bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of extraction and enrichment process of cannabidiol from industrial hemp and evaluation of its bioactivity
Authors: Wu Junkai , Zhang Xiaomeng , Liu Xiaoqing , Sheng Zunlai , Hu Jianping , Zhang Feiyan 
Published: February 2025

IntroductionThe Cannabis Sativa L., a perennial dioecious herb renowned for its industrial applications, serves as the source of hemp. Cannabidiol (CBD), a non-psychotropic compound derived from industrial hemp, has garnered considerable interest due to its promising therapeutic potential.MethodsThe extraction parameters for CBD from industrial hemp were optimized using the Box-Behnken design and response surface methodology (RSM). The purification process involved characterizing the penetration and desorption profiles of CBD on HPD-100 resin. The in vitro antibacterial activity was assessed by determining the minimum inhibitory concentration (MIC) against Staphylococcus aureus and Escherichia coli. Antioxidant properties were evaluated using DPPH and ABTS assays, as well as an iron-reducing ability test.ResultsAfter optimization, the extraction rate of CBD reached 0.26 ± 0.02%. The use of HP-100 resin in the purification process resulted in a significant enrichment of CBD content, which was 4.2 times higher than that of the crude extract, with a recovery rate of 83.13%. The MIC against S. aureus was found to be 5 mg/mL, while no inhibitory effect was observed against E. coli. The IC50 values for the DPPH and ABTS assays were 0.1875 mg/mL and 2.988 mg/mL, respectively, indicating the potent antioxidant capacity of CBD. Additionally, CBD demonstrated a strong iron-reducing ability.ConclusionThese findings contribute to the development of CBD for broader applications in various industries, highlighting its potential as a valuable compound in health and wellness sectors.
The regulation of tobacco growth under preceding crop planting: insights from soil quality, microbial communities, and metabolic profiling
Authors: Zhao Peiyan , Zhou Houfa , Liao Xiaolin , Zhao Leifeng , Zheng Yuanxian , Xiong Tiane , Zhang Gaorun , Jiang Sirong , Wang Jiming , He Yuansheng , Li Jiangtao , Zhu Jieying , Zhang Yongjun , Li Yanrun , Nian Fuzhao , Liu Di 
Published: February 2025

IntroductionSpecific microorganisms and metabolites in soil play key roles in regulating organismal behavior. Currently, the effects of different preceding crops on the rhizosphere soil quality of flue-cured tobacco remain unclear.MethodsFour treatments were compared in the study: fallow + tobacco (CK), maize + tobacco (T1), rapeseed + tobacco (T2), and wheat + tobacco (T3).Results and discussionResults showed that preceding crops significantly enhanced soil nutrient levels and improved tobacco growth by altering rhizosphere metabolites and microbial community structure. Previous cultivation of maize and rapeseed significantly promoted tobacco growth, rapeseed and wheat cultivation enhanced the diversity of soil bacterial communities, and notably decreased the abundance of urea-degrading bacteria. In contrast, the preceding crop of maize reduced plant pathogenic fungi and promoted positive microbial interactions. Metabolomics analysis showed that different preceding crops altered lipids, organic acids, flavonoids, alkaloids, and terpenoids, enhancing secondary metabolite synthesis pathways in soil. Preceding crops regulated rhizosphere metabolites which potentially participated in soil carbon and nitrogen cycling, balancing soil nutrients, and improving tobacco yield. Overall, the three preceding crops altered the composition and function of metabolites and microbial community structures in rhizosphere soil, thereby increased soil nutrient concentration. Both maize and rapeseed cultivation significantly boosted tobacco growth and biomass. These findings offer new insights into the potential interactions between rhizosphere metabolites and microbial communities and strategies of comprehensively regulating tobacco growth.
DAILY – A personalized circadian Zeitgeber therapy as an adjunctive treatment for alcohol use disorder patients: results of a pilot trial
Authors: Springer Naomi , Echtler Lisa , Volkmann Paul , Hühne-Landgraf Anisja , Hochenbleicher Jasmin , Hoch Eva , Koller Gabi , Landgraf Dominic 
Published: February 2025

