bluuebunny/crossref_metadata_2025_split huggingface dataset:
BAM15, a mitochondrial uncoupler regulates mitochondrial function by FUNDC1 dependently in hyperglycemia
Authors: Rethineswaran Vinothkumar , Jang Woong Bi , Choi Jaewoo , Lim Hye Ji , Park Sangmi , Lee Eun Ji , Ha Jong Seong , Yun Jisoo , Kwon Sang-Mo 
Published: May 2023

Abstract
Mitochondria are intracellular organelles that regulate cell survival and death, and hyperglycemia modulates mitochondrial function in endothelial cells. In the current study, we have discovered that high glucose (HG) treatment reduces FUNDC1 (FUN14 domain containing 1) expression in endothelial cells. FUNDC1 expression in mitochondria inhibits proteasomal degradation of COX-IV, and regulates mitochondrial complexes I and IV activity and ATP synthesis. FUNDC1 depletion in HG affects mitochondrial complexes I and IV activity and ATP synthesis and promotes mitochondrial damage through loss of mitochondrial membrane potential and ROS (Reactive Oxygen Species) production. BAM15, a mitochondrial uncoupler, improves mitochondrial function and endothelial survival more effectively. Co-treatment of HG with BAM15 increased FUNDC1 protein expression, mitochondrial translocation of FUNDC1 in HG-treated cells. BAM15-induced up regulation of FUNDC1 expressions improve mitochondrial expression of COX-IV, and complex I and IV activity and ATP synthesis. Our findings propose that FUNDC1 expression in endothelial cells under hyperglycemic stress play a significant role in limiting vascular damage and apoptotic cell death.
The A allele of TERT rs13167280 improves HCC progression and prognosis in patients with chronic hepatitis B
Authors: Zhang Xin , Wang Yikai , Wu Fengping , Liu Chenrui , Hao Miao , LYU Shasha , Zhang Miaomiao , Dang Shuangsuo 
Published: May 2023

Abstract
Purpos
To study the effect of telomere reverse transcriptase (TERT) gene polymorphism on the progression of HCC.
Methods
Using several databases to analyze the correlation between TERT and clinicopathology in HCC patients, and to evaluate its prognostic significance and its correlation with immune infiltration. A cohort of 141 patients with HCC, 153 patients with cirrhosis, and 180 healthy controls was included. Gene polymorphism detection and correlation analysis were performed for TERT rs13167280.
Results
The expression of TERT was elevated in HCC, positively correlated with tumor-infiltrating immune cells, and indicated a poor prognosis. There was no difference in smoking, drinking, and heart disease history among the three groups. The biochemical indexes of the liver cirrhosis group and HCC group were significantly different from those of the control group. The proportions of the history of diabetes and hypertension in the HCC group were higher than those in the cirrhosis group. In addition, the HCC group had higher age, lower PT, and higher rGT, PTA, and AFP compared with the cirrhosis group (P < 0.001). The three groups of genotype distributions conformed to the Hardy-Weinberg equilibrium. Individuals with the GA+AA genotype had a 4.797-fold increased risk of HCC compared with GG or GA. The risk of HCC in cirrhotic patients with A allele and AA genotype was 0.601 and 0.567, respectively.
Conclusion
TERT suggests a poor prognosis for HCC, and the A allele of TERT rs13167280 can improve the progression of HCC in patients with chronic HBV infection.
“ChatGPT, can you help me save my child’s life?” - Diagnostic Accuracy and Supportive Capabilities to lay rescuers by ChatGPT in prehospital Basic Life Support and Paediatric Advanced Life Support cases – an in-silico analysis
Authors: Bushuven Stefan , Bentele Michael , Bentele Stefanie , Gerber Bianka , Bansbach Joachim , Ganter Julian , Trifunovic-Koenig Milena , Ranisch Robert 
Published: May 2023

