bluuebunny/crossref_metadata_2025_split huggingface dataset:
A prediction model based on artificial intelligence techniques for disintegration time and hardness of fast disintegrating tablets in pre-formulation tests
Authors: Momeni Mehri , Afkanpour Marziyeh , Rakhshani Saleh , Mehrabian Amin , Tabesh Hamed 
Published: March 2024

Abstract
Background
The pharmaceutical industry is continually striving to innovate drug development and formulation processes. Orally disintegrating tablets (ODTs) have gained popularity due to their quick release and patient-friendly characteristics. The choice of excipients in tablet formulations plays a critical role in ensuring product quality, highlighting its importance in tablet creation. The traditional trial-and-error approach to this process is both expensive and time-intensive. To tackle these obstacles, we introduce a fresh approach leveraging machine learning and deep learning methods to automate and enhance pre-formulation drug design.

Methods
We collected a comprehensive dataset of 1983 formulations, including excipient names, quantities, active ingredient details, and various physicochemical attributes. Our study focused on predicting two critical control test parameters: tablet disintegration time and hardness. We compared a range of models like deep learning, artificial neural networks, support vector machines, decision trees, multiple linear regression, and random forests.

Results
A 12-layer deep neural network, as a form of deep learning, surpassed alternative techniques by achieving 73% accuracy for disintegration time and 99% for tablet hardness. This success underscores its efficacy in predicting complex pharmaceutical factors. Such an approach streamlines the drug formulation process, reducing iterations and material consumption.

Conclusions
Our findings highlight the deep learning potential in pharmaceutical formulations, particularly for tablet hardness prediction. Future work should focus on enlarging the dataset to improve model effectiveness and extend its application in pharmaceutical product development and assessment.
Health characteristics and factors associated with transition shock in newly graduated registered nurses: a latent class analysis
Authors: Wang Pan , Zhou Juan , Shen Xin , Ge Yaping , LI Yanran , Ge Hui , LI Shuwen 
Published: March 2024

Abstract
Background
Transition shock occurs at a vulnerable time in newly graduated registered nurses’ careers and has a clear impact on both newly graduated registered nurses’ productivity and patient recovery outcomes. Identifying classification features of transition shock and targeting interventions to support newly graduated registered nurses is imperative. The study aimed to explore potential transition shock subgroups of newly graduated registered nurses and further explore the impact of population characteristics and two indices of health on transition shock.

Methods
A descriptive, cross-sectional design was conducted. An online questionnaire was sent via WeChat to newly graduated registered nurses who started work in 2021 at seven hospitals between August and November 2021, and 331 nurses filled out the questionnaire. Latent class analysis was used to identify the potential class of the transition shock of newly graduated registered nurses, and multinomial logistic regression analyses were used to determine the factors of potential classification.

Results
The study identified four classes of transition shock in newly graduated registered nurses, namely, “high transition shock”, “physical fatigue-lack of knowledge”, “development adaptation” and “low transition shock-worry” groups. Newly graduated registered nurses who urinated less than 4 times per day (OR = 0.051, 95% CI = 0.005–0.502) were likely to be in the “high transition shock” group. Newly graduated registered nurses who did not delay urination (OR = 4.267, 95% CI = 1.162–11.236) were more likely to belong to the “low transition shock-worry” group. Newly graduated registered nurses without sleep disturbance were more likely to be in the “physical fatigue - lack of knowledge” (OR = 3.109, 95% CI = 1.283–7.532), “development adaptation” (OR = 8.183, 95% CI = 2.447–27.066), and “low transition shock-worry” (OR = 8.749, 95% CI = 1.619–47.288) groups than in the ‘high transition shock’ group.

Conclusions
This study highlights potential patterns of transition shock among newly graduated registered nurses. Two indices of health, namely, delayed urination and sleep disturbance, can predict the subgroups of newly graduated registered nurses with transition shock.
Nurses’ perceptions, experience and knowledge regarding artificial intelligence: results from a cross-sectional online survey in Germany
Authors: Sommer Domenic , Schmidbauer Lukas , Wahl Florian 
Published: March 2024

Abstract
Background
Nursing faces increasing pressure due to changing demographics and a shortage of skilled workers. Artificial intelligence (AI) offers an opportunity to relieve nurses and reduce pressure. The perception of AI by nurses is crucial for successful implementation. Due to a limited research state, our study aims to investigate nurses’ knowledge and perceptions of AI.

