Search

This study surveyed 183 college and senior high school students' graph-interpretation competence in scientific and daily contexts. Specifically, whether students' graph interpretation in scientific and daily contexts differed across educational levels was investigated. Furthermore, the questions of whether students' graph interpretation competence in scientific contexts might predict their graph interpretation in daily contexts were explored. Other factors including age and gender were also considered and examined to discern significant factor(s) predicting graph interpretation competence in daily contexts. Results indicated that there were statistically significant differences across educational levels in terms of graph interpretation competence in both scientific and daily contexts. Furthermore, the students' graph interpretation competence was related between scientific and daily contexts. The important factors predicting students' graph interpretation in daily contexts include age and graph-interpretation in scientific literacy. Implications are discussed.

This article - Recommendations and Guidelines of Integrative Medicine (IM) for COVID-19 Care - was one of the outcomes from an Asia-Pacific Economic Cooperation (APEC) Project (Integrative Medicine (IM) and COVID -19 Care) during the time between May 2022 and March 2023. With the efforts from care providers, researchers, health policy makers and healthcare administrative leaders among APEC economies, the purpose of this file was to provide comprehensive IM systems for COVID-19 care as recommendations and suggestive guidelines including care methods, tools, procedures, symptom conditions and targets selections, and points need to be considered during care applications. All cited COVID-19 care practices have confirmed their efficacy and usefulness either used alone or combined with conventional medicine. This article provides current useful medical information on IM for COVID-19 care which could benefit APEC economies and world health communities on their healthcare system.

This study analyzed the trends in ChatGPT-based learning research through a systematic review with bibliometric analysis. Based on the PRISMA guidelines, relevant articles were identified by searching several reputable sources (i.e., Embase, Scopus, PubMed, CINAHL, and WoS), and a total of 50 empirical articles that met the selection criteria were included. The results are twofold: (1) Bibliometric attributes of the research were identified. First, we found that authors from China, the United States, Australia, and Saudi Arabia are the most productive contributors to the field. Second, over 64% of the analyzed research was published in educational technology journals (e.g., EIT, AJET, ILE). (2) The systematic review identified key learning features of the research. Most research focused on non-specific learning, and subjects related to English learning in ChatGPT use were the second most frequently researched topic. The third most frequently researched subject is related to STEAM courses, in which most research employed ChatGPT-based assistant learning as an instructional design in the course. The role of ChatGPT-based learning in education involves domain experts, teachers/tutors, administrators, and learning tools. Regarding the educational context of the research, the participants were mainly in higher education settings, including undergraduate and graduate students. Based on the results, we concluded that research on ChatGPT-based learning in education is still in its early stages, with limited empirical studies addressing effective instructional design and learning strategies.

Abstract Potteries, one of the tools widely used by early humans, encapsulates rich historical information. Deep neural networks have been applied to analyzing pottery digital images, bypassing the need for intricate handcrafted features. However, existing models focus solely on pottery shape comparison, neglecting the analysis of their evolution across different historical periods. In this work, we propose a method based on deep learning to assist experts in identifying the evolutionary patterns of a given pottery type within their specified chronological divisions. First we train a convolutional neural network for pottery classification, extracting low and high level features that represent different ages of pottery samples. Next, we employ clustering algorithms to identify representative potteries for each historical period based on high level features. To facilitate intuitive comparisons across different ages, we use shallow features and compute cosine similarities between potteries, visualizing shape and decoration differences. This approach enhances understanding of pottery evolution patterns directly through visual analysis. The effectiveness and efficiency of our proposed method are evaluated by validating it on three distinct era division cases using data from the Dabagou and Miaozigou archaeological sites, which represent the Miaozigou culture and exhibit clear evolutionary patterns. Our method identifies representative artifacts for each era and uncovers their evolutionary patterns effectively and efficiently, achieving conclusions comparable to those of experts while significantly reducing time compared to traditional manual methods.

