bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-inflammatory and protective effects of Pimpinella candolleana on ulcerative colitis in rats: a comprehensive study of quality, chemical composition, and molecular mechanisms
Authors: Liu Xiaoqi , Xiao Hai , Luo Mingxia , Meng Junpeng , Zhong Lin , Wu Tao , Zhao Yongxia , Wu Faming , Xie Jian 
Published: April 2024

Introduction:P. candolleana Wight et Arn. Is a traditional Chinese herbal medicine used by the Gelao nationality in southwest China, has been historically applied to treat various gastrointestinal disorders. Despite its traditional usage, scientific evidence elucidating its efficacy and mechanisms in treating ulcerative colitis (UC) remains sparse. This study aimed to determine the quality and chemical composition of Pimpinella candolleana and to identify its potential therapeutic targets and mechanisms in acetic acid-induced ulcerative colitis (UC) rats through integrated approaches.Methods: Morphological and microscopic characteristics, thin layer chromatography (TLC) identification, and quantitative analysis of P. candolleana were performed. UPLC-Q-TOF-MS, network pharmacology, and molecular docking were used to identify its chemical composition and predict its related targets in UC. Furthermore, a rat model was established to evaluate the therapeutic effect and potential mechanism of P. candolleana on UC.Results: Microscopic identification revealed irregular and radial arrangement of the xylem in P. candolleana, with a light green cross-section and large medullary cells. UPLC-Q-TOF-MS analysis detected and analyzed 570 metabolites, including flavonoids, coumarins, and terpenoids. Network pharmacology identified 12 effective components and 176 target genes, with 96 common targets for P. candolleana-UC, including quercetin, luteolin, and nobiletin as key anti-inflammatory components. GO and KEGG revealed the potential involvement of their targets in RELA, JUN, TNF, IKBKB, PTGS2, and CHUK, with action pathways such as PI3K-Akt, TNF, IL-17, and apoptosis. Molecular docking demonstrated strong affinity and binding between these key components (quercetin, luteolin, and nobiletin) and the key targets of the pathway, including JUN and TNF. Treatment with P. candolleana improved body weight loss, the disease activity index, and colonic histological damage in UC rats. Pimpinella candolleana also modulated the levels of IL-2 and IL-6 in UC rats, reduced the expression of pro-inflammatory cytokines such as IL-6, MAPK8, TNF-α, CHUK, and IKBKB mRNA, and decreased the expression of TNF, IKBKB, JUN, and CHUK proteins in the colon of UC rats, thereby reducing inflammation and alleviating UC symptoms.Conclusion:P. candolleana exerts its protective effect on UC by reducing the expression of proinflammatory cytokines and inhibiting inflammation, providing scientific evidence for its traditional use in treating gastrointestinal diseases. This study highlights the potential of P. candolleana as a natural therapeutic agent for UC and contributes to the development of novel medicines for UC treatment.
A dual contrastive learning-based graph convolutional network with syntax label enhancement for aspect-based sentiment classification
Authors: Huang Yuyan , Dai Anan , Cao Sha , Kuang Qiuhua , Zhao Hongya , Cai Qianhua 
Published: April 2024

Introduction: Aspect-based sentiment classification is a fine-grained sentiment classification task. State-of-the-art approaches in this field leverage graph neural networks to integrate sentence syntax dependency. However, current methods fail to exploit the data augmentation in encoding and ignore the syntactic relation in sentiment delivery.Methods: In this work, we propose a novel graph neural network-based architecture with dual contrastive learning and syntax label enhancement. Specifically, a contrastive learning-based contextual encoder is designed, integrating sentiment information for semantics learning. Moreover, a weighted label-enhanced syntactic graph neural network is established to use both the syntactic relation and syntax dependency, which optimizes the syntactic weight between words. A syntactic triplet between words is generated. A syntax label-based contrastive learning scheme is developed to map the triplets into a unified feature space for syntactic information learning.Results: Experiments on five publicly available datasets show that our model substantially outperforms the baseline methods.Discussion: As such, the proposed method shows its effectiveness in aspect-based sentiment classification tasks.
Good reasons for bad behavior: a randomized controlled experiment on the impact of narrative reading and writing on empathic concern, perspective-taking, and attitude
Authors: Bientzle Martina , Eggeling Marie , Kimmerle Joachim 
Published: April 2024

