found for SVT (45.8%), AF (6%), pause (1.2%), AVB (2.4%), and VT (9.6%) by 14-day ECG patch but not by 24-h Holter monitor in patients with ischemic stroke or syncope. CONCLUSIONS: A 14-day ECG patch can be used on patients with ischemic stroke or syncope for the early detection of AF or other cardiac arrhythmia events. The patch can be helpful for physicians in planning medical or mechanical interventions of patients with ischemic stroke and occult AF.
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Fibrilación Atrial , Bloqueo Atrioventricular , Accidente Cerebrovascular Isquémico , Taquicardia Ventricular , Humanos , Estudios Transversales , Síncope/diagnóstico , Síncope/etiología , ElectrocardiografíaRESUMEN
BACKGROUND: Sentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its colloquialism and multilingualism, make it different from other languages and pose additional challenges to sentiment analysis. Recent advances in models such as ChatGPT offer potential viable solutions. OBJECTIVE: This study investigated the efficacy of GPT-3.5 and GPT-4 in Cantonese sentiment analysis in the context of web-based counseling and compared their performance with other mainstream methods, including lexicon-based methods and machine learning approaches. METHODS: We analyzed transcripts from a web-based, text-based counseling service in Hong Kong, including a total of 131 individual counseling sessions and 6169 messages between counselors and help-seekers. First, a codebook was developed for human annotation. A simple prompt ("Is the sentiment of this Cantonese text positive, neutral, or negative? Respond with the sentiment label only.") was then given to GPT-3.5 and GPT-4 to label each message's sentiment. GPT-3.5 and GPT-4's performance was compared with a lexicon-based method and 3 state-of-the-art models, including linear regression, support vector machines, and long short-term memory neural networks. RESULTS: Our findings revealed ChatGPT's remarkable accuracy in sentiment classification, with GPT-3.5 and GPT-4, respectively, achieving 92.1% (5682/6169) and 95.3% (5880/6169) accuracy in identifying positive, neutral, and negative sentiment, thereby outperforming the traditional lexicon-based method, which had an accuracy of 37.2% (2295/6169), and the 3 machine learning models, which had accuracies ranging from 66% (4072/6169) to 70.9% (4374/6169). CONCLUSIONS: Among many text analysis techniques, ChatGPT demonstrates superior accuracy and emerges as a promising tool for Cantonese sentiment analysis. This study also highlights ChatGPT's applicability in real-world scenarios, such as monitoring the quality of text-based counseling services and detecting message-level sentiments in vivo. The insights derived from this study pave the way for further exploration into the capabilities of ChatGPT in the context of underresourced languages and specialized domains like psychotherapy and natural language processing.
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Inteligencia Artificial , Pueblo Asiatico , Comunicación , Lenguaje , Humanos , Consejeros , Hong Kong , Modelos LinealesRESUMEN
Ultrafast excited-state dynamics of the simplest nitrostilbenes, namely trans-4-nitrostilbene (t-NSB), was studied in solvents of various polarities with ultrafast broadband time-resolved fluorescence and transient absorption spectroscopies, and by quantum-chemical computations. The results revealed that the initially excited S1(ππ*) state deactivation dynamics is strongly influenced by the solvent polarity. Specifically, the t-NSB S1-state lifetime decreases by three orders of magnitude from â¼60 ps in high-polarity solvents to â¼60 fs in nonpolar solvents. The strong solvent-polarity dependence arises from the differences in dipole moments among the S1 and relevant states, including the major intersystem crossing (ISC) receiver triplet states, and therefore, the solvent polarity can modulate their relative energies and ISC rates. In nonpolar solvents, the sub-100 fs lifetime is due to a combination of efficient ISC and internal conversion. In medium-polarity solvents, the S1-state population decays via a competing ISC relaxation mechanism in a biphasic manner, and the ISC rates are found to obey the inverse energy gap law of the strong coupling case. In high-polarity solvents, the S1 state is stabilized to a much lower energy such that ISC becomes energetically infeasible, and the S1 state decays via barrier crossing along the torsion angle of the central ethylenic bond to the nonfluorescent perpendicular configuration. Regardless of the initial S1-state deactivation pathways in various solvents, the excited-state population is ultimately trapped in the metastable T1-state perpendicular configuration, at which a slower ISC occurs to bring the system to the ground state and bifurcate into either trans or cis form of NSB.