In professional healthcare training programs, field experience after physical courses is essential for students to become professionals. However, the outbreak of the pandemic has restricted such field experience, and so students' problem-solving awareness when facing clinical emergencies in a professional field after graduation has become a critical issue. In conventional teaching, video-based instruction with case-based learning sheets is usually adopted for healthcare training. In this teaching mode, students generally lack opportunities to experience the process of dealing with authentic cases, and hence might be unable to immediately judge and solve problems when entering the workplace. To enhance students' critical thinking and problem-solving awareness, the present study proposed a reflective cycle-based virtual reality (RC-VR) approach to provide a realistic environment and enable repeated practice. To examine its effectiveness, this study adopted a quasi-experimental design and applied it in a healthcare training program for risk assessment of maternal labor. The results indicated that the proposed RC-VR approach effectively enhanced students' learning achievement, sense of presence, critical thinking, and problem-solving awareness in comparison to the conventional teaching approach.

Background and Purpose: Metavisualization plays a key role in science and technological learning in which visualization is practiced. We conducted two sequential studies with the purposes to first develop an instrument that allows individuals to report or reflect on their metavisualization, and then validate the instrument and investigate the relationships among the dimensions of metavisualization. Sample: A total of 320 university students participated in this research. Methods: Through exploratory factor analysis (EFA) in the first study and partial least squares -- structural equation modeling (PLS-SEM) in the second study, the validity and reliability of the instrument measuring the four dimensions of metavisualization were reported, and a theoretical model delineating the relationships among the four variables was explored. Findings: It was found that metacognitive skills, rather than metacognitive knowledge, significantly contributed to the demonstration of epistemic knowledge and judgment criteria during visualization. Metacognitive knowledge may also play an indirect role in learners' epistemic performance through its relation with metacognitive skills. Implications: The results provide insights to advance understanding of metavisualization and its relation to metacognition and epistemic practice. The validated instruments may be used for future quantitative or mixed research to advance understanding of the role metavisualization plays in various contexts of learning in science and technological education.

Educators have recognized the importance of providing a realistic learning environment which helps learners to not only comprehend learning content, but also to link the content to practical problems. Such an environment can hence foster problem-solving skills in nursing training. However, when learners interact in a virtual environment with rich learning resources, they might encounter difficulties if there is a lack of proper guidance, clinical sense, or a well thought-out instructional design process. Hence, this work developed a maternity VR-based situated learning system (MVR-SLS) based on the experiential learning theory to support professional courses in obstetrics. A quasi-experiment was conducted to verify the impacts of this method on learners' learning achievement, OSCE (Objective Structured Clinical Examination) competency, problem solving skills, learning engagement, and teaching effectiveness. The experimental results indicate that the new method improved learners' learning achievement, OSCE competency, problem-solving ability, and recognition of learning engagement. Moreover, the learners who learned with the new method showed more active learning behaviors compared to the learners in the control group. Findings of the present study offer concrete suggestions for implementing effective virtual reality (VR)-based learning strategies for medical and nursing textbooks.

One issue facing teachers who implement model-based instruction within the school system is the tight curricular schedule. The 'lesson objective tension' calls for investigations to address instructional issues such as how to organise modelling-based instruction at the curriculum level which is across multiple units. We investigated the effect of the cyclic curricular design spacing out three modelling-based instruction units with virtual labs over three semesters, each involving 73, 181, and 150 junior high school students, respectively. Results indicate that, overall, the approach of modelling with virtual labs better promoted students' scientific literacy than the traditional instruction did. Specifically, students with low and moderate school science achievements benefitted more as shown in their scientific literacy scores than did the high achievement students. Furthermore, this study found that receiving one unit of modelling-based instruction may not be sufficient to promote students' scientific literacy, whereas the cyclic approach that suggests students receive two or more units of modelling-based instruction with virtual labs spaced over consecutive semesters had significant effects on promoting students' scientific literacy. The results provide insights into when and how modelling-based learning with virtual labs can promote scientific literacy at a curricular level.