BackgroundEmpathic concern and perspective-taking may contribute to avoiding stigmatization of adverse health behavior. Narrative writing has been shown to be effective in promoting perspective-taking and empathy. But since narrative writing is time consuming, we tested in the present study narrative reading as an alternative, more parsimonious approach.MethodsIn a randomized controlled experiment, we compared writing a narrative text about a fictitious person who displays disapproved of health behavior to reading such a text and to a control condition in which participants wrote about an unrelated topic. With a sample of n = 194 participants, we investigated the impact of writing and reading a narrative text on promoting empathic concern and perspective-taking as well as on attitude change.ResultsWe found that both writing and reading a narrative text about the fictitious character increased empathic concern, F(1, 191) = 32.85, p &lt; 0.001, part. η2 = 0.15, and perspective-taking, F(1, 191) = 24.76, p &lt; 0.001, part. η2 = 0.12, more strongly than writing about an unrelated topic. Writing and reading a narrative text also resulted in a more positive attitude toward this person, F(1, 191) = 17.63, p &lt; 0.001, part. η2 = 0.08. Simply reading a narrative text was equally efficient as narrative writing with respect to empathic concern, p = 0.581, perspective-taking, p = 0.629, and attitude, p = 0.197.ConclusionThe finding that narrative reading is as effective as narrative writing suggests that the readers appear to be able to comprehend and engage with the story being told. When narrative reading is as effective as narrative writing, it can succeed with reduced effort in increasing empathic concern, perspective-taking, and attitude. We discuss the benefits of this approach for reducing stigmatization of adverse health behavior.
A study of the attenuation stage of a global infectious disease
Authors: Sun Tianyi , Jin Baisuo , Wu Yuehua , Bao Junjun 
Published: April 2024

IntroductionDifferences in control measures and response speeds between regions may be responsible for the differences in the number of infections of global infectious diseases. Therefore, this article aims to examine the decay stage of global infectious diseases. We demonstrate our method by considering the first wave of the COVID-19 epidemic in 2020.MethodsWe introduce the concept of the attenuation rate into the varying coefficient SEIR model to measure the effect of different cities on epidemic control, and make inferences through the integrated adjusted Kalman filter algorithm.ResultsWe applied the varying coefficient SEIR model to 136 cities in China where the total number of confirmed cases exceeded 20 after the implementation of control measures and analyzed the relationship between the estimated attenuation rate and local factors. Subsequent analysis and inference results show that the attenuation rate is significantly related to the local annual GDP and the longitude and latitude of a city or a region. We also apply the varying coefficient SEIR model to other regions outside China. We find that the fitting curve of the average daily number of new confirmed cases simulated by the variable coefficient SEIR model is consistent with the real data.DiscussionThe results show that the cities with better economic development are able to control the epidemic more effectively to a certain extent. On the other hand, geographical location also affected the effectiveness of regional epidemic control. In addition, through the results of attenuation rate analysis, we conclude that China and South Korea have achieved good results in controlling the epidemic in 2020.
COVID-19 patient satisfaction and associated factors in telemedicine and hybrid system
Authors: Gashaw Dagmawit G. , Alemu Zewdie Aderaw , Constanzo Freddy , Belay Feben T. , Tadesse Yakob W. , Muñoz Carla , Rojas Juan Pablo , Alvarado-Livacic Cristobal 
Published: April 2024