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BACKGROUND: Marriage has long been considered protective against suicide, but shifting social norms since 2000 in Hong Kong raise doubts regarding whether this is still the case. The aim of the study was to investigate the changing association between suicide and marital status. METHODS: Official suicide data for 2002-2020 in Hong Kong were obtained. Suicide rates and suicide risk ratios were calculated by gender, age group, and marital status (married, never-married, widowed, divorced/separated). RESULTS: Suicide risk decreased significantly over time for men and women of all ages. People who were never-married, divorced/separated, had significantly higher suicide risks than their married counterparts. Increasing suicide risks over time were observed for never-married men aged 20-49 years, never-married women aged 35-49 years, and divorced/separated men aged 20-34 years. Widowed men and women of any age had higher suicide risks compared with previous studies in Hong Kong. LIMITATIONS: Marital status is a time-varying covariate, and the time spent in a given marital status could affect suicide risk. Some age and gender subgroups had much smaller sample sizes than others, thus it is possible that our suicide risk estimates were overestimated. CONCLUSIONS: Despite rapidly social changing in Hong Kong during the study period, marriage remains a strong protective factor against suicide for men and women. The protective effect is particularly evident for younger people. Increasing suicide rates for divorced/separated, never-married, or widowed people suggest that they require more psychosocial support.
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Matrimonio , Suicidio , Masculino , Femenino , Humanos , Factores Protectores , Hong Kong/epidemiología , Estado Civil , DivorcioRESUMEN
Background: Suicide is a complex and multifaceted issue, and suicidal behaviors are often driven by multiple, interacting factors. It has been challenging to identify reasons for suicide using existing scientific methodologies. This study aims to identify critical reasons for suicide and suicidal behaviors through the application of novel network science methods. Methods: Based on cases investigated by the Hong Kong Coroner's Court from 2002 to 2019, we modelled identified reasons for 13,001 suicide cases as a co-occurrence network, and calculated each reason's eigencentrality to determine their respective relative importance. We then analyzed the temporal and demographic changes in the structure and eigencentrality of the network. We further conducted simulation studies based on the United Nations population projection to assess potential burden of different reasons for suicide on the population in the coming years. Findings: School-related issues had the highest eigencentrality (eigencentrality = 0.49) for individuals younger than 20 years of age. Financial issues were crucial for adults aged 20-59 years, but their importance differed between males (eigencentrality = 0.51) and females (eigencentrality = 0.14). Physical illness (eigencentrality = 0.80) was the core concern for adults over 60 years. Across the Hong Kong population, the reasons for suicide appear to have shifted from financial issues in the early 2000s (eigencentrality = 0.46) to issues related to physical illnesses since 2011 (eigencentrality = 0.58). Simulation findings indicate that, by 2050, most suicides in Hong Kong will be due to physical illness-related issues (eigencentrality = 0.69) due to the rapidly aging population. Interpretation: There have been important sex and age differences over time, in reasons for suicide. Given the projected increasing age of the Hong Kong population over the next decades, older adults with physical illnesses appear to be the highest contributors to suicide cases in the overall population. This novel network analysis approach provides important data-driven information upon which to base effective proactive public health suicide prevention strategies and interventions. Funding: Hong Kong Jockey Club Charities Trust, Collaborative Research Fund (C7151-20G), and General Research Fund (17606521).
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The ubiquity of Internet gaming as part of the younger generation's (11-35 year-olds) lifestyle to-day warrants a deeper understanding of its impact on their mental health. In particular, there has been scant research investigating the link between Internet Gaming Disorder (IGD) and suicidal behaviors in this demographic group, even though several mental health symptoms of the former are known risk factors for the latter. This paper aims to establish the presence or absence of association between IGD and each of suicidal ideation, self-harm, and suicide attempt among the younger generation. A large-scale online survey on Internet gamers in Hong Kong was conducted in February 2019. 3430 respondents were recruited through purposive sampling. Study samples were stratified into distinct age groups and multiple logistic regression was conducted for each measured suicidal behavior in each age group. After controlling for sociodemographics, Internet usage, self-reported bullying perpetration and bullying victimization, social withdrawal, and self-reported psychiatric diagnoses such as depression and psychosis, analyses revealed that adolescent (11-17 year-old) gamers with IGD were more likely than their peers who had no IGD to have had suicidal ideation, self-harm, and suicide attempt in their lifetime. These associations did not hold for 18-35 year-old gamers. Findings suggest that it may be prudent to recognize IGD as a growing public mental health priority for the young populace, particularly adolescents. Existing suicide prevention efforts can be complemented through screening adolescents for IGD, and could be expanded to online gaming platforms to reach more hidden at-risk individuals.