Methods
In June 2023, we conducted a cross-sectional online survey of nurses in Bavaria, Germany. A convenience sample via care facilities was used for the questionnaire oriented on existing AI surveys. Data analysis was performed descriptively, and we used a template analysis to evaluate free-text answers.

Results
114 (♀67.5 %, ♂32.5 %) nurses participated. Results show that knowledge about AI is limited, as only 25.2 % can be described as AI experts. German nurses strongly associate AI with (i) computers and hardware, (ii) programming-based software, (iii) a database tool, (iv) learning, and (v) making decisions. Two-thirds of nurses report AI as an opportunity. Concerns arise as AI is seen as uncontrollable or threat. Administration staff are seen as the biggest profiteers.

Conclusion
Even though there is a lack of clear understanding of AI technology among nurses, the majority recognizes the benefits that AI can bring in terms of relief or support. We suggest that nurses should be better prepared for AI in the future, e.g., through training and continuing education measures. Nurses are the working group that uses AI and are crucial for implementing nursing AI.
Drivers of vulnerability to medicine smuggling and combat strategies: a qualitative study based on online news media analysis in Iran
Authors: Fakhrzad NourolHoda , Yazdi-Feyzabadi Vahid , Fakhrzad Maryam 
Published: March 2024

AbstractBackgroundMedicine smuggling poses a serious public health threat, limiting patients’ safe and timely access to this essential resource. Thus, this study aims to identify the factors contributing to the vulnerability to medicine smuggling and propose effective strategies to combat this issue in Iran.MethodsAn analysis of news media was conducted using qualitative content analysis. News text items related to medicine smuggling were retrieved from various online news sources between March 21, 2017, and May 21, 2023. To select health-oriented and general online news stations, news agencies, and newspapers, the purposeful sampling method with a maximum variation strategy was used. The selected sources included Mehr News Agency, Khabar Online, Islamic Consultative Assembly News Agency (ICANA), Islamic Republic News Agency (IRNA), Iranian Students News Agency (ISNA), Hamshahri, Donya-e-Eqtesad newspapers, Webda, Sepid Online, and Iran’s Food and Drug Administration News Agency (IFDANA). All data coding was manually done using Microsoft Excel software version 2016.ResultsA total of 277 news articles were found to meet the established criteria for inclusion. The analysis revealed four main themes, each with several sub-themes, that shed light on the factors that drive vulnerability and the strategies to combat medicine smuggling. These themes are the economic environment, government and stewardship, information technology systems, and socio-cultural factors. The economic environment emerged as the most significant theme, encompassing medicine selection, reimbursement, and procurement, all of which affect the smuggling of pharmaceuticals in Iran.ConclusionTo combat medicine smuggling, it is important to adjust policies based on the identified vulnerabilities. Effective strategies to reverse pharmaceutical smuggling include capacity building of pharmaceutical manufacturing companies, implementing regulated and enhanced supervisory and rulemaking policies, strengthening health insurance, improving e-infrastructure, and increasing public awareness through collaborative approaches involving various stakeholders within and outside the health system.
Barriers to proper maternal referral system in selected health facilities in Eastern Ethiopia: a qualitative study
Authors: Mengist Betelhem , Semahegn Agumasie , Yibabie Shegaye , Amsalu Bezabih , Tura Abera Kenay 
Published: March 2024

Abstract
Background
Appropriate maternal referral system plays an essential role in curbing maternal mortality. Although the occurrence of obstetric complications is often unpredictable, addressing bottlenecks of the referral system is crucial to facilitate the women to have access to timely lifesaving interventions. Nonetheless, little is known about the barriers to maternal referral system in the eastern Ethiopia. Therefore, this study aimed to explore the barriers to maternal referral system at selected referral hospitals in eastern Ethiopia.

Methods
Key informant interviews and in-depth interviews were conducted among purposively selected respondents who had a role in maternal referral processes. A total of 12 key informants that comprised of liaison officers, healthcare providers and three in-depth interviews with referred women were conducted. Semi-structured interview guide was developed and used to facilitate the interviews. All the interviews were tape recorded, complemented by note taking. Then audio recorded interviews were transcribed as per verbatim and imported to NVivo for coding and merging. The data were thematically synthesized.