BackgroundThe quality assessment of the home-based isolation and care program (HBIC) relies heavily on patient satisfaction and length of stay. COVID-19 patients who were isolated and received HBIC were monitored through telephone consultations (TC), in-person TC visits, and a self-reporting application. By evaluating patient satisfaction and length of stay in HBIC, healthcare providers could gauge the effectiveness and efficiency of the HBIC program.MethodsA cross-sectional study design enrolled 444 HBIC patients who answered a structured questionnaire. A binary logistic regression model assessed the association between independent variables and patient satisfaction. The length of stay in HBIC was analyzed using Cox regression analysis. The data collection started on April (1–30), 2022, in Addis Ababa, Ethiopia.ResultsThe median age was 34, and 247 (55.6%) were females. A greater proportion (313, 70.5%) of the participants had high satisfaction. Higher frequency of calls (&gt;3 calls) (AOR = 2.827, 95% CI = 1.798, 4.443, p = 0.000) and those who were symptomatic (AOR = 2.001, 95% CI = 1.289, 3.106, p = 0.002) were found to be significant factors for high user satisfaction. Higher frequency of calls (&gt;3 calls) (AHR = 0.537, 95% CI = 0.415, 0.696, p = 0.000) and more in-person visits (&gt;1 visit) (AHR = 0.495, 95% CI = 0.322, 0.762, p = 0.001) had greater chances to reduce the length of stay in the COVID-19 HBIC.Conclusion70.5% of the participants had high satisfaction with the system, and frequent phone call follow-ups on patients’ clinical status can significantly improve their satisfaction and length of recovery. An in-person visit is also an invaluable factor in a patient’s recovery.
Risk factors for overweight and obesity in Mexican American children and adolescents living on the Texas–Mexico border
Authors: Low Ee Vien , Lee Miryoung , Bauer Cici , Fisher-Hoch Susan P. , McCormick Joseph B. , Rowan Paul J. , Abughosh Susan , Essien Ekere J. , Chen Hua 
Published: April 2024

BackgroundThis study aimed to compare the obesity rates between border-residing Mexican American children with the National Health and Nutritional Surveys (NHANES), and to examine the individual and household characteristics associated with weight status in these children.MethodsThis was a cross-sectional analysis of 354 children aged 8–18 years and their parents in the Cameron County Hispanic Cohort (CCHC) from 2014 to 2020. Children were categorized as healthy weight, overweight, class 1 obesity, class 2 obesity and class 3 obesity. The distribution of CCHC children's weight status was compared with Hispanic participants of the NHANES with matched age, sex, and the year of the interview. An ordinal least square regression analysis was conducted to assess the association between individual and household characteristics with CCHC children's weight status.ResultsApproximately 48.0% of CCHC children had a healthy weight, 17.9% were overweight, 22.2% were in class 1 obesity, 7.7% were in class 2 obesity, and 4.3% were in category 3. The weight distribution of the CCHC cohort was similar to that in the matched NHANES participants (p = 0.28). Being overweight was associated with higher household income (OR = 2.25, 95% CI: 1.01–5.02) while being in class 2 and class 3 obesity was associated with boys (Class 2 &amp; 3 obesity: OR = 2.94, 95% CI: 1.27–6.81) and environmental factors such as parents' BMI (Class 2 and3 Obesity: OR = 1.13, 95% CI: 1.05–1.21).ConclusionsFamily socioeconomic status was positively associated with being overweight and Class 1 obesity, while gender and parent's BMI affected a child's likelihood of being class 2 and 3 obesity.
Combining artificial neural networks and a marginal structural model to predict the progression from depression to Alzheimer's disease
Authors: Orimaye Sylvester O. , Schmidtke Kelly A. 
Published: April 2024

IntroductionDecades of research in population health have established depression as a likely precursor to Alzheimer's disease. A combination of causal estimates and machine learning methods in artificial intelligence could identify internal and external mediating mechanisms that contribute to the likelihood of progression from depression to Alzheimer's disease.MethodsWe developed an integrated predictive model, combining the marginal structural model and an artificial intelligence predictive model, distinguishing between patients likely to progress from depressive states to Alzheimer's disease better than each model alone.ResultsThe integrated predictive model achieved substantial clinical relevance when using the area under the curve measure. It performed better than the traditional statistical method or a single artificial intelligence method alone.DiscussionThe integrated predictive model could form a part of a clinical screening tool that identifies patients who are likely to progress from depression to Alzheimer's disease for early behavioral health interventions. Given the high costs of treating Alzheimer's disease, our model could serve as a cost-effective intervention for the early detection of depression before it progresses to Alzheimer's disease.
Objective and subjective sleep characteristics in hospitalized older adults and their associations to hospital outcomes
Authors: Blackwell Terri L. , Robinson Sarah C. , Thompson Nicholas , Dean-Gilley Lisa , Yu Phillip , Pressman Alice , Stone Katie L. 
Published: April 2024