BackgroundDisturbances of circadian rhythms and everyday structures are hallmarks of alcohol use disorder (AUD). Recurring activities such as sleep, activity, and meals represent time cues, so called Zeitgebers, that synchronize the circadian system. With our newly developed therapy approach for AUD patients, we aim to reduce relapses and alcohol consumption in AUD patients undergoing a withdrawal program by strengthening their circadian rhythms.Methods/DesignWe aim to achieve the improvement of circadian rhythms with personalized structure plans for daily Zeitgeber activities, which are used in parallel with the standard therapy at our clinic. The DAILY pilot study is a six-week monocentric trial with a controlled, randomized, single-blinded, parallel-group design. 41 AUD patients participated in the pilot study and were randomly assigned to an intervention group (IG) or a control group (CG).ResultsThe variability of daily activities was significantly lower in the IG group than in the CG group. Of the IG participants, two had relapsed during the study (&lt;12%), whereas ten relapsed in the CG group (&gt;60%). The relapsing IG participants recorded a total of three alcohol consumption days, while the CG participants recorded 52 consumption days. Abstinent participants showed significantly less variability in the times of their daily activities than relapsed participants. In addition, our analyses indicate that craving for alcohol is related to variability in the time of getting up and that craving and temporal variability increase before relapses. Moreover, the general well-being of the IG participants improved more than that of the CG participants.DiscussionThe data from this pilot study show that following a personalized daily structure plan helps AUD patients to remain abstinent during withdrawal therapy. The analyses indicate that temporal variability of daily activities and the risk of relapse are correlated. On the one hand, adherence to the daily structure may prevent relapse, on the other hand, an increase in variability may be a helpful predictor of approaching relapse. In our view, these data justify a continuation of the DAILY study with the addition of further measurements such as the determination of endogenous circadian rhythms.Clinical trial registrationhttps://drks.de, identifier DRKS00019093.
Development of a social learning theory-based pressure injury training program for nursing assistants in Chinese nursing homes
Authors: Guo Yanxia , Yang Shengnan , Boonyamalik Plernpit , Powwattana Arpaporn , Zhu Wen , Xu Lingxia 
Published: February 2025

IntroductionPressure injury (PI) is a significant concern in Chinese nursing homes, particularly in China, especially due to the rapidly aging population. Nursing assistants play a vital role in PI prevention and management but often lack adequate training. To address this gap, we developed a training program for nursing assistants based on Social Learning Theory (SLT), aimed at improving their competencies in PI prevention and management. The modified Delphi method was used to gather expert consensus on the program’s structure and content.MethodsA two-round Delphi process was performed involving an expert panel in wound care, community nursing, geriatric nursing, and nursing education. The training program was designed based on SLT, emphasizing observational learning, enactive learning, and behavioral reinforcement. Several experts evaluated the training program’s content, which was informed by systematic reviews and qualitative interviews with stakeholders. Data analysis included expert’s positive coefficient, expert’s authority coefficient (Cr), expert’s coordination coefficient (Kendall’s W), and coefficient of variation (CV) were used to reflect reliability and consensus.ResultsConsensus was reached on 79 key indicators for the training program, which included 4 first-level indicators (training objectives, content, methods, and evaluation), 13 second-level indicators, and 62 third-level indicators. The expert authority coefficient was 0.93, and Kendall’s W values of 0.372 (p &lt; 0.001) in the first round and 0.177 (p &lt; 0.001) in the second round indicated strong agreement among experts. The program integrates SLT principles, such as attention, retention, motor reproduction, and motivation, to enhance the training’s effectiveness.ConclusionThe study developed a comprehensive SLT-based PI training program for nursing assistants in Chinese nursing homes using the modified Delphi method. The program addresses the critical need for competency-based training in PI prevention and management. Future research should focus on the implementation and evaluation of this program in real-world settings to determine its effectiveness in improving nursing assistants’ skills and reducing PI incidence among older adult residents.
Artificial intelligence: a useful tool in active tuberculosis screening among vulnerable groups in Romania - advantages and limitations
Authors: Mahler Beatrice , Stoichiță Alexandru , Băiceanu Dragoș , Panciu Traian-Constantin , Dendrino Dragoș , Mihai Mihaela , Bobocea Raluca , Ibraim Elmira , Bălteanu Mara , Popescu Oana , Burecu Mădălina Oana , Moșteanu Ioana Mădălina , Veronese Vanessa , Matache Radu , Munteanu Ioana , Popa Cristina , Dragomir Justina Antonela 
Published: February 2025

