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Objective: This study investigated the ability of Large Language Models (LLMs) to provide accurate and consistent answers by focusing on their performance in complex gynecologic cancer cases. Background: LLMs are advancing rapidly and require a thorough evaluation to ensure that they can be safely and effectively used in clinical decision-making. Such evaluations are essential for confirming LLM reliability and accuracy in supporting medical professionals in casework. Study design: We assessed three prominent LLMs—ChatGPT-4 (CG-4), Gemini Advanced (GemAdv), and Copilot—evaluating their accuracy, consistency, and overall performance. Fifteen clinical vignettes of varying difficulty and five open-ended questions based on real patient cases were used. The responses were coded, randomized, and evaluated blindly by six expert gynecologic oncologists using a 5-point Likert scale for relevance, clarity, depth, focus, and coherence. Results: GemAdv demonstrated superior accuracy (81.87 %) compared to both CG-4 (61.60 %) and Copilot (70.67 %) across all difficulty levels. GemAdv consistently provided correct answers more frequently (>60 % every day during the testing period). Although CG-4 showed a slight advantage in adhering to the National Comprehensive Cancer Network (NCCN) treatment guidelines, GemAdv excelled in the depth and focus of the answers provided, which are crucial aspects of clinical decision-making. Conclusion: LLMs, especially GemAdv, show potential in supporting clinical practice by providing accurate, consistent, and relevant information for gynecologic cancer. However, further refinement is needed for more complex scenarios. This study highlights the promise of LLMs in gynecologic oncology, emphasizing the need for ongoing development and rigorous evaluation to maximize their clinical utility and reliability.

Abstract 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

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 (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.

Abstract 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.

Abstract 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.

Abstract 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.

BackgroundClinical 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. ObjectiveThe 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. MethodsIn 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. ResultsThe 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. ConclusionsThe 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 flexible solution to relieve the community’s burden of continuous health monitoring.

Abstract Background A variety of human diseases transmitted by arthropod vectors, including ticks, are emerging around the globe. Birds are known to be hosts of ticks and can disperse exotic ticks and tick-borne pathogens. In Taiwan, previous studies have focused predominantly on mammals, leaving the role of birds in the maintenance of ticks and dissemination of tick-borne pathogens undetermined. Methods Ticks were collected opportunistically when birds were studied from 1995 to 2013. Furthermore, to improve knowledge on the prevalence and mean load of tick infestation on birds in Taiwan, ticks were thoroughly searched for when birds were mist-netted at seven sites between September 2014 and April 2016 in eastern Taiwan. Ticks were identified based on both morphological and molecular information and were screened for potential tick-borne pathogens, including the genera Anaplasma, Babesia, Borrelia, Ehrlichia and Rickettsia. Finally, a list of hard tick species collected from birds in Taiwan was compiled based on past work and the current study. Results Nineteen ticks (all larvae) were recovered from four of the 3096 unique mist-netted bird individuals, yielding a mean load of 0.006 ticks/individual and an overall prevalence of 0.13%. A total of 139 ticks from birds, comprising 48 larvae, 35 nymphs, 55 adults and one individual of unknown life stage, were collected from 1995 to 2016, and 11 species of four genera were identified, including three newly recorded species (Haemaphysalis wellingtoni, Ixodes columnae and Ixodes turdus). A total of eight tick-borne pathogens were detected, with five species (Borrelia turdi, Anaplasma sp. clone BJ01, Ehrlichia sp. BL157-9, Rickettsia helvetica and Rickettsia monacensis) not previously isolated in Taiwan. Overall, 16 tick species of five genera have been recorded feeding on birds, including nine species first discovered in this study. Conclusion Our study demonstrates the paucity of information on ticks of birds and emphasizes the need for more research on ticks of birds in Taiwan and Southeast Asia. Moreover, some newly recorded ticks and tick-borne pathogens were found only on migratory birds, demonstrating the necessity of further surveillance on these highly mobile species.

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.

