bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of Rapid Verbal Persuasion to Promote Influenza Vaccination: A Randomized Controlled Trial
Authors: Xu Dong , Luo Huanyuan , Liu Siyuan , Chen Xiaoshan , He Tianfeng , Gong Wenjie , Liang Huijuan , Zhang Nan , Jin Yingying , Wu Dan , Bishai David , Zhang Dexing , Gong Wenfeng , Cai Yiyuan , Wang Duolao , Bai Yanping , Zhu Jiayu , Li Qing-Qing , He Wenjun , Zhao Qing , Zhang Lanping , Li Xiuzhen , Zhu Xiaoqing 
Published: February 2025

Abstract

Background
Influenza vaccination rates remain suboptimal globally, particularly in China, highlighting the need for effective, low-cost interventions. This randomized controlled trial aimed to evaluate the effectiveness of a 30-second Rapid Verbal Persuasion intervention in promoting influenza vaccination uptake among individuals visiting vaccination centers in China.
Methods
The study was conducted from November 13 to December 7, 2023, across eight primary healthcare centers in three Chinese cities (Ningbo, Hohhot, and Shaoyang). Participants visiting for non-influenza vaccinations were randomly assigned to either the intervention or control group. In the Rapid Verbal Persuasion group, doctors delivered a 30-second theory-driven message promoting influenza vaccination immediately before administering other vaccines. The control group received standard care without active influenza vaccine promotion. The primary outcome was influenza vaccination uptake within one month.
Findings
Among 1,922 participants (1,040 intervention, 882 control), the influenza vaccination rate was 14.62% in the intervention group compared to 0.91% in the control group (RR=16.11, 95% CI: 7.96-32.62), indicating a significant increase due to the rapid intervention. Subgroup analyses revealed greater effectiveness among younger, female, better-educated, and urban participants or their companions.
Interpretation
This 30-second Rapid Verbal Persuasion intervention significantly increased influenza vaccination rates, demonstrating its potential as a simple, cost-effective strategy to address suboptimal vaccination coverage, particularly in resource-limited settings. Future research should explore ways to enhance its impact further, such as combining the intervention with strategies to improve vaccine availability and affordability, targeting adults accompanying children, and testing even shorter messaging.
Trial registration number: ChiCTR2300077506
The Effect of Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: A Randomized Controlled Trial
Authors: Galyean Shannon , Alcorn Michelle , Chavez Justin , Niraula Surya Raj , Childress Allison 
Published: February 2025

Abstract

Background
Age-related muscle loss can be decreased with increased protein intake. Recent evidence suggests that increasing animal-based protein such as lean beef can be the most effective for age-related muscle repair and growth. Culinary medicine (CM) is a science-based field to teach people the art of food and cooking with the science of medicine to improve health.
Aim
This study aimed to assess the impact of a digital culinary medicine education program emphasizing lean beef on protein intake and muscle quality among community-dwelling senior adults.
Methods
A 16-week randomized study compared a culinary medicine intervention group (CM) to a control group (CN). Among 47 senior adults assessed for eligibility, 28 participants completed the intervention. The CM invention included weekly cooking demonstration and nutrition education videos. Protein intake, cooking effectiveness, physical activity, and nutrition knowledge were assessed with questionnaires while muscle quality, vitamin B12, folate, and creatinine levels were objectively measured.
Results
Muscle quality measurements showed a significant difference in change in muscle mass between groups (P = 0.041). Higher protein intake was seen in the CM group compared to a decrease in protein intake seen among the CN group. However, there was no between-group difference in protein intake from the pre-study (P = 0.454). Similar results were seen with the other measurements from baseline.
Conclusion
The results suggest that this CM intervention was associated with improved muscle mass. There is also potential for this type of intervention to increase protein intake.
Clinical Trials ID: NCT06157385
The Efficacy of a Novel Medical Artificial Intelligence Large Model(MedGo)-Guided Identification and Personalized Treatment of Sepsis: Study Protocol for a Single- centered Randomized Controlled Trial
Authors: Jiang Sen , Liu Tong , Wang Chunxue , An Bo , Zhang Haitao , Tang Lunxian 
Published: February 2025