IntroductionDespite advances in diagnostic technologies for tuberculosis (TB), global control of this disease requires improved technologies for active case finding in selected vulnerable populations. The integration of artificial intelligence (AI) into imaging modalities has been anticipated to assume a pivotal position in conjunction with traditional bacteriological diagnostic approaches, especially in the active diagnosis of vulnerable groups.MethodsThe study was conducted as a prospective investigation spanning from November 2019 to October 2023, in Romania’s national TB screening project. From total of 92,368 tested participants, 404 patients were included in the study, with 202 individuals diagnosed with TB and 202 individuals serving as controls. The initial interpretation of radiological images was performed by AI X-Vision software and patients with suspicious findings were confirmed to have TB using GeneXpert testing. The objective of this study is to discover a threshold at which the AI score can accurately assess the risk of TB, regardless of the patient’s medical background.ResultsThe study involved a number of 404 people, among whom 202 were diagnosed with TB out of a total of 92,368 participants, and the remaining 202 patients represent the control group. The current study highlighted, at an AI threshold value of 0.4, that 89% of the screened people benefited from a correct assessment using the AI associated with the radiological examination. ROC curve analysis indicates an AUC of 0.923 (95% CI:0.893–0.947; significance level p &lt; 0.0001) which shows that the test has a high capacity to accurately detect individuals with TB and also to rule out those who do not have the disease, with sensitivity 87.1, specificity 91.6 and criterion &gt;0.3585.ConclusionOur study brings to the fore the significance of integrating AI software X-vision with bacteriological diagnosis in detecting TB among vulnerable groups in Romania. This underscores the imperative at the global level to develop solutions in the prompt diagnosis of TB, particularly within vulnerable groups.
Impact of healthcare-associated infections on in-hospital outcomes during the COVID-19 era: a multicenter comparative study of 20,942 isolated microorganisms from ICU patients
Authors: Khavandegar Armin , Siami Zeinab , Rasouli Aziz , Nazemi Pershang , Gull Anoosha 
Published: February 2025

BackgroundHealthcare-associate infection (HAI) has been one of the health care issues worldwide. During the COVID-19 pandemic, HAI prevention was considered a vital aspect of the clinical management of COVID-19. In the present study, we aimed to compare the frequency of HAIs in ICU-admitted cases within and before the COVID-19 era.MethodsThis multicenter retrospective study applied a descriptive-analytical approach to investigate the frequency of HAIs in the ICU departments of hospitals affiliated with Tehran University of Medical Sciences from 2017 to 2022.ResultsOverall, 14,268 cases with 20,942 isolated microorganisms were recruited for this study, with 8,289 (58.1%) of them being male and 5,975 (41.9%) being female. A total of 6,722 (47.1%) cases with 9,917 (47.4%) isolated microorganisms were documented in the pre-COVID-19 era, while 7,546 (52.9%) patients with 11,025 (52.64%) were reported in COVID-19 era. Of 14,268 patients admitted to the ICU during the study period, 9,197 (64.8%) were discharged and 5,071 died (35.5%), of which 1,970 (29.3%) occurred in pre-COVID and 4,752 (70.7%) in the COVID-19 era (p-value &lt; 0.001). Klebsiella species, Acinetobacter species, Escherichia coli, Staphylococcus species, and Pseudomonas aeruginosa were the five most frequent isolated microorganisms, reported in 5,542 (26.50%), 4,171 (19.90%), 2,651 (12.70%), 2,537 (12.10%), and 1,851 (8.80%) cultures, respectively. VAEs were the most common infection types as reported in 3,562 (25%) patients. There was a statistically significant difference in UTI, PMEU, BSI, and others, with an increase in PMEUs (13.5% vs. 17.1%) and BSI (22.7% vs. 24.5%) and a decrease in UTIs (24.5% vs. 22.2%) and others (4.2% vs. 2.6%) in COVID-19 era compared to pre-COVID-19. The odds of in-hospital mortality in all six main infection categories have significantly increased in the COVID-19 era when compared to the pre-COVID-19 era. The odds of death were increased in the SSI group more than the rest (OR:2.65, CI 95%: 2.13–3.29).ConclusionCOVID-19 changed the pattern of HAIs and also increased their mortality. Overall, the findings of this study emphasize the importance of continuous monitoring and improvement of infection control measures in ICUs to reduce the incidence of HAIs and improve patient outcomes.
Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks
Authors: Zhu Yutao , Yang Qing , Fu Lingmei , Cai Chun , Wang Jinmei , He Ling 
Published: February 2025