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Conducta Adictiva , Juegos de Video , Adolescente , Humanos , Niño , Adulto Joven , Adulto , Ideación Suicida , Modelos Logísticos , Trastorno de Adicción a Internet , Conducta Adictiva/diagnóstico , Encuestas y Cuestionarios , InternetRESUMEN
BACKGROUND: Individual organisms may exhibit phenotypic plasticity when they acclimate to different conditions. Such plastic responses may facilitate or constrain the adaptation of their descendant populations to new environments, complicating their evolutionary trajectories beyond the genetic blueprint. Intriguingly, phenotypic plasticity itself can evolve in terms of its direction and magnitude during adaptation. However, we know little about what determines the evolution of phenotypic plasticity, including gene expression plasticity. Recent laboratory-based studies suggest dominance of reversing gene expression plasticity-plastic responses that move the levels of gene expression away from the new optima. Nevertheless, evidence from natural populations is still limited. RESULTS: Here, we studied gene expression plasticity and its evolution in the montane and lowland populations of an elevationally widespread songbird-the Rufous-capped Babbler (Cyanoderma ruficeps)-with reciprocal transplant experiments and transcriptomic analyses; we set common gardens at altitudes close to these populations' native ranges. We confirmed the prevalence of reversing plasticity in genes associated with altitudinal adaptation. Interestingly, we found a positive relationship between magnitude and degree of evolution in gene expression plasticity, which was pertinent to not only adaptation-associated genes but also the whole transcriptomes from multiple tissues. Furthermore, we revealed that genes with weaker expressional interactions with other genes tended to exhibit stronger plasticity and higher degree of plasticity evolution, which explains the positive magnitude-evolution relationship. CONCLUSIONS: Our experimental evidence demonstrates that species may initiate their adaptation to new habitats with genes exhibiting strong expression plasticity. We also highlight the role of expression interdependence among genes in regulating the magnitude and evolution of expression plasticity. This study illuminates how the evolution of phenotypic plasticity in gene expression facilitates the adaptation of species to challenging environments in nature.
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Aclimatación , Adaptación Fisiológica , Fenotipo , Adaptación Fisiológica/genética , Altitud , Expresión Génica , Evolución BiológicaRESUMEN
Organisms often acquire physiological and morphological modifications to conquer ecological challenges when colonizing new environments which lead to their adaptive evolution. However, deciphering the genomic mechanism of ecological adaptation is difficult because ecological environments are often too complex for straightforward interpretation. Thus, we examined the adaptation of a widespread songbird-the rufous-capped babbler (Cyanoderma ruficeps)-to a relatively simple system: distinct environments across elevational gradients on the mountainous island of Taiwan. We focused on the genomic sequences of 43 birds from five populations to show that the Taiwan group split from its sister group in mainland China around 1-2 million years ago (Ma) and colonized the montane habitats of Taiwan at least twice around 0.03-0.22 Ma. The montane and lowland Taiwan populations diverged with gene flow between them, suggesting strong selection associated with different elevations. We found that the montane babblers had smaller beaks than the lowland ones, consistent with Allen's rule, and identified candidate genes-COL9A1 and SOX11-underlying the beak size changes. We also found that altitudinally divergent mutations were mostly located in noncoding regions and tended to accumulate in chromosomal inversions and autosomes. The altitudinally divergent mutations might regulate genes related to haematopoietic, metabolic, immune, auditory and vision functions, as well as cerebrum morphology and plumage development. The results reveal the genomic bases of morphological and physiological adaptation in this species to the low temperature, hypoxia and high UV light environment at high elevation. These findings improve our understanding of how ecological adaptation drives population divergence from the perspective of genomic architecture.