Results
The study identified a range of barriers that affect the maternal referral system in Eastern Ethiopia. The main barriers are grouped into three domains, such as: communication, transportation, and healthcare system. The most commonly reported barriers were lack of pre-referral communication and feedback, using informal communication, incomplete referral forms, poor ambulance service including misuse of ambulances, lack of skilled healthcare escort and lack of medical equipment at emergency, unnecessary self-referrals, poor referral skills and limited number of health professions.

Conclusions
The maternal referral system is overwhelmingly affected by lack of skill, logistics (referral form), misuse of available ambulance, poor communication, and limited seeking of feedback. Regular consultative meeting with relevant stakeholders and uptake of feedback are crucial to improve referral communication, proper use of ambulance and building capacity of health workforce about referral are essential to improve maternal referral system.
Green fabrication of ZnO nanoparticles via spirulina platensis and its efficiency against biofilm forming pathogens
Authors: Ahmed Nashwa A. , Othman Amal S. 
Published: March 2024

AbstractExcessive consumption of antibiotics is considered one of the top public health threats, this necessitates the development of new compounds that can hamper the spread of infections. A facile green technology for the biosynthesis of Zinc oxide nanoparticles (ZnO NPs) using the methanol extract of Spirulina platensis as a reducing and stabilizing agent has been developed. A bunch of spectroscopic and microscopic investigations confirmed the biogenic generation of nano-scaled ZnO with a mean size of 19.103 ± 5.66 nm. The prepared ZnO NPs were scrutinized for their antibacterial and antibiofilm potentiality, the inhibition zone diameters ranged from 12.57 ± 0.006 mm to 17.33 ± 0.006 mm (at 20 µg/mL) for a variety of Gram-positive and Gram-negative pathogens, also significant eradication of the biofilms formed by Staphylococcus aureus and Klebsiella pneumoniae by 96.7% and 94.8% respectively was detected. The free radical scavenging test showed a promising antioxidant capacity of the biogenic ZnO NPs (IC50=78.35 µg/mL). Furthermore, the anti-inflammatory role detected using the HRBCs-MSM technique revealed an efficient stabilization of red blood cells in a concentration-dependent manner. In addition, the biogenic ZnO NPs have significant anticoagulant and antitumor activities as well as minimal cytotoxicity against Vero cells. Thus, this study offered green ZnO NPs that can act as a secure substitute for synthetic antimicrobials and could be applied in numerous biomedical applications.
Non-ribosomal peptide synthetase (NRPS)-encoding products and their biosynthetic logics in Fusarium
Authors: Huang Ziwei , Zhu Wangjie , Bai Yifan , Bai Xuelian , Zhang Huawei 
Published: March 2024

AbstractFungal non-ribosomal peptide synthetase (NRPS)-encoding products play a paramount role in new drug discovery. Fusarium, one of the most common filamentous fungi, is well-known for its biosynthetic potential of NRPS-type compounds with diverse structural motifs and various biological properties. With the continuous improvement and extensive application of bioinformatic tools (e.g., anti-SMASH, NCBI, UniProt), more and more biosynthetic gene clusters (BGCs) of secondary metabolites (SMs) have been identified in Fusarium strains. However, the biosynthetic logics of these SMs have not yet been well investigated till now. With the aim to increase our knowledge of the biosynthetic logics of NPRS-encoding products in Fusarium, this review firstly provides an overview of research advances in elucidating their biosynthetic pathways.
Characterization of the biological and transcriptomic landscapes of bone marrow-derived mesenchymal stem cells in patients with multiple myeloma
Authors: Lu Yu , Zheng Chaohui , Zhang Wenxia , Liu Xuan , Zhou Ziwei , Wang Zhenzhen , Hua Huan , Song Zhengrong , Zhang Xuejun , Liu Shuyi , Zhang Leisheng , Wang Fuxu 
Published: March 2024

Abstract
Background
Mesenchymal stem/stromal cells (MSCs) have been acknowledged as the most important stromal cells in the bone marrow (BM) microenvironment for physiologic hematopoiesis and the concomitant hematologic malignancies. However, the systematic and detailed dissection of the biological and transcriptomic signatures of BM-MSCs in multiple myeloma (MM) are largely unknown.