Abstract
Background: Paediatric emergencies are challenging for healthcare workers, first aiders, and parents waiting for emergency medical services to arrive. With the expected rise of virtual assistants, people will likely seek help from such digital AI tools, especially in regions lacking emergency medical services. Large Language Models like ChatGPT proved effective in providing health-related information and are competent in medical exams but are questioned regarding patient safety. Currently, there is no information on ChatGPT’s performance in supporting parents in paediatric emergencies requiring help from emergency medical services. This study aimed to test 20 paediatric and two basic life support case vignettes for ChatGPT and GPT-4 performance and safety in children.
Methods: We provided the cases three times each to two models, ChatGPT and GPT-4, and assessed the diagnostic accuracy, emergency call advice, and the validity of advice given to parents.
Results: Both models recognized the emergency in the cases, except for septic shock and pulmonary embolism, and identified the correct diagnosis in 94%. However, ChatGPT/GPT-4reliably advised to call emergency services only in 12 of 22 cases (54%), gave correct first aid instructions in 9 cases (45%) and incorrectly advised advanced life support techniques to parents in 3 of 22 cases (13.6%).
Conclusion: Considering these results of the recent ChatGPT versions, the validity, reliability and thus safety of ChatGPT/GPT-4 as an emergency support tool is questionable. However, whether humans would perform better in the same situation is uncertain. Moreover, other studies have shown that human emergency call operators are also inaccurate, partly with worse performance than ChatGPT/GPT-4in our study.
However, one of the main limitations of the study is that we used prototypical cases, and the management may differ from urban to rural areas and between different countries, indicating the need for further evaluation of the context sensitivity and adaptability of the model. Nevertheless, ChatGPT and the new versions under development may be promising tools for assisting lay first responders, operators, and professionals in diagnosing a paediatric emergency.
Trial registration: not applicable
Succinic Acid functionalized, Silk Fibroin and Hydroxyapatite Based Scaffolds for Craniofacial Deformity Repair
Authors: Arshad Aysha , Khalid Hamad , Hameed Fareeha , Zeeshan Rabia , Mutahir Zeeshan , Akhtar Hafsah , Alhamoudi Fahad Hussain , Chaudhary Aqif Anwar , Khan Ather 
Published: May 2023

Abstract
Intricate craniofacial deformities require artificial bone grafts or scaffolds combined with adequate properties for functional restoration. To address such defects, we fabricated freeze dried silk fibroin (SF) based composite. The hydroxyapatite (HAp) was used as an additive for tunable microstructure and succinic acid (SA) was used as a novel crosslinker to modulate biodegradation rate. Mechanical properties, microstructure/porosity, degradation, swelling, and biocompatibility were examined in this study. The presence of hydroxyapatite and silk fibroin lead to increased swelling potential. The porosity of composite scaffolds was calculated 50% to 66% which considered relevant for cell adhesion and proliferation properties of composites. The in vitro cell viability assay concluded no cytotoxic effects. The viability results illustrated that the presence of both HA and silk govern higher percentage viability. The presence of ZnO was observed as a potent instigator of osteoblast proliferation and mineralization, hence promoting bone healing processes. The live dead assay also supported the findings that the composite scaffolds serve as matrices that promote osteogenic differentiation potential and support cell growth. Conclusively, the fabricated novel composite scaffolds possess all the potential characteristics that could be used promisingly for repair and regeneration of craniofacial deformities.
Integrating Radiosensitivity Gene Signature Improves Prostate Cancer Outcome Prediction
Authors: Wu Qi-Qiao , Zheng Ting-Ting , Jiang Tao , Chen Bin , Wang Xin-Yue , Yin Zhao-Sheng 
Published: May 2023