Abstract

Background
Sepsis, a life-threatening organ dysfunction resulting from a dysregulated host response to infection, remains a major global health challenge with high morbility and mortality. Current diagnostic and management frameworks still lack the satisfied sensitivity and specificity for early detection and personalized treatment. In this study, we aim to evaluate the efficacy of MedGo-Sepsis, a novel large language model developed by our collaborating team and us that integrates clinical and immunological data, to guide the identification and personalized treatment of sepsis in the emergency department.
Methods
This single-center, randomized controlled trial will enroll adult patients presenting to the emergency department with suspected sepsis. Participants will be randomized 1:1 at the physician team level to either the intervention group receiving standard care augmented by MedGo-Sepsis guidance or the control group receiving standard care alone. MedGo-Sepsis provides real-time risk assessments, detailed immune parameter profiling, stratification based on immune phenotypes, and personalized treatment recommendations. The primary outcome is 28-day all-cause mortality. Secondary outcomes include changes in Sequential Organ Failure Assessment (SOFA) score, diagnostic accuracy, time to appropriate antibiotic administration, resource utilization, patient-reported outcomes, and physician workload.
Discussion
This trial will assess whether MedGo-Sepsis, through the integration of individualized immune data with large language model technology, improves outcomes for patients with sepsis compared to standard care. The combination of enhanced diagnostics and tailored therapeutic strategies has the potential to advance precision management of sepsis in the critical emergency setting.
Trial registration
The trial has been prospectively registered in the Chinese Clinical Trial Registry (ChiCTR2400094116) on December 17, 2024.
Phototropic self-growing hydrogels based on a tricyanofuran derivatized photoswitch
Authors: Li Chuang , HAN PEIXI , Yang Xuehan , Zhou Shuailong , Zheng Yifan , Chu Zhaomiao , Du Mengqi 
Published: February 2025

Abstract

Phototropism is ubiquitous in plants that endows them directional movement and substantial growth toward light sources. Simultaneous replication of such phototropic movement and volumetric growth in synthetic polymers is important but currently remains challenging. Here, we report the molecular design of a photoswitchable tricyanofuran (TCF) based hydrogel that can concurrently display such phototropic movement and self-growth in water under stimulation of light and pH. The macroscale growth of the hdyrogel originates directly from the molecular charge rise of the TCF switch upon isomerization induced by light or pH, which dramatically improves the polymer hydrophilicity and facilicates water diffusion into the network. As the growing rate under each stimulation is independently regulated, we successfully developed TCF hydrogels displaying heterogeneous growth accompanied with phototropic bending deformation by taking the advantage of the differential growing rates induced by light and pH. Importantly, the phototropic deformation direction during the growing process can be flexibly switched to be either positive or negative by tuning the light irradiation and pH conditions for applications in replicating the structure and function of natural light-responsive systems. Our work provides a novel molecular design strategy for advancing the development of biomimetic systems with capability of phototropic deformation and self-growth.
Positive Psychology Interventions: A Catalyst for Job Satisfaction, Work Engagement, and Withdrawal Intentions Among Remote-Working Cancer Survivors in Rural Areas
Authors: Renani Hamid Yari , Rahmanian Alireza , Saeidi Zahra , Birashk Behrooz , Saraei Iman , Ghodusi Shirin 
Published: February 2025

Abstract

Background
Advances in cancer treatment have significantly increased the survival rate of cancer patients, but these survivors often face challenges in the workplace. Existing literature highlights the significant influence of cancer on job performance, job satisfaction, and the increased risk of withdrawal intention. However, the effects of positive psychology interventions on cancer survivors, particularly in less urbanized settings and remote worker communities, remain underexplored.
Purpose
This study investigates the effects of positive psychology interventions on job satisfaction, work engagement, and withdrawal intentions among cancer survivors in rural and remote workforce communities.
Methods
A quasi-experimental design was employed, involving 68 cancer survivors. The study used the Minnesota Job Satisfaction Questionnaire, the Utrecht Work Engagement Scale, and the Withdrawal Intention Scale to measure outcomes following a 14-session positive psychology intervention. The results revealed statistically significant improvements in the experimental group compared to the control group.
Results
Job satisfaction mean scores increased from 50.23 to 58.94, work engagement mean scores rose from 26.79 to 31.05, and withdrawal intentions mean scores decreased from 48.35 to 39.05. These findings highlight the potential of positive psychology interventions to address the unique challenges faced by cancer survivors in remote workforce communities, particularly in less urbanized areas.
Conclusions
By enhancing job satisfaction and work engagement while reducing withdrawal intentions, these interventions can significantly contribute to the occupational well-being of cancer survivors, advocating for their integration into cancer care and organizational practices.
Reduction of Postpartum Hemorrhage Through Quality Improvement Science
Authors: Cury Giovana Signorelli Astolfi , Negrini Romulo , Santana Eduardo Felix , Campanharo Felipe Favorette 
Published: February 2025