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Passeriformes , Pájaros Cantores , Animales , Pájaros Cantores/genética , Adaptación Fisiológica/genética , Genoma/genética , Genómica , Passeriformes/genéticaRESUMEN
Background: Using Minnesota Multiphasic Personality Inventory-2 (MMPI-2) clinical scales to evaluate clinical symptoms in schizophrenia is a well-studied topic. Nonetheless, research focuses less on how these clinical scales interact with each other. Aims: Investigates the network structure and interaction of the MMPI-2 clinical scales between healthy individuals and patients with schizophrenia through the Bayesian network. Method: Data was collected from Wuhan Psychiatric Hospital from March 2008 to May 2018. A total of 714 patients with schizophrenia and 714 healthy subjects were identified through propensity score matching according to the criteria of the International Classification of Diseases (ICD-11). Separated MMPI-2 clinical scales Bayesian networks were built for healthy subjects and patients with schizophrenia, respectively. Results: The Bayesian network showed that the lower 7 scale was a consequence of the correlation between the lower 2 scale and the greater 8 scale. A solely lower 7 scale does yield neither a lower 2 scale nor a higher 8 scale. The proposed method showed 72% of accuracy with 78% area under the ROC curve (AUC), similar to the previous studies. Limitations: The proposed method simplified the continuous Bayesian network to predict binary outcomes, including other categorical data is not explored. Besides, the participants might only represent an endemic as they come from a single hospital. Conclusion: This study identified MMPI-2 clinical scales correlation and built separated Bayesian networks to investigate the difference between patients with schizophrenia and healthy people. These differences may contribute to a better understanding of the clinical symptoms of schizophrenia and provide medical professionals with new perspectives for diagnosis.
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BACKGROUND: Clinical mobility and balance assessments identify older adults who have a high risk of falls in clinics. In the past two decades, sensors have been a popular supplement to mobility and balance assessment to provide quantitative information and a cost-effective solution in the community environment. Nonetheless, the current sensor-based balance assessment relies on manual observation or motion-specific features to identify motions of research interest. OBJECTIVE: The objective of this study was to develop an automatic motion data analytics framework using signal data collected from an inertial sensor for balance activity analysis in community-dwelling older adults. METHODS: In total, 59 community-dwelling older adults (19 males and 40 females; mean age = 81.86 years, SD 6.95 years) were recruited in this study. Data were collected using a body-worn inertial measurement unit (including an accelerometer and a gyroscope) at the L4 vertebra of each individual. After data preprocessing and motion detection via a convolutional long short-term memory (LSTM) neural network, a one-class support vector machine (SVM), linear discriminant analysis (LDA), and k-nearest neighborhood (k-NN) were adopted to classify high-risk individuals. RESULTS: The framework developed in this study yielded mean accuracies of 87%, 86%, and 89% in detecting sit-to-stand, turning 360°, and stand-to-sit motions, respectively. The balance assessment classification showed accuracies of 90%, 92%, and 86% in classifying abnormal sit-to-stand, turning 360°, and stand-to-sit motions, respectively, using Tinetti Performance Oriented Mobility Assessment-Balance (POMA-B) criteria by the one-class SVM and k-NN. CONCLUSIONS: The sensor-based approach presented in this study provided a time-effective manner with less human efforts to identify and preprocess the inertial signal and thus enabled an efficient balance assessment tool for medical professionals. In the long run, the approach may offer a ï¬exible solution to relieve the community's burden of continuous health monitoring.
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Vida Independiente , Equilibrio Postural , Anciano , Anciano de 80 o más Años , Algoritmos , Femenino , Humanos , Masculino , Medición de RiesgoRESUMEN
Invited for the cover of this issue are Chin-Wei Lu, Zu-Po Yang, Hai-Ching Su, and co-workers at National Yang Ming Chiao Tung University and Providence University. The image depicts electron transport for light-emitting electrochemical cells. Read the full text of the article at 10.1002/chem.202103739.