Abstract Counselling sessions have multiple stages, each with its themes and objectives. This study aimed to apply Hidden Markov Models (HMMs) to analyse counselling sessions from Open Up, an online text-based counselling platform in Hong Kong. The focus was on inferring latent stages over word distributions and identifying distinctive patterns of progression in more versus less satisfying sessions. Transcripts from 2589 sessions were categorized into more satisfying sessions ( $$n=\mathrm{1993}$$ n = 1993 ) and less satisfying sessions ( $$n=596$$ n = 596 ) based on post-session surveys. A message-level HMM identified five distinct stages: Rapport-building, Problem-identification, Problem-exploration, Problem-solving, and Wrap-up. Compared with less satisfying sessions, more satisfying sessions saw significantly more efficient initial rapport building (7.5% of session duration), problem introduction (20.2%), problem exploration (28.5%), elaborated solution development (46.6%), and concise conclusion (8.2%). This study offers insights for improving the efficiency and satisfaction of text-based counselling services through efficient initial engagement, thorough issue exploration, and focused problem-solving.

Avian hosts of brood parasites can evolve anti‐parasitic defenses to recognize and reject foreign eggs from their nests. Theory predicts that higher inter‐clutch and lower intra‐clutch variation in egg appearance facilitates hosts to detect parasitic eggs as egg‐rejection mainly depends on the appearance of the egg. Therefore, we predict that egg patterns and rejection rates will differ when hosts face different intensity of cuckoo parasitism. We tested this prediction in two populations of the plain prinia Prinia inornata: Guangxi in mainland China with high diversity and density of cuckoo species, and Taiwan where there is only one breeding cuckoo species, the oriental cuckoo Cuculus optatus. As expected, egg patterns were similar within clutches but different among clutches (polymorphic eggs) in the mainland population, while the island population produced more uniform egg morphs. Furthermore, the mainland population showed a high rate of egg rejection, while the island population exhibited dramatically reduced egg grasp‐rejection ability in the absence of parasitism by the common cuckoo Cuculus canorus. Our study suggests that prinias show lower intra‐clutch consistency in egg colour and lose egg‐rejecting ability under relaxed selection pressure from brood parasitism.

This paper aims to demonstrate a simplified nonlinear wake model that fills the technical gap between the low-cost and less-accurate linear formulation and the high-cost and high-accuracy large eddy simulation, to offer a suitable balance between the prediction accuracy and the computational cost, and also to establish a robust approach for long-term wind farm power prediction. A simplified actuator disk model based on the momentum theory is proposed to predict the wake interaction among wind turbines along with their power output. The three-dimensional flow field of a wind farm is described by the steady continuity and momentum equation coupled with a k-ε turbulence model, where the body force representing the aerodynamic impact of the rotor blade on the airflow is uniformly distributed in the Cartesian cells within the actuator disk. The characteristic wind conditions identified from the data of the supervisory control and data acquisition (SCADA) system were employed to build the power matrix of these typical wind conditions for reducing the computation demands to estimate the yearly power production. The proposed model was favorably validated with the offshore measurement of Horns Rev wind farm, and three Taiwanese onshore wind farms were forecasted for their yearly capacity factors with an average error less than 5%, where the required computational cost is estimated about two orders of magnitude smaller than that of the large eddy simulation. However, the proposed model fails to pronouncedly reproduce the individual power difference among wind turbines in the investigated wind farm due to its time-averaging nature.

Background/Aims: Intermittent hypoxia (IH) may exert pre-conditioning-like cardioprotective effects and alter Ca2+ regulation; however, the exact mechanism of these effects remains unclear. Thus, we examined Ca2+-handling mechanisms induced by IH in rat neonatal cardiomyocytes. Methods: Cardiomyocytes were exposed to repetitive hypoxia-re-oxygenation cycles for 1-4 days. Mitochondrial reactive oxygen species (ROS) generation was determined by flow cytometry, and intracellular Ca2+ concentrations were measured using a live-cell fluorescence imaging system. Protein kinase C (PKC) isoforms and Ca2+-handling proteins were analysed using immunofluorescence and western blotting. Results: After IH exposure for 4 days, the rate of Ca2+ extrusion from the cytosol to the extracellular milieu during 40-mM KCl-induced Ca2+ mobilization increased significantly, whereas ROS levels increased mildly. IH activated PKC isoforms, which translocated to the membrane from the cytosol, and Na+/Ca2+ exchanger-1, leading to enhanced Ca2+ efflux capacity. Simultaneously, IH increased sarcoplasmic reticulum (SR) Ca2+-ATPase and ryanodine receptor 2 (RyR-2) activities and RyR-2 expression, resulting in improved Ca2+ uptake and release capacity of SR in cardiomyocytes. Conclusions: IH-induced mild elevations in ROS generation can enhance Ca2+ efflux from the cytosol to the extracellular milieu and Ca2+-mediated SR regulation in cardiomyocytes, resulting in enhanced Ca2+-handling ability.

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.