Abstract

Background
Regarding causes of avoidable maternal mortality, Postpartum Hemorrhage (PPH) remains in first place in the world and second in Brazil. Considering the latent need for improved diagnostic and therapeutic approaches to PPH, a multidisciplinary team from Hospital Israelite Albert Einstein (HIAE) developed an Institutional Protocol based on Improvement Science.
Aim
To assess the impact of this protocol on the reduction of maternal morbidity due to postpartum hemorrhage (PPH) within the institution.
Methods
Observational, descriptive, retrospective study comprising all parturient attended during childbirth at HIAE Morumbi unit from January 2017 to December 2021. Data were obtained from the Business Intelligence (BI) information system, with no identification of patients. The examined indicators were evolution of quantity and weight of surgical pads used during childbirth assistance (outcome), adherence rate to the counting and weighing of pads (process) and incidence of unused blood reserves (equilibrium). Exclusion criterion: blood reserves not associated with hemorrhagic complications during childbirth. The statistical analysis was based on execution diagrams that demonstrate the evolution of indicators over short intervals, thereby enabling a temporal evaluation of the implemented strategies’ effects.
Results
Adherence to the counting and weighing of used pads during childbirth exhibited a significant change within the first month of the protocol's implementation. The average quantity and weight of used pads showed a marked and sustained reduction. Beside subsequent use, there was an increase on the average quantity of unused blood reserves.
Conclusion
The process changes engendered by the new protocol have facilitated a reduction in blood loss during the births assisted at the unity over the considered period.
HSMTL-Net: A Multi-Task Learning Framework for Human Segmentation with Integrated Regression and Classification Modules
Authors: Rohani Faezeh , Khobdeh Soroush Babaee 
Published: February 2025

Abstract

Human segmentation is a critical task in computer vision, with many applications in different fields. In this paper, we propose a novel multi-task learning approach, called HSMTL-Net, for human segmentation that incorporates classification and regression tasks along with segmentation. The proposed model is inspired with the U-Net architecture but with less layers and same depth features, which consists of three modules: Seg-Module, Gender-Module, and Seg-Tuner-Module. The Seg-Module performs the segmentation task, while the Gender-Module performs the gender classification task, and the Seg-Tuner-Module performs the tasks that relates to age and other parameters estimation. The proposed approach achieved an exceptional performance for human segmentation, and in addition to that, it includes gender classification and age estimation. Multi-task learning enables the model to learn multiple related tasks simultaneously using shared features and parameters, thereby improving the generalization and efficiency of the model. As a result, the proposed model achieved a Dice score of 97.83% and a mean IoU of 96.21%, which outperformed all previous approaches.
Administration of probiotics and synbiotics and systemic inflammation in Kenyan infants: an open label, randomised, phase II trial
Authors: Otiti Mary Iwaret , June Micah , K’Oloo Alloys , Chomba Miriam , Dodd James , Kiu Raymond , Hall Lindsay , Wang Duolao , Otieno Kephas , Kariuki Simon , Kuile Feiko O. Ter , Allen Stephen 
Published: February 2025