Traditional nursing and health education design courses usually only transfer knowledge via lectures, and lack interaction, drills and personalized feedback. However, the development and widespread adoption of generative artificial intelligence via the ChatGPT system presents an opportunity to address these issues. Some CIDI model-based ChatGPT systems have been developed, but how to effectively apply these technologies in nursing education design courses remains a challenging problem for researchers. In order to explore the application mode and effect of generative artificial intelligence via ChatGPT technology in nursing education, this study integrated generative artificial intelligence via the ChatGPT system into the teaching activities of nursing and health education design courses, and used computers as learning tools to guide learners to learn nursing and health knowledge. At the same time, two classes of nursing undergraduates were recruited to conduct a quasi-experiment. One of the classes was the experimental group, which used the generative artificial intelligence via the ChatGPT system for learning; the other class was the control group, which used traditional teaching methods for learning. By analyzing learners' learning efficiency and learning satisfaction, we obtained results about the application effect of generative artificial intelligence via ChatGPT technology in a nursing education design course. According to the experimental results, the generative artificial intelligence via ChatGPT system effectively improved learners' critical thinking ability, problem solving, and learning enjoyment. These results indicate that the generative artificial intelligence via ChatGPT system has great potential in nursing education design courses, and can improve the deficiencies of traditional teaching methods.

Background: Data visualizations transform data into visual representations such as graphs, diagrams, charts and so forth, and enable inquiries and decision-making in many professional fields, as well as in public and economic areas. How students' data visualization literacy (DVL), including constructing, comprehending, and utilizing adequate data visualizations, can be developed is gaining increasing attention in STEM education. As fundamental steps, the purpose of this study was to understand common student difficulties and useful strategies during the process of constructing data visualization so that suggestions and principles can be made for the design of curricula and interventions to develop students' DVL. Methods: This study engaged 57 college and high school students in constructing data visualizations relating to the topic of air quality for a decision-making task. The students' difficulties and strategies demonstrated during the process of data visualization were analyzed using multiple collected data sources including the students' think-aloud transcripts, retrospective interview transcripts, and process videos that captured their actions with the data visualization tool. Qualitative coding was conducted to identify the students' difficulties and strategies. Epistemic network analysis (ENA) was employed to generate network models revealing how the difficulties and strategies co-occurred, and how the college and high school students differed. Results: Six types of student difficulties and seven types of strategies were identified. The strategies were further categorized into non-, basic- and high-level metavisual strategies. About three-quarters of the participants employed basic or high-level metavisual strategies to overcome the technological and content difficulties. The high school students demonstrated a greater need to develop content knowledge and representation skills, whereas the college students needed more support to know how to simplify data to construct the best data visualizations. Conclusions and implications: The study specified metacognition needed for data visualization, which builds on and extends the cognitive model of drawing construction (CMDC) and theoretical perspectives of metavisualization. The results have implications for developing students' data visualization literacy in STEM education by considering the difficulties and trajectories of metacognitive strategy development, and by addressing the different patterns and needs demonstrated by the college and high school students.

Nuclear receptor coactivator 2 (Ncoa2) is a member of the Ncoa family of coactivators, and we previously showed that Ncoa2 regulates the differentiation of induced regulatory T cells. However, it remains unknown if Ncoa2 plays a role in CD8+ T-cell function. Here, we show that Ncoa2 promotes CD8+ T cell-mediated immune responses against tumors by stimulating T-cell activation via upregulating PGC-1α expression to enhance mitochondrial function. Mice deficient in Ncoa2 in T cells (Ncoa2fl/fl/CD4Cre) displayed defective immune responses against implanted MC38 tumors, which associated with significantly reduced tumor-infiltrating CD8+ T cells and decreased IFNγ production. Consistently, CD8+ T cells from Ncoa2fl/fl/CD4Cre mice failed to reject tumors after adoptive transfer into Rag1-/- mice. Further, in response to TCR stimulation, Ncoa2fl/fl/CD4Cre CD8+ T cells failed to increase mitochondrial mass, showed impaired oxidative phosphorylation, and had lower expression of PGC-1α, a master regulator of mitochondrial biogenesis and function. Mechanically, T-cell activation-induced phosphorylation of CREB triggered the recruitment of Ncoa2 to bind to enhancers, thus, stimulating PGC-1α expression. Forced expression of PGC-1α in Ncoa2fl/fl/CD4Cre CD8+ T cells restored mitochondrial function, T-cell activation, IFNγ production, and antitumor immunity. This work informs the development of Ncoa2-based therapies that modulate CD8+ T cell-mediated antitumor immune responses.