Methods
In this study, we isolated and identified BM-MSCs from 10 primary MM patients and 10 healthy donors (HD). On the one hand, we compared the multifaceted biological characteristics of the indicated two BM-MSCs, including biomarker expression pattern, multilineage differentiation potential, stemness and karyotyping, together with the cellular vitality and immunosuppressive property. On the other hand, we took advantage of RNA-SEQ and bioinformatics analysis to verify the similarities and differences at the transcriptomic level between MM-MSCs and HD-MSCs.

Results
As to biological phenotypes and biofunctions, MM-MSCs revealed conservation in immunophenotype, stemness and differentiation towards adipocytes and chondrocytes with HD-MSCs, whereas with impaired osteogenic differentiation potential, cellular vitality and immunosuppressive property. As to transcriptomic properties, MM-MSCs revealed multidimensional alterations in gene expression profiling and genetic variations.

Conclusions
Overall, our date systematic and detailed reflected the multifaceted similarities and variations between MM-MSCs and HD-MSCs both at the cellular and molecular levels, and in particular, the alterations of immunomodulation and cellular viability of MM-MSCs, which wound benefit the further exploration of the pathogenesis and new drug application (NDA) of multiple myeloma from the view of BM-MSCs.
An evaluation of LLIN physical integrity and population attitudes towards net use, care and handling during the Magude project in southern Mozambique
Authors: Alafo Celso , Montoya Lucia Fernandez , Martí-Soler Helena , Máquina Mara , Malheia Arlindo , Sacoor Charfudin , Abílio Ana Paula , Marrenjo Dulcisaria , Cuamba Nelson , Galatas Beatriz , Aide Pedro , Saúte Francisco , Paaijmans Krijn P. 
Published: March 2024

Abstract
Background
The Magude Project assessed the feasibility of eliminating malaria in Magude district, a low transmission setting in southern Mozambique, using a package of interventions, including long-lasting insecticidal nets (LLINs). As the efficacy of LLINs depends in part on their physical integrity, this metric was quantified for Olyset® Nets post mass-distribution, in addition to net use, care and handling practices and other risk factors associated with net physical integrity.

Methods
Nets were collected during a cross-sectional net evaluation, nine months after the Magude project commenced, which was 2 years after the nets were distributed by the National Malaria Control Programme (NMCP). The physical integrity of the nets was assessed by counting and sizing the holes at different positions on each net. A structured questionnaire was administered to assess how the selected net was used and treated (care, wash and repair). Net bio-efficacy was assessed following the standard World Health Organization (WHO) cone bioassay procedures.

Results
Out of the 170 Olyset® Nets included in the analysis, 63.5% had been used the night before. The main reason for not using a net was the notion that there were no mosquitoes present. The average number of people using each net was 1.79. Two thirds of the nets had only been washed once or twice since distribution. Most nets (80.9%) were holed and 18% were torn, but none of the risk factors were significantly associated with net integrity, except for presence of mice in the household. Less than half of the participants noticed holes in holed nets, and of those only 38.6% attempted to repair those. None of the six nets that were tested for bio-efficacy passed the WHO threshold of 80% mosquito mortality.

Conclusion
Overall the majority of Olyset® Nets were in serviceable condition two years post-distribution, but their insecticidal effect may have been lost. This study—together with previous evidence on suboptimal access to and use of LLINs in Magude district—highlights that LLINs as an intervention could have been optimized during the Magude project to achieve maximum intervention impact.
Characterizing and forecasting neoantigens-resulting from MUC mutations in COAD
Authors: Chen Min , Zhang Xin , Ming Zihe , Lingyu  , Feng Xiaorong , Han Zhenguo , An Han-Xiang 
Published: March 2024

Abstract
Background
The treatment for colon adenocarcinoma (COAD) faces challenges in terms of immunotherapy effectiveness due to multiple factors. Because of the high tumor specificity and immunogenicity, neoantigen has been considered a pivotal target for cancer immunotherapy. Therefore, this study aims to identify and predict the potential tumor antigens of MUC somatic mutations (MUCmut) in COAD.