Abstract

Environmental enteric dysfunction (EED) in early life, caused by gut pathogen colonisation, contributes to chronic systemic inflammation (CSI) which impairs growth and organ development and increases non-communicable disease risk. Pro/synbiotics may prevent or ameliorate EED, and thereby reduce CSI, through boosting colonisation resistance against enteropathogens and provide other intestinal and immune benefits. We evaluated three pro/synbiotics consisting of live, multi-strain Bifidobacterium spp. and Lactobacillaceae in reducing CSI. In this open-label, randomised, four-arm, phase II trial, 600 healthy Kenyan newborns (1–3 days old, birthweight ≥2000g) were allocated 1:1:1:1, stratified by HIV exposure, to receive Labinic synbiotic, Lab4b synbiotic or Lab4b probiotic or no intervention daily for ten days, then weekly until six months. The primary outcome was CSI (plasma α1-acid glycoprotein > 1g/L) at six months with blinded laboratory assessments. At six months, CSI occurred in 60/138 (43%) controls versus 4/144 (3%; relative risk (RR) 0.06, 95% CI 0.02–0.17; p < 0.0001) infants in the Labinic synbiotic, 3/132 (2%; RR = 0.05, 0.02–0.16; P < 0.0001) in the Lab4b synbiotic, and 3/141 (2%; RR = 0.05, 0.02–0.15; P < 0.0001) in the Lab4b probiotic arm. Serious adverse events and mortality over 0–24 months were similar across study arms. Pro/synbiotics safely and markedly reduced CSI in this disadvantaged population, warranting investigation of health impacts.
Controlling the morphology transition on MOVPE-grown (100) β-Ga2O3 film between step-flow growth and step-bunching: A machine learning-assisted approach
Authors: Chou Ta-Shun , Anooz Saud Bin , Dropka Natasha , Chen Han-Hsu , Galazka Zbigniew , Albrecht Martin , Fiedler Andreas , Popp Andreas 
Published: February 2025

Abstract

The step-bunching instability in (100) β-Ga₂O₃ films grown via metalorganic vapor phase epitaxy (MOVPE) was investigated using a machine learning approach based on Random Forest (RF). The study reveals the interplay of Ga supersaturation (O2/Ga) and impurity effects as coexisting mechanisms driving the morphological transition (from step-flow growth to step-bunching). The developed machine-learning framework accurately classifies growth morphology and offers valuable insights by correlating theoretical principles with experimental parameters. Critical growth parameters influencing the film morphology were identified. The corresponding strategy, high Ga supersaturation, is proposed to mitigate the step-bunching formation and maintain the desired step-flow growth mode. Despite the challenges posed by small datasets, the RF model demonstrates robust classification performance, establishing machine learning as a powerful tool for experimental science.
Optimal Plant Design Using A Non-Linear Generalized Structured Component Analysis Approach
Authors: Nurudeen Abdulhakeem Hassan , Ugheoke Iyenagbe Benjamin 
Published: February 2025

Abstract

Plant design is essential in improving the performance of a plant, reducing the cost of production, enhancing material handling costs as well as generating a good return on investment. Poorly designed facilities are susceptible to higher production costs and material handling, and inadequate utilization of resources such as This study was conducted to investigate the feasibility of integrating non-linear generalized structured component analysis with systematic layout planning methodology for facility layout design to derive a statistical inference from the combination. The study adopted the non-linear Generalized Structural Component Analysis methodology on a proposed plant layout dehydration of fruits and vegetables. At the end of the study, it was observed that it was possible to adopt non-linear GSCA in plant design to derive meaningful statistical inferences when the ratings were inverted. The study proposes these findings as novel. The transposed rating table results obtained were better than the Initial experiments performed and it’s suggested that when integrating non-linear GSCA to facility design the inverted approach should be adopted. The results also proved that nonlinear generalized structured component analysis is suitable and can be incorporated as a new plant design approach.
Imagery Rescripting and Imaginal Extinction attenuate the Return of Generalized Fear
Authors: Mitra Sharmili , Asthana Manish Kumar 
Published: February 2025