PurposeSleep in the hospital setting is understudied, with limited literature describing measurement of sleep quality. This study among older inpatients in an acute-care hospital describes sleep characteristics both objectively and subjectively, and explores the associations of sleep with hospital outcomes.Materials and methodsOlder patients (n = 112) at Sutter Tracy Community Hospital were enrolled from January 2016 to November 2017. Sleep prior to admission was measured subjectively [Pittsburgh Sleep Quality Index (PSQI)], while sleep during hospitalization was measured subjectively (sleep diaries) and objectively (actigraphy, averaged over all nights). Outcomes measured included change in cognition during the hospital stay (i.e., Montreal Cognitive Assessment), length of stay (LOS), discharge to a skilled nursing facility (SNF), and re-admittance to a hospital within 30 days of discharge.ResultsThe participants were on average 68.7 ± 6.5 years old, predominately white (77%) and 55% women. Average PSQI was high (9.1 ± 4.2) indicating poor sleep quality prior to admission. Actigraphy was well-tolerated, with most (89%) having complete data. Sleep during the hospital stay was disturbed, with low levels of total sleep time (5.6 ± 2.0 h) and high levels of fragmentation (sleep efficiency 68.4 ± 15.0%). Sleep interruption was reported on 71% of sleep diaries, with the most common reasons being due to medical care [measurement of vitals (23%), staff interruptions (22%), blood draws (21%)]. Those with lower sleep efficiency had more cognitive decline upon discharge. Although underpowered, there was a suggestion of an association with poor sleep and the likelihood of being discharged to a SNF. Those with worse self-reported sleep quality (PSQI) prior to admission had a slightly longer LOS. No associations were seen with sleep quality and likelihood of readmission.ConclusionsCollection of objective and subjective sleep measures was feasible among hospitalized older adults. Disrupted sleep was common, and was potentially related to poor hospital outcomes. Our next steps will be to leverage these results to design and implement an intervention to improve sleep in hospitalized adults.
Mapping the flow of veterinary antibiotics in Kenya
Authors: Morang’a Alexina K. , Muloi Dishon M. , Kamau Simon M. , Onono Joshua O. , Gathura Peter B. , Moodley Arshnee 
Published: April 2024

IntroductionTo effectively regulate and reduce antibiotic use, in the livestock sector, a thorough understanding of the flow of veterinary antibiotics will help to identify key nodes in the chain for targeted interventions. The aim of this study was to understand the flow of antibiotics from import to end-user, and identify relevant governance mechanisms.MethodsA mixed methods approach was used to collect data in three Kenyan counties (Nairobi, Kiambu, and Kajiado). Focus group discussions (n = 23), individual interviews (n = 148), and key informant interviews (n = 10) were conducted.ResultsThe key actors identified include primary wholesalers, secondary wholesalers, retailers, animal health service providers (AHSPs), and farmers. Kenya imports 100% of its veterinary antibiotics: primary wholesalers legally import antibiotics as finished pharmaceutical products (90%) or active pharmaceutical ingredients (10%) after approval by the Veterinary Medicines Directorate. Secondary wholesalers play a major role in the distribution of antibiotics (60% of antibiotics) from importers to farmers, AHSPs, and retailers. Some of the illegal sources of antibiotics include unlicenced/unauthorized middlemen and online platforms that sell directly to retailers, AHSPs, and farmers.DiscussionDespite the presence of various laws and regulations governing the antibiotic value chain, implementation has been a challenge due to financial and human resource constraints. This contributes to over-the-counter sale of antibiotics without prescription, unlicensed businesses selling antibiotics, illegal importation, and presence of poor-quality drugs. There is a need to review the applicability of existing policies and address policy gaps (e.g., product containing antibiotic combinations, and use of human critically important antibiotics) to ensure the prudent sale and use of antibiotics, pharmacovigilance, antimicrobial use surveillance, and developing a business model that aligns with antibiotic stewardship. Additional interventions include awareness raising and capacity building of the different stakeholders along the antibiotic distribution chain to reduce antibiotic mis- and overuse.
Research on the Ecological Restoration Effects of a Vallisneria natans (Lour.) Hara-Dominated Multitrophic Level Ecosystem
Authors: Li Bin , Han Zheng , Jiang Ruitong , Cai Qingjie , Zhang Meiqiong , Wang Rong , Liu Yuchao , Shao Liu , Wu Meiqin , Zhang Jianheng , He Wenhui , Liu Jinlin , He Peimin 
Published: April 2024