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Recently, perovskites have attracted intense attention due to their high potential in optoelectronic applications. Employing perovskites as the emissive materials of light-emitting electrochemical cells (LECs) shows the advantages of simple fabrication process, low-voltage operation, and compatibility with inert electrodes, along with saturated electroluminescence (EL) emission. Unlike in previously reported perovskite LECs, in which salts are incorporated in the emissive layer, the ion-transport layer was separated from the emissive layer in this work. The layer of ionic transition metal complex (iTMC) not only provides mobile ions but also serves as an electron-injection/transport layer. Orthogonal solvents are used in spin coating to prevent the intermixing of stacked perovskite and iTMC layers. The blue iTMC with high ionization potential is effective in blocking holes from the emissive layer and thus ensures EL color saturation. In addition, the carrier balance of the perovskite/iTMC LECs can be optimized by adjusting the iTMC layer thickness. The optimized external quantum efficiency of the CsPbBr3 /iTMC LEC reaches 6.8 %, which is among the highest reported values for perovskite LECs. This work successfully demonstrates that, compared with mixing all components in a single emissive layer, separating the layer of ion transport, electron injection and transport from the perovskite emissive layer is more effective in adjusting device carrier balance. As such, solution-processable perovskite/iTMC LECs open up a new way to realize efficient perovskite LECs.
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Machine learning (ML) algorithms have been applied to predicting coronary artery disease (CAD). Our purpose was to utilize autoantibody isotypes against four different unmodified and malondialdehyde (MDA)-modified peptides among Taiwanese with CAD and healthy controls (HCs) for CAD prediction. In this study, levels of MDA, MDA-modified protein (MDA-protein) adducts, and autoantibody isotypes against unmodified peptides and MDA-modified peptides were measured with enzyme-linked immunosorbent assay (ELISA). To improve the performance of ML, we used decision tree (DT), random forest (RF), and support vector machine (SVM) coupled with five-fold cross validation and parameters optimization. Levels of plasma MDA and MDA-protein adducts were higher in CAD patients than in HCs. IgM anti-IGKC76-99 MDA and IgM anti-A1AT284-298 MDA decreased the most in patients with CAD compared to HCs. In the experimental results of CAD prediction, the decision tree classifier achieved an area under the curve (AUC) of 0.81; the random forest classifier achieved an AUC of 0.94; the support vector machine achieved an AUC of 0.65 for differentiating between CAD patients with stenosis rates of 70% and HCs. In this study, we demonstrated that autoantibody isotypes imported into machine learning algorithms can lead to accurate models for clinical use.
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The niche variation hypothesis (NVH) predicts that populations with wider niches exhibit greater morphological variation through increased interindividual differences in both niche and morphology. In this study, we examined niche-trait relationships in three passerine species (Cyanoderma ruficeps, Sinosuthora webbiana, and Zosterops simplex). A total of 289 C. ruficeps from 7 sites, 259 S. webbiana from 8 sites, and 144 Z. simplex from 6 sites were sampled along an elevation gradient (0-2,700 m) in Taiwan from 2009 to 2017. We measured bill traits (length, width, and depth of bill) and body size traits (length of head, tarsus, and wing) of the birds, which were reduced to four principal components (bill PC1, bill PC2, body size PC1, and body size PC2). We collected feather tissues for stable carbon and nitrogen isotope analyses to quantify their isotope niche. We quantified interindividual differences in isotope space and trait space with four diversity metrics (divergence, dispersion, evenness, and uniqueness) and tested whether interindividual differences in isotope space and trait space are positively associated. We quantified population isotope niche width by Bayesian ellipse area and population morphological variation by variances of the PCs. The results showed that individual uniqueness in isotope niche and bill morphology (average closeness of individuals within the population isotope/trait space) were positively associated across three species. Furthermore, isotope niche width and bill PC1 (reflecting the size of bill) variation at population level were also positively associated across the three species, supporting the NVH. Of the three species, C. ruficeps and S. webbiana showed stronger support for the NVH than Z. simplex, possibly due to the latter having narrower elevational distribution and a more specialized, plant-based diet. The diversity metrics represented different aspects of interindividual differences in niche/trait space, and for the passerines, individual uniqueness appeared to play an important role in their niche-trait dynamics.