Methods
Three databases of TCGA, TIMER2.0, and cBioPortal were used for a detailed evaluation of the association between MUCmut and multi-factors like tumor mutation burden (TMB), microsatellite instability (MSI), prognosis, and the tumor microenvironment within the context of total 2242 COAD patients. Next, TSNAdb and the differential agretopicity index (DAI) were utilized to predict high-confidence neopeptides for MUCmut based on 531 COAD patients’ genomic information. DAI was calculated by subtraction of its predicted HLA binding affinity of the MUCmut peptide from the corresponding wild-type peptide.

Results
The top six mutation frequencies (14 to 2.9%) were from MUC16, MUC17, MUC5B, MUC2, MUC4 and MUC6. COAD patients with MUC16 and MUC4 mutations had longer DFS and PFS. However, patients with MUC13 and MUC20 mutations had shorter OS. Patients with the mutation of MUC16, MUC5B, MUC2, MUC4, and MUC6 exhibited higher TMB and MSI. Moreover, these mutations from the MUC family were associated with the infiltration of diverse lymphocyte cells and the expression of immune checkpoint genes. Through TSNAdb 1.0/NetMHCpan v2.8, 452 single nucleotide variants (SNVs) of MUCmut peptides were identified. Moreover, through TSNAdb2.0/NetMHCpan v4.0, 57 SNVs, 1 Q-frame shift (TS), and 157 short insertions/deletions (INDELs) of MUCmut were identified. Finally, 10 high-confidence neopeptides of MUCmut were predicted by DAI.

Conclusions
Together, our findings establish the immunogenicity and therapeutic potential of mutant MUC family-derived neoantigens. Through combining the tools of TSNAdb and DAI, a group of novel MUCmut neoantigens were identified as potential targets for immunotherapy.
Cognitive decline, Aβ pathology, and blood–brain barrier function in aged 5xFAD mice
Authors: Nehra Geetika , Promsan Sasivimon , Yubolphan Ruedeemars , Chumboatong Wijitra , Vivithanaporn Pornpun , Maloney Bryan J. , Lungkaphin Anusorn , Bauer Bjoern , Hartz Anika M. S. 
Published: March 2024

AbstractBackgroundPatients with Alzheimer's disease (AD) develop blood–brain barrier dysfunction to varying degrees. How aging impacts Aβ pathology, blood–brain barrier function, and cognitive decline in AD remains largely unknown. In this study, we used 5xFAD mice to investigate changes in Aβ levels, barrier function, and cognitive decline over time.Methods5xFAD and wild-type (WT) mice were aged between 9.5 and 15.5 months and tested for spatial learning and reference memory with the Morris Water Maze (MWM). After behavior testing, mice were implanted with acute cranial windows and intravenously injected with fluorescent-labeled dextrans to assess their in vivo distribution in the brain by two-photon microscopy. Images were processed and segmented to obtain intravascular intensity, extravascular intensity, and vessel diameters as a measure of barrier integrity. Mice were sacrificed after in vivo imaging to isolate brain and plasma for measuring Aβ levels. The effect of age and genotype were evaluated for each assay using generalized or cumulative-linked logistic mixed-level modeling and model selection by Akaike Information Criterion (AICc). Pairwise comparisons were used to identify outcome differences between the two groups.Results5xFAD mice displayed spatial memory deficits compared to age-matched WT mice in the MWM assay, which worsened with age. Memory impairment was evident in 5xFAD mice by 2–threefold higher escape latencies, twofold greater cumulative distances until they reach the platform, and twice as frequent use of repetitive search strategies in the pool when compared with age-matched WT mice. Presence of therd1allele worsened MWM performance in 5xFAD mice at all ages but did not alter the rate of learning or probe trial outcomes. 9.5-month-old 15.5-month-old 5xFAD mice had twofold higher brain Aβ40and Aβ42levels (p < 0.001) and 2.5-fold higher (p = 0.007) plasma Aβ40levels compared to 9.5-month-old 5xFAD mice. Image analysis showed that vessel diameters and intra- and extravascular dextran intensities were not significantly different in 9.5- and 15.5-month-old 5xFAD mice compared to age-matched WT mice.Conclusion5xFAD mice continue to develop spatial memory deficits and increased Aβ brain levels while aging. Given in vivo MP imaging limitations, further investigation with smaller molecular weight markers combined with advanced imaging techniques would be needed to reliably assess subtle differences in barrier integrity in aged mice.