Abstract

Standard extinction (SE) is the most widely implemented intervention for reducing conditioned and generalized fear; however, the possibility of fear return still remains. Hence, novel interventions may be used to augment the efficiency of SE. Imagery rescripting (ImRS), based on the premise of unconditioned stimulus (UCS) devaluation, encompasses the devaluation of the cognitive representation of the UCS in a positive direction. Imaginal extinction (IE), based on the principles of UCS expectancy evaluation, involves vivid imagination of the conditioned stimuli during extinction. In the current study, we compared the efficacy of ImRS over IE and SE in attenuating the return of generalized fear. Seventy-two healthy individuals were randomly assigned to ImRS, IE, or SE groups. Day 1 comprised the fear acquisition and generalization phases. On day 2, the intervention and generalization testing phases were conducted. On day 3, 15 days after acquisition, the return of fear due to spontaneous recovery was assessed. Our study is the first known to compare the efficacy of ImRS and IE in attenuating the return of generalized fear response. We found that ImRS effectively attenuated the return of fear response. Further, the CS valence increased in a positive direction on Day 3. However, the rate of extinction was slower, and the generalized fear response was sustained for the IE group. The findings suggest that distinct mechanisms may be involved in ImRS and IE. ImRS may require a higher level of cognition, inducing novelty due to introducing the positive narrative. ImRS resulted in a competition between the two memories during retrieval, following a dynamic ‘higher route’. On the contrary, the fear responses were sustained in the IE group, showing the possibility of a slow and stagnant ‘lower route’. Hence, ImRS may be a more effective intervention for attenuating the return of generalized fear.
Understanding Autistic Identity Contingencies: The Chain Mediation Effect of Autism Acceptance and Loneliness in Ableist Microaggressions and Social Camouflage
Authors: Guan Siqing , Takahashi Fumito , Wada Makoto , Takashina Hikari N , Ueda Midori , Kawaguchi Yasuo , Kawashima Masamitsu , Kato Takeo , Ogawa Shinichiro , Tsuchiya Kenji , Oshima Fumiyo 
Published: February 2025

Abstract

Ableist microaggressions—subtle forms of disability-based discrimination—serve as a key minority stressor. Amplified by autistic identity contingencies that shape how autistic identity is judged and treated in social contexts, these factors drive social camouflage in autistic adults, compelling them to conceal autistic characteristics for adapting to non-autistic groups, often resulting in negative mental health outcomes. This study proposes a novel Autistic Identity Contingencies Model to explore how autism acceptance and loneliness mediate the relationship between ableist microaggressions and social camouflage. An online survey of 330 autistic adults was conducted, followed by hierarchical multiple regression and chain mediation analyses. Results indicated that, ableist microaggressions positively predicted three social camouflage phenotypes: compensation, masking, and assimilation, with loneliness also predicting assimilation. Furthermore, after controlling for personal attributes, general stress and mental health conditions, less external autism acceptance and loneliness mediated the positive relationship between ableist microaggressions and assimilation, whereas internal autism acceptance showed no significant effect. Assimilation is uniquely shaped by autistic social identity threat and loneliness, distinguishing it from compensation and masking. These findings highlight social camouflage as responses to minority stressors driven by social autistic identity contingencies, rooted in stigmatized behaviors rather than in personal autistic identity.
The high-pressure, vacancy-stabilized component in clinopyroxenes
Authors: Baziotis Ioannis , Ma Chi , Klemme Stephan , Berndt Jasper , Tschauner Oliver , Asimow Paul D. 
Published: February 2025

Abstract
Motivated by the recent discovery of albitic clinopyroxene, we assess the molar volume systematics of vacancy-stabilized, high-pressure clinopyroxenes. Previous assessments used the Ca-Eskola component (Ca0.5□0.5)M2AlM1Si2TO6 (where the empty rectangle symbol denotes a vacancy) as an end-member and were limited to compositions with ≤ 50% vacancies in the M2 site. The discovery of albitic jadeite calls for extension of the solid solution space towards an end member with entirely vacant M2 sites, □M2SiM1Si2TO6, i.e. silica in the C2/c pyroxene structure. Based on our new and compiled data, we fit a model for volumes of clinopyroxenes in an 11-component subsystem. We tested two different scenarios: ideal mixing and symmetric excess volumes. Ideal mixing is easily rejected, as the correlation between vacancy concentration and volume at standard conditions is clearly nonlinear. The symmetric excess volume model, however, yields an adequate fit to the data when using 3 excess terms (Hd-En, Hd-Di, and Hd-Jd). The estimated molar volume of the clinopyroxene-structured silica end member, which has one octahedrally-coordinated silicon atom per formula unit, is 60.77 ± 0.75 cm3/mol on a six-oxygen formula basis, slightly smaller than that of coesite (61.73 cm3/mol) but much larger than that of stishovite (41.44 cm3/mol). We also obtained a molar volume of 62.16 ± 0.75 cm3/mol for the Ca-Eskola component, modestly larger than earlier estimates extrapolated with an ideal mixing assumption from natural samples (60.52 ± 0.73 cm3/mol) or experiments (60.87 ± 0.63 cm3/mol). The proposed volume model provides a partial basis for assessing the formation conditions of vacancy-stabilized pyroxenes.