Dienogest has been proven effective as long-term therapeutic option for pelvic pain caused by endometriosis. However, in Taiwan, there is a lack of a well-tailored consensus on its long-term administration. To address this gap, Taiwanese experts in collaboration with the Taiwan Endometriosis Society (TES), convened to provide structured recommendations on dienogest treatment and monitoring strategies. Drawing from clinical evidence and collective expertise, the experts formulated individualized treatment strategies based on treatment objectives and the patient's demographics. The experts recommend long-term dienogest administration for endometriosis patients for appropriate symptom control while reducing the risk of disease recurrence. Specifically, they recommend regular ultrasound examinations and relevant blood tests to monitor disease progression and therapeutic response with additional breast screening for patients at high risk for breast cancer. These recommendations aim to provide physicians with comprehensive guidance on the long-term administration of dienogest for endometriosis, ensuring patient safety and optimizing treatment outcomes.

Abstract Most cancer cells reprogram their glucose metabolic pathway from oxidative phosphorylation to aerobic glycolysis for energy production. By reducing enzyme activity of pyruvate kinase M2 (PKM2), cancer cells attain a greater fraction of glycolytic metabolites for macromolecule synthesis needed for rapid proliferation. Here we demonstrate that hydrogen sulfide (H2S) destabilizes the PKM2 tetramer into monomer/dimer through sulfhydration at cysteines, notably at C326, leading to reduced PKM2 enzyme activity and increased PKM2-mediated transcriptional activation. Blocking PKM2 sulfhydration at C326 through amino acid mutation stabilizes the PKM2 tetramer and crystal structure further revealing the tetramer organization of PKM2-C326S. The PKM2-C326S mutant in cancer cells rewires glucose metabolism to mitochondrial respiration, significantly inhibiting tumor growth. In this work, we demonstrate that PKM2 sulfhydration by H2S inactivates PKM2 activity to promote tumorigenesis and inhibiting this process could be a potential therapeutic approach for targeting cancer metabolism.

Abstract Background Given the increasing complexity of illnesses and rapid pace of technological advancements in professional training, it is vital to offer nurses ample opportunities to hone their clinical expertise and skills, particularly in ensuring the delivery of premier medical care. This study aimed to determine the factors and predictors influencing nurses’ satisfaction with adopting mobile learning approaches in intensive care unit healthcare settings. Additionally, it sought to investigate the applicability of the technology acceptance model in explaining their inclinations and validating the measurement scales employed in the research. Methods The study employed a cross-sectional survey research design, utilizing a technology acceptance questionnaire and a learning satisfaction questionnaire. The survey was conducted in six intensive care unit departments. A total of 212 participants completed the survey as the primary instrument. Rigorous assessments were conducted to establish the content validity and ensure instrument reliability. Results The findings demonstrated that perceived usefulness was the most influential factor affecting nurses’ intentions to embrace mobile learning approaches, with perceived ease of use emerging as the principal determinant of perceived usefulness. Conclusions Incorporating mobile learning methodologies is paramount to increasing the calibration of professional nursing education programs. By effectively integrating digital information technology and tools, nursing educators can overcome teaching challenges, deliver innovative clinical nursing education content through mobile learning approaches, and foster optimal development in the field.

Lactic acid bacteria (LAB) are widely used in the development of plant-based fermented foods, which play an important role in forming and improving the unique flavor, and promoting the diversification of nutritional and health benefits of fermented products. This article introduces the health benefits of LAB and reviews the recent applications of LAB in fermented tea with special reference to the basis, the fermentation process and its impact on tea quality. Meanwhile, future prospects for the application of LAB in the production of fermented tea are discussed, hoping to provide a reference for the development of LAB fermented tea products and high-value utilization of summer and autumn tea.

Objective: Identification of heavy menstrual bleeding (HMB) cases in primary care settings is often done by using pictorial blood assessment charts (PBAC). The study aims to highlight the challenge of assessing blood loss, to develop a standardized method to efficiently customize a patient-reported pictorial chart, to validate the tool produced with our proposed method, and to demonstrate the feasibility of using PBACs in settings where resources are scarce. Materials and methods: Using blood samples and feedback from 21 women aged 30–51 years, we followed guidelines suggested in the literature, developed a method to produce PBACs for regular, long and night sizes, and had 9 participants testuse them. Linear regression analysis was performed to determine the correlation between participants’ scores and menstrual blood weight. Results: The study demonstrated the feasibility of customizing product-sensitive and size-specific pictorial charts by adopting essential steps including collecting menstrual blood with menstrual cups, employing fluid application techniques, and using sanitary pads as icons for easy identification. Linear regression analyses of score versus blood weight showed that the recorded blood weight was around 95% of the scored values (R2 = 0.9428, 0.947, and 0.9508, respectively; p