Abstract
Background This study aimed to establish a nomogram that combine 31-gene signature (31-GS), radiosensitivity index (RSI) and radiation resistance related gene index (RRRI) for predicting recurrence and in prostate cancer (PCa) patients.Methods The transcriptome data of PCa were obtained from GEO and TCGA to validate the predictive potential of three sets of published biomarkers, the 31-GS, RSI and RRRI. To adjust these markers for the characteristics of prostate cancer, we integrated four new PCa-associated radiosensitivity predictive indexes based on 31-GS, RSI and RRRI by the Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. A time-dependent receiver operating characteristic (ROC) curve, decision curve analyses (DCA), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to compare the radiosensitivity predictive ability of these four gene signatures. a nomogram was built to improve the recurrence prediction capability.Results We validated and compared the predictive potential of two published predictive indexes. Based on the 31-GS, RSI and RRRI, we integrated four PCa-associated radiosensitivity predictive indexes: 14Genes, RSI, RRRI, 20Genes. Among them, a 14-gene radiosensitivity predictive index showed the most promising predictive performance and discriminative capacity. The area under receiver operating characteristic curve for 14-gene is the highest in both TCGA and GSE cohort.Conclusions This study successfully established a Radiosensitivity related nomogram which had an excellent performance in predicting recurrence in patients with PCa. For patient who received radiation therapy, 20Genes and RRRI model can be used in predicting RFS while 20Genes is more radiotherapy-specific but needs further external validation.
Formal Verification of Cloud Scaling Policies: A Comparative Study using Markov Decision Process and Discrete-Time Markov Chain
Authors: Jawaddi Siti Nuraishah Agos , Hatta Muhammad Nur Haziq Mohammad , Kamarulzaman Anis Faqihah , Ismail Azlan 
Published: May 2023

Abstract
Cloud scaling plays a critical role in fulfilling the resource requirements of web-based enterprises. Nevertheless, current autoscaler implementations primarily operate reactively, triggering scaling actions based on predetermined thresholds. This approach often leads to erroneous decisions during peak hours, resulting in resource waste, energy consumption, performance degradation, and QoS violations. To overcome these challenges, we propose a formal verification approach utilizing probabilistic model checking, specifically Markov Decision Process (MDP) and discrete-time Markov Chain (DTMC), for analyzing the cloud scaling process. In this investigation, we compare the insights obtained from evaluating MDP and DTMC models for cloud scaling based on four key metrics: latency violation, CPU utilization, response time, and RAM capacity. To quantify probabilities and verify cloud scaling objectives, we employ Probabilistic Computation Tree Logic (PCTL). Experimental evaluations were conducted to assess the performance of the formalized cloud scaling process. The results demonstrate that the non-deterministic scaling behaviors in MDP models effectively reduce extreme-provisioning events compared to DTMC, which lacks the non-determinism aspect. Moreover, the non-deterministic characteristic enables MDP models to exhibit varying levels of accuracy when tested with different sample sizes. In contrast, DTMC, which relies solely on probability-based state transitions, maintains its accuracy in capturing the scaling behavior regardless of sample sizes. Our contributions encompass a formalization approach for the cloud scaling process, considering both deterministic and non-deterministic scaling actions. We present experimental results comparing MDP-based and DTMC-based cloud scaling processes, along with model accuracy results based on CPU utilization, response time, and RAM capacity. By addressing gaps in the existing literature, our study offers valuable perspectives and insights into the analysis of the cloud scaling process.
Manually-established abnormal karyotype dataset based on normal chromosomes effectively train artificial intelligence model for better cytogenetic abnormalities prediction
Authors: Deng Jinhai , Peng Weixiong , Lu Qinyang , Wang Zheng , Fu Qiang , Zhou Xingang , Cai Yufeng , Mu Yang , Pan Teng , Liu Zaoqu , Cai Zixing , Yin Mingzhu , Liu Lijue , Lai Yueyun 
Published: May 2023