ObjectivesThe objective was to aggregate the various scenarios that occur during nonconventional public health emergencies (NCPHEs) and analyze the evolutionary patterns of NCPHEs to better avoid risks and reduce social impacts. The aim was to enhance strategies for handling NCPHEs.Study designNews reports were crawled to obtain the scenario elements of NCPHEs and categorized into the spreading stage or derivation stage. Finally, the key scenario nodes and scenario evolution process were analyzed in combination with a corresponding emergency response assessment of each scenario by experts.MethodsDempster–Shafer (DS) theory and Bayesian networks (BNs) were applied for data reasoning, and a spread-derived coupled scenario–response theoretical model of NCPHEs for major public health emergencies was constructed. The scenario evolution path of COVID-19 was derived by combining seven types of major scenario states and corresponding emergency response measures extracted from 952 spreading scenarios.ResultsThe 26 NCPHE spread scenarios and 41 NCPHE derivation scenarios were summarized. Optimized and pessimistic NCPHE scenario pathways were generated by combining the seven major spreading scenarios to help decision makers predict the development of NCPHEs and take timely and effective emergency response measures for key scenario nodes.ConclusionThis study provides a new approach for understanding and managing NCPHEs, emphasizing the need to consider the specificity and complexity of such emergencies when developing decision-making strategies. Our contextual derivation model and emergency decision-making system provide practical tools with which to enhance NCPHE response capabilities and promote public health and safety.
The impact of economic burden of disease on poverty among young migrant workers: evidence from China
Authors: Chen Yiyan , Yan Yueping , Chen Lijun 
Published: February 2025

IntroductionThe treatment cost expenditure for family members with illness is a significant factor exacerbating poverty. Using nationally representative data concerning the migrant population, this study analyzes the impact of the economic burden from family members’ illness on poverty among young migrant workers.MethodsFirstly, we construct a multidimensional poverty index system based on five dimensions: income, education, employment, health, and livelihood,and used the A-F method for calculation. Moreover, diverging from existing studies that objectively measure the economic burden of disease, we explore an evaluation method based on subjective perceptions.ResultsThe incidence of multidimensional poverty among young migrant workers is relatively high, at 30.93%. The economic burden imposed by family members’ illnesses significantly exacerbates their risk of poverty, particularly within the 26-35 age bracket. Furthermore, compared to their male counterparts, female young migrant workers are more susceptible to the adverse effects of the economic burden of disease.DiscussionIn China, migrant workers confront numerous challenges in both their professional and personal lives, with the economic burden on their families further exacerbating their predicament. Consequently, policymakers should prioritize enhancing health insurance coverage and expanding the reach of social welfare programs to alleviate poverty and the pressures faced by young migrant workers who are the primary breadwinners.
A comparison of the acute effects of high intensity interval training and moderate intensity continuous training on working memory and emotional state in adolescent women with subthreshold depression
Authors: Yuan Shiwei , Lin Lili , Liu Libin , Zhang Xinyuan , Gu Qian 
Published: February 2025