Abstract Autophagy can be classified as degradative and secretory based on distinct functions. The small GTPase proteins Rab8a and Rab37 are responsible for secretory autophagy‐mediated exocytosis of IL‐1β, insulin, and TIMP1 (tissue inhibitor of 54 metalloproteinase 1). Other Rab family members participating in secretory autophagy are poorly understood. Herein, we identified 26 overlapped Rab proteins in purified autophagosomes of mouse pancreatic β‐cell “Min‐6” and human lung cancer cell “CL1‐5‐Q89L” with high secretory autophagy tendency by LC–MS/MS proteomics analysis. Six Rab proteins (Rab8a, Rab11b, Rab27a, Rab35, Rab37, and Rab7a) were detected in autophagosomes of four cell lines, associating them with autophagy‐related vesicle trafficking. We used CL1‐5‐Q89L cell line model to evaluate the levels of Rab proteins colocalization with autophagy LC3 proteins and presence in purified autophagosomes. We found five Rab proteins (Rab8a, Rab11b, Rab27a, Rab35, and Rab37) are highly expressed in the autophagosome compared to the normal control by immunoblotting under active secretion conditions. However, only Rab8a, Rab35, and Rab37 showing high colocalization with LC3 protein by cofocal microscopy. Despite the discrepancy between the image and immunoblotting analysis, our data sustains the speculation that Rab8a, Rab11b, Rab27a, Rab35, and Rab37 are possibly associated with the secretory autophagy machinery. In contrast, Rab7a shows low colocalization with LC3 puncta and low level in the autophagosome, suggesting it regulates different vesicle trafficking machineries. Our findings open a new direction toward exploring the role of Rab proteins in secretory autophagy‐related cargo exocytosis and identifying the cargoes and effectors regulated by specific Rab proteins.

Abstract Autophagy is a self‐recycling machinery to maintain cellular homeostasis by degrading harmful materials in the cell. Autophagy‐related gene 5 (Atg5) is required for autophagosome maturation. However, the role of Atg5 in tumorigenesis under autophagy deficient conditions remains unclear. This study focused on the autophagy‐independent role of Atg5 and the underlying mechanism in tumorigenesis. We demonstrated that knockout of autophagy‐related genes including Atg5, Atg7, Atg9, and p62 in mouse embryonic fibroblast (MEF) cells consistently decreased cell proliferation and motility, implying that autophagy is required to maintain diverse cellular functions. An Atg7 knockout MEF (Atg7−/− MEF) cell line representing deprivation of autophagy function was used to clarify the role of Atg5 transgene in tumorigenesis. We found that Atg5‐overexpressed Atg7−/‐MEF (clone A) showed increased cell proliferation, colony formation, and migration under autophagy deficient conditions. Accordingly, rescuing the autophagy deficiency of clone A by overexpression of Atg7 gene shifts the role of Atg5 from pro‐tumor to anti‐tumor status, indicating the dual role of Atg5 in tumorigenesis. Notably, the xenograft mouse model showed that clone A of Atg5‐overexpressed Atg7−/− MEF cells induced temporal tumor formation, but could not prolong further tumor growth. Finally, biomechanical analysis disclosed increased Wnt5a secretion and p‐JNK expression along with decreased β‐catenin expression. In summary, Atg5 functions as a tumor suppressor to protect the cell under normal conditions. In contrast, Atg5 shifts to a pro‐tumor status under autophagy deprivation conditions.