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The UV-C light emitting diode (LED) has shown numerous advantages over the traditional UV mercury lamp for water sterilization applications. Multi-chip LED array was used to provide sufficient UV fluence for bacteria inactivation in limited time. According to the point light source characteristic of LEDs, the arrangement of LEDs in the batch reactor is crucial to optimize the inactivation efficiency. In this study, the inactivation of Escherichia coli (E. coli) was investigated using the 280 nm UV-C LED array. Input electrical power, chip interspace (L) and distance (D) between the reactor and water surface were analysed in terms of their effects on the inactivation of the microorganisms. An optimal inactivation efficiency of E. coli was obtained under the condition of L = D=25â mm to reach 4.0 log without using a magnetic stirrer. Additionally, the increasing rate of log inactivation of E. coli decreased with input power due to the significant decrease of wall plug efficiency of the UV-C LEDs.
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Desinfección , Purificación del Agua , Escherichia coli , Rayos Ultravioleta , Agua , Microbiología del AguaRESUMEN
BACKGROUND: Obligate brood parasites exert strong selective pressure on target hosts. In response, hosts typically evolve anti-parasitism strategies, of which egg recognition is one of the most efficient. Generally, host egg-recognition capacity is determined using model eggs. Previous studies have shown that some host species, which are capable of detecting parasite eggs, do not reject model eggs. However, it is unknown that whether the reaction to model eggs varies among distinct populations of the same host in relation to the degree of parasitism pressure. RESULTS: Here, we compared the rejection frequencies of model eggs and real eggs between mainland and island populations of the plain prinia (Prinia inornata), which are respectively sympatric and allopatric with their brood parasite, the common cuckoo (Cuculus canorus). Our results indicated that the mainland and island populations rejected real eggs at similar rates, but rejected model eggs, which were similar in size to real eggs but heavier, at significantly different rates: the island population rejected fewer model eggs, possibly because the rejection motivation of this population was lower due to absence of parasitism. CONCLUSIONS: Our results indicated that some factors affecting the decision to reject, such as rejection motivation, varied according to the degree of parasitism pressure, and thus influenced the frequency of egg rejection. Furthermore, our results suggested that model eggs should be used with caution in comparative studies of egg recognition abilities among species or populations subjected to different intensities of brood parasitism. That is, model eggs may fail to accurately detect egg recognition in host populations with little to no risk of parasitism.
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It has been documented that reactive oxygen species (ROS) contribute to oxidative stress, leading to diseases such as ischemic heart disease. Recently, increasing evidence has indicated that short-term intermittent hypoxia (IH), similar to ischemia preconditioning, could yield cardioprotection. However, the underlying mechanism for the IH-induced cardioprotective effect remains unclear. The aim of this study was to determine whether IH exposure can enhance antioxidant capacity, which contributes to cardioprotection against oxidative stress and ischemia/reperfusion (I/R) injury in cardiomyocytes. Primary rat neonatal cardiomyocytes were cultured in IH condition with an oscillating O2 concentration between 20% and 5% every 30 min. An MTT assay was conducted to examine the cell viability. Annexin V-FITC and SYTOX green fluorescent intensity and caspase 3 activity were detected to analyze the cell death. Fluorescent images for DCFDA, Fura-2, Rhod-2, and TMRM were acquired to analyze the ROS, cytosol Ca2+, mitochondrial Ca2+, and mitochondrial membrane potential, respectively. RT-PCR, immunocytofluorescence staining, and antioxidant activity assay were conducted to detect the expression of antioxidant enzymes. Our results show that IH induced slight increases of O2-· and protected cardiomyocytes against H2O2- and I/R-induced cell death. Moreover, H2O2-induced Ca2+ imbalance and mitochondrial membrane depolarization were attenuated by IH, which also reduced the I/R-induced Ca2+ overload. Furthermore, treatment with IH increased the expression of Cu/Zn SOD and Mn SOD, the total antioxidant capacity, and the activity of catalase. Blockade of the IH-increased ROS production abolished the protective effects of IH on the Ca2+ homeostasis and antioxidant defense capacity. Taken together, our findings suggest that IH protected the cardiomyocytes against H2O2- and I/R-induced oxidative stress and cell death through maintaining Ca2+ homeostasis as well as the mitochondrial membrane potential, and upregulation of antioxidant enzymes.