This study aims to assess the ecological restoration effects of Vallisneria natans in a multitrophic level ecosystem. The water-purification effects of two hierarchical configuration modes of V. natans-Bellamya aeruginosa and V. natans-B. aeruginosa-Hyriopsis cumingii were studied. Results show that a V. natans and B. aeruginosa configuration ratio of 15:2 stabilizes water quality at Grade IV (TN ≤ 1.5 mg/L, TP ≤ 0.3 mg/L), and increasing B. aeruginosa density significantly reduces total phosphorus. The V. natans, B. aeruginosa, and H. cumingii configuration at 15:2:10 stabilizes water at Grade III (TN ≤ 1.0 mg/L, TP ≤ 0.2 mg/L), with a positive correlation between H. cumingii density and chlorophyll-a removal. Furthermore, the filtration and biocycling actions of B. aeruginosa (snails) and H. cumingii (mussels) significantly reduce levels of Total Nitrogen (TN), Total Phosphorus (TP), and Ammonium (NH4+-N) in water, thus enhancing the self-purification capacity of the water bodies. However, the bioturbation effect of H. cumingii can temporarily increase phosphorus release from sediments, leading to a short-term rise in TP concentration in the water. Overall, the study concludes that multitrophic level ecosystems are effective in purifying water quality and offer significant ecological restoration benefits. This research provides crucial data support for future construction and ecological restoration projects involving multitrophic level approaches in China’s rivers and lakes.
Peningkatan Proses dan Hasil Belajar Matematika Menggunakan Model Problem Based Learning di Sekolah Dasar
Authors: Ajeng Rahmatika Agustin  , Nyoto Harjono  
Published: April 2024

Mathematics is considered a difficult subject matter for students, which causes problem-solving processes and low learning outcomes. This collaborative classroom action research (PTKK) was carried out to improve the process and results of learning mathematics on the topic of addition and subtraction of 1st grade students of SD Negeri Randuacir 03 Salatiga. It was carried out over two cycles with two meetings in each cycle. The data collection technique uses test techniques in the form of posttests and non-tests in the form of observations, with data collection tools using posttest questions, student learning process observation instruments, and teacher activity observation instruments. The posttest questions were tested for validity with a significance of 0.05 and reliability with the reliable category. The results of the research obtained (1) that the problem-based learning model can improve the learning process in class I, which is known from the results of observations of student learning processes and teacher activities in the pre-cycle; the percentages were 42.85% and 57.14 in the category not good, cycle I 72, 32%, and 71.42% in the good category, and cycle II 85.71% and 92.85% in the very good category; and (2) that the problem-based learning model can improve learning outcomes with a percentage of 78.57% from the pre-cycle to cycle I and 100% from cycle I to cycle II. The conclusion from the research results is that the problem-based learning model can improve the mathematics learning process and outcomes of 1st grade students.
Abstrak
Matematika dianggap sebagai muatan pelajaran yang sulit bagi siswa yang menyebabkan proses pemecahan masalah dan hasil belajar rendah. Penelitian Tindakan Kelas Kolaboratif (PTKK) ini dilakukan untuk memperbaiki proses dan hasil belajar matematika topik penjumlahan dan pengurangan di kelas I SD Negeri Randuacir 03 Salatiga yang dilaksanakan selama dua siklus dengan tiap siklus dua pertemuan. Teknik pengumpulan data menggunakan teknik tes berupa posttest dan nontes berupa observasi, dengan alat pengumpulan data menggunakan soal posttest, instrumen observasi proses belajar siswa, dan instrumen observasi aktivitas guru. Soal postest diuji validitas dengan signifikansi < 0,05 dan uji reliabilitas dengan kategori reliabel. Hasil penelitian diperoleh (1) model Problem Based Learning dapat meningkatkan proses pembelajaran di kelas I yang diketahui dari hasil observasi proses belajar siswa dan aktivitas guru pada pra siklus diperoleh presentase 42,85% dan 57,14 dengan kategori kurang baik, siklus I 72,32% dan 71,42% dengan kategori baik, dan siklus II 85,71% dan 92,85% dengan kategori sangat baik; (2) model Problem Based Learning dapat meningkatkan hasil belajar dengan presentase 78,57% pada pra siklus ke siklus I dan 100% dari siklus I ke siklus II. Simpulan dari hasil penelitian bahwa model Problem Based Learning dapat meningkatkan proses dan hasil belajar matematika siswa kelas I.