Purpose: Head injury criterion (HIC) companied by a rotation-based metric was widely believed to be helpful for head injury prediction in road traffic accidents. Recently, the Euro-New Car Assessment Program utilized a newly developed metric called diffuse axonal multi-axis general evaluation (DAMAGE) to explain test device for human occupant restraint (THOR) head injury, which demonstrated excellent ability in capturing concussions and diffuse axonal injuries. However, there is still a lack of comprehensive understanding regarding the effectiveness of using DAMAGE for Hybrid Ⅲ 50th percentile male dummy (H50th) head injury assessment. The objective of this study is to determine whether the DAMAGE could capture the risk of H50th brain injury during small overlap barrier tests. Methods: To achieve this objective, a total of 24 vehicle crash loading curves were collected as input data for the multi-body simulation. Two commercially available mathematical dynamic models, namely H50th and THOR, were utilized to investigate the differences in head injury response. Subsequently, a decision method known as simple additive weighting was employed to establish a comprehensive brain injury metric by incorporating the weighted HIC and either DAMAGE or brain injury criterion. Furthermore, 35 sets of vehicle crash test data were used to analyze these brain injury metrics. Results: The rotational displacement of the THOR head is significantly greater than that of the H50th head. The maximum linear and rotational head accelerations experienced by H50th and THOR models were (544.6 ± 341.7) m/s2, (2468.2 ± 1309.4) rad/s2 and (715.2 ± 332.8) m/s2, (3778.7 ± 1660.6) rad/s2, respectively. Under the same loading condition during small overlap barrier (SOB) tests, THOR exhibits a higher risk of head injury compared to the H50th model. It was observed that the overall head injury response during the small overlap left test condition is greater than that during the small overlap right test. Additionally, an equation was formulated to establish the necessary relationship between the DAMAGE values of THOR and H50th. Conclusion: If H50th rather than THOR is employed as an evaluation tool in SOB crash tests, newly designed vehicles are more likely to achieve superior performance scores. According to the current injury curve for DAMAGE and brain injury criterion, it is highly recommended that HIC along with DAMAGE was prioritized for brain injury assessment in SOB tests.

Background: Cytomegalovirus (CMV) can cause infection and critical diseases in hematopoietic stem cell transplantation (HSCT) recipients. This study aimed to explore the cumulative incidence and risk factors for CMV infection and disease among HSCT recipients in Taiwan. Methods: This retrospective cohort study using the Taiwan Blood and Marrow Transplantation Registry (TBMTR) included HSCT recipients between 2009 and 2018 in Taiwan. The primary outcome was cumulative incidence of CMV infection or disease at day 100 after HSCT. Secondary outcomes included day 180 cumulative incidence of CMV infection or disease, infection sites, risk factors for CMV infection or disease, survival analysis, and overall survival after CMV infection and disease. Results: There were 4394 HSCT recipients included in the study (2044 auto-HSCT and 2350 allo-HSCT). The cumulative incidence of CMV infection and disease was significantly higher in allo-HSCT than in auto-HSCT patients at day 100 (53.7% vs. 6.0%, P

Objective: Researchers looked into the safety and effectiveness of blepharoplasty in conjunction with botulinum toxin type A for the treatment of periocular skin laxity. Methods: 92 patients who received treatment at our institution for periocular skin laxity were chosen as research subjects. Their admission time ranged from May 2020 to December 2022. Using various therapy modalities, the patients were split into two groups: an observational team (n = 46) and a controlling team (n = 46). They were respectively given blepharoplasty treatment intervention and botulinum toxin type A combined with blepharoplasty treatment intervention. Eyelid bags, crow's feet, skin radiance and aesthetic results, quality of life were analyzed before and after the intervention, and physician and patient’ satisfaction with the results were compared. Results: 95.65 % was the effective rate of the observed group, which was 71.74 % compared with the control group, and significantly increased (P

Background: Candida is one of the common pathogens in nosocomial infections. Culture is the gold standard for diagnosing candidemia. Candida albicans is identified via the germ tube test, which uses serum as the culture medium, which is costly and time-consuming. This study was conducted to evaluate and compare a relatively simple, fast, and reliable method for the detection of Candida albicans . Methods: We conducted this randomized case study at Taipei City Hospital (TCH) from January 2023 to August 2023, with a total of 30 specimen culture reports collected and confirmed to be cases of Candida albicans infection. A germ tube test was performed in a 37°C water bath using serum, plasma, and safe plasma products (Fresh Frozen Plasma, FFP). Further, the same procedures were repeated with the addition of 22% bovine serum albumin (BSA) to the identification/culture. Results: By adding BSA, more than 50% of the budding phenomenon was observed in 40 minutes, which shortened the diagnosis time compared with the traditional method (2-3 hours). Using BSA can shorten the identification time for early clinical medication and improve the quality of medical care Conclusion: Using safer plasma products for germ tube test of candidiasis not only reduced the risk of infection for medical technicians but could also replace the serum used in traditional methods to increase convenience and save time. This study proposed BSA as a germ tube induction medium enhancer, which reduced the culture time, thereby enabling quicker diagnosis of C. albicans infections.