ObjectiveVarious guidelines emphasize the cognitive and emotional benefits of physical activity. However, it is not yet clear what kind of exercise intensity is suitable for individuals with subthreshold depression. Therefore, this study aims to examine the effects of high intensity interval training (HIIT) and moderate intensity continuous training (MICT) on the working memory and emotional state.MethodsForty-nine female students with subthreshold depression (mean age 16.3 ± 0.5 yrs) completed 20-min group of sit (SIT), MICT, and HIIT on separate days in a counterbalanced order. The modified n-back task was employed to evaluate working memory. Emotional state was assessed using the Feeling Scale (FS) and Felt Arousal Scale (FAS).ResultsRegarding working memory, for accuracy, SIT (82.41 ± 13.79%), MICT (81.79 ± 13.19%) and HIIT (82.06 ± 11.36%) have no significant difference (all p &gt; 0.05). However, for reaction time, MICT (459.86 ± 131.47 ms) is significantly faster than HIIT (491.16 ± 115.68 ms) (p = 0.046), and there is no significant difference between MICT and SIT (462.71 ± 120.64 ms) (p &gt; 0.05). Concerning emotional state, for arousal, FAS scores significantly increased after both HIIT (2.39 ± 1.30 to 3.76 ± 1.12, p &lt; 0.001) and MICT (2.55 ± 0.88 to 3.94 ± 1.08, p &lt; 0.001) compared to pre-exercise, and the increase caused by them was significantly higher than that of SIT (HIIT: p = 0.011; MICT: p &lt; 0.01). For pleasure, the increase in FS score after MICT (−0.27 ± 1.13 to 1.06 ± 1.79) was significantly higher than that of SIT (0.32 ± 1.38 to 0.58 ± 1.53) (p &lt; 0.01).ConclusionAcute MICT can enhance working memory and improve the emotional state of adolescent women with subthreshold depression, while HIIT may decrease working memory and pleasure in this particular population.
Validation of the Arabic eHealth literacy questionnaire: a factor and Rasch analysis study
Authors: Al-Qerem Walid , Fadhil Osama N. , Jarab Anan , Hammad Alaa , Al-Asmari Fawaz , Zidan Rahaf , Eberhardt Judith 
Published: February 2025

IntroductionAmidst the rapid digitalization of healthcare, there is a need for tools that accurately assess eHealth literacy across cultural contexts. This study focused on the validation of an Arabic version of the eHealth Literacy Questionnaire (eHLQ), a tool to facilitate patient engagement and health outcomes in digital healthcare.MethodUsing a convenience sampling method, the study recruited a diverse sample of 657 participants from Jordan (58.9% females and 41.1% males).ResultsConfirmatory Factor Analysis and Rasch analysis supported a six-factor model and demonstrated satisfactory item performance within established thresholds. The findings revealed good internal consistency with Cronbach’s α ranging between ranging between 0.71 to 0.84. Differential Item Functioning analysis indicated no gender-specific variations.DiscussionThe validated Arabic eHLQ is a reliable tool that can help in supporting the development of tailored interventions to improve healthcare delivery in Arabic-speaking regions.
Construction of a prediction and visualization system for cognitive impairment in elderly COPD patients based on self-assigning feature weights and residual evolution model
Authors: Cheng Wenwen , Yu Chen , Liu Xiaohui 
Published: February 2025

BackgroundAssessing cognitive function in patients with chronic obstructive pulmonary disease (COPD) is crucial for ensuring treatment efficacy and avoiding moderate cognitive impairment (MCI) or dementia. We aimed to build better machine learning models and provide useful tools to provide better guidance and assistance for COPD patients' treatment and care.MethodsA total of 863 COPD patients from a local general hospital were collected and screened, and they were separated into two groups: cognitive impairment (356 patients) and cognitively normal (507 patients). The Montreal Cognitive Assessment (MoCA) was used to test cognitive function. The swarm intelligence optimization algorithm (SIOA) was used to direct feature weighting and hyperparameter optimization, which were considered simultaneous activities. A self-assigning feature weights and residual evolution (SAFWRE) algorithm was built on the concept of linear and nonlinear information fusion.ResultsThe best method in SIOA was the circle search algorithm. On the training set, SAFWRE's ROC-AUC was 0.9727, and its PR-AUC was 0.9663; on the test set, SAFWRE's receiver operating characteristic-area under curve (ROC-AUC) was 0.9243, and its precision recall-area under curve (PR-AUC) was 0.9059, and its performance was much superior than that of the control technique. In terms of external data, the classification and prediction performance of various models are comprehensively evaluated. SAFWRE has the most excellent classification performance, with ROC-AUC of 0.8865 and pr-auc of 0.8299.ConclusionThis work develops a practical visualization system based on these weight attributes which has strong application importance and promotion value.