ObjectivesSignificant increase in tacrolimus exposure was observed during co-administration with voriconazole, and no population pharmacokinetic model exists for tacrolimus in renal transplant recipients receiving voriconazole. To achieve target tacrolimus concentrations, an optimal dosage regimen is required. This study aims to develop individualized dosing parameters through population pharmacokinetic analysis and simulate tacrolimus concentrations under different dosage regimens.MethodsWe conducted a retrospective study of renal transplant recipients who were hospitalized at the Second Xiangya Hospital of Central South University between January 2016 and March 2021. Subsequently, pharmacokinetic analysis and Monte Carlo simulation were employed for further analysis.ResultsNineteen eligible patients receiving tacrolimus and voriconazole co-therapy were included in the study. We collected 167 blood samples and developed a one-compartment model with first-order absorption and elimination to describe the pharmacokinetic properties of tacrolimus. The final typical values for tacrolimus elimination rate constant (Ka), apparent volume of distribution (V/F), and apparent oral clearance (CL/F) were 8.39 h−1, 2690 L, and 42.87 L/h, respectively. Key covariates in the final model included voriconazole concentration and serum creatinine. Patients with higher voriconazole concentration had lower tacrolimus CL/F and V/F. In addition, higher serum creatinine levels were associated with lower tacrolimus CL/F.ConclusionOur findings suggest that clinicians can predict tacrolimus concentration and estimate optimal tacrolimus dosage based on voriconazole concentration and serum creatinine. The effect of voriconazole concentration on tacrolimus concentration was more significant than serum creatinine. These findings may inform clinical decision-making in the management of tacrolimus and voriconazole therapy in solid organ transplant recipients.

Long-term exposure to ambient PM2.5 is known associated with cardiovascular and respiratory health effects. However, the heterogeneous concentrationresponse function (CRF) between PM2.5 exposure across different concentration range and cardiopulmonary disease and diabetes mellitus (DM) incidence, and their implications on attributable years lived with disability (YLD) and regulation policy has not been well-studied. In this retrospective longitudinal cohort study, disease-free participants (approximately 170,000 individuals, aged ≥ 30 years) from the MJ Health Database were followed up (2007–2017) regarding incidents of coronary heart disease (CHD), ischemic stroke, chronic obstructive pulmonary disease (COPD), lower respiratory tract infections (LRIs), and DM. We used a time-dependent nonlinear weight-transformation Cox regression model for the CRF with an address-matched 3-year mean PM2.5 exposure estimate. Town/district-specific PM2.5-attributable YLD were calculated by multiplying the disease incidence rate, population attributable fraction, disability weight, and sex-age group specific subpopulation for each disease separately. The estimated CRFs for cardiopulmonary diseases were heterogeneously with the hazard ratios (HRs) increased rapidly for CHD and ischemic stroke at PM2.5 concentration lower than 10 μg/m3, whereas the HRs for DM (LRIs) increased with PM2.5 higher than 15 (20) μg/m3. Women had higher HRs for ischemic stroke and DM but not CHD. Relative to the lowest observed PM2.5 concentration of 6 μg/m3 of the study population, the PM2.5 level with an extra risk of 0.1 % (comparable to the disease incidence) for CHD, ischemic stroke, DM, and LRIs were 8.59, 11.85, 22.09, and 24.23 μg/m3, respectively. The associated attributable YLD decreased by 51.4 % with LRIs reduced most (83.6 %), followed by DM (63.7 %) as a result of PM2.5 concentration reduction from 26.10 to 16.82 μg/m3 during 2011–2019 in Taiwan. The proportion of YLD due to CHD and ischemic stroke remained dominant (56.4 %-69.9 %). The cost-benefit analysis for the tradeoff between avoidable YLD and mitigation cost suggested an optimal PM2.5 exposure level at 12 μg/m3. CRFs for cardiopulmonary diseases, attributable YLD, and regulation level, may vary depending on the national/regional background and spatial distribution of PM2.5 concentrations, as well as demographic characteristics.