Abstract
With the advent of the utilization of machine learning techniques in the diagnosis of hematological diseases, endless potential can be foreseen, including digital images analysis. The application of machine-learning tool in cytogenetics contributes to the lightening of manpower burden, the improvement of recognition efficiency and the enrichment of cytogenetic maps, which paves the way for the development of digital pathology. Chromosome banding analysis is an essential technique for chromosome karyotyping, which comprises of one of important tools for the diagnostics in hematological malignancies. Its important role has been emphasized in clinic for dozens of years till now. The recognition of abnormal karyotypes is indispensable for disease classification and even diagnosis. However, a lack of abnormal karyotype images as reference dataset restricts its utilization in clinic, especially for uncommon hematological diseases. Here, to our best knowledge, we, for the first time, successfully generated abnormal karyotype images of t(9;22)(q34;q11)manually from normal karyotype images using machine learning, providing a proof-of-concept for establishing abnormal karyotypes of hematological malignancies as clinical reference. Moreover, to verify the reliability of generated abnormal dataset, artificial intelligence (AI)-recognizing models were further established based on ‘manually-built’ karyogram dataset and real karyotype dataset, respectively. The results showed that there was no difference between ‘manually-built’ karyotype dataset derived AI model (model-M) and real karyotype dataset derived AI model (model-R) regarding the recognition of t(9;22)(q34;q11) abnormality, with model-M (AUC=0.984, 95%CI 0.98-0.988) versus model-R (AUC=0.988, 95%CI 0.984-0.993) (p>0.05), which pointed out that our generated abnormal karyotype images were comparable to real images to assist the establishment of AI-recognising models. Collectively, our work demonstrates the potential application of machine learning in generating unlimited dataset from limited sources, helping to overcome the big challenge of AI in healthcare.
The impact of treated eave ribbons in reducing malaria transmission; A mathematical modelling perspective
Authors: Nambunga Ismail H. , Shirima Gloria G. , Mbarawa Asiya , Ferguson Heather M. , Okumu Fredros O. , Viana Mafalda , Kiware Samson S. 
Published: May 2023

Abstract

BackgroundDespite significant progress against malaria, the use of two core interventions, namely insecticide-treated nets (ITNs) and indoor residual spraying (IRS), are becoming increasingly vulnerable due to insecticide resistance and outdoor biting by mosquitoes. One representative example is Kilombero Valley in Tanzania where transmission continues despite over 80% of the population using ITNs. Further progress in this and similar African settings will require identifying which supplementary tools combine most effectively with ITNs to reduce mosquito exposure.MethodsUsing the Kilombero Valley as a case study, the Vector Control Optimization Model (VCOM) was adapted and extended to simulate the impact of adding eave ribbons treated with spatial repellent (ER) as supplementary intervention in an area of high ITN coverage. Simulation was conducted to assess the impact of varying coverage of this supplementary intervention on the entomological inoculation rates (EIR) generated by two common vectors in Kilombero,Anopheles arabiensisandAnopheles funestus. Finally, the impact of introducing this intervention on the combined EIR fromAn. arabiensisandAn. funestuswas assessed to identify scenarios in which values fell below 1; the likely threshold required for malaria interruption.ResultsER was predicted to substantially reduce the EIR in Kilombero valley when combined with 80% ITN coverage. However, the nature of the impact varied notably between vector species. ER was predicted to have a much larger effect on transmission mediated byAn. funestusthanAn. arabiensis. Additionally, in the situation where EIR from bothAn. arabiensisandAn. funestuswas combined, substantial coverage of this supplementary intervention was predicted to lower EIR to below one.ConclusionDespite the significant impact of ER in combination with ITNs on one of the two vectors (An. funestusorAn. arabiensis), this intervention is insufficient when combined with ITNs to reduce the EIR to below one in settings like Kilombero Valley where both species contribute to malaria transmission.
Screening, identification and pigment characteristics of actinomycin D-producing actinomycetes from Purple soil in Sichuan Basin
Authors: Wan Xin , Liu Rui , Jiang Peng , Li LiHuan , Chen JingPing , Wei Hongfu , Liu Mingxue 
Published: May 2023

Abstract
Background
Natural pigments from microbial sources is a type of compounds with various structures and a wide range of uses, which is already an important source of antibiotic production.
Results
In this research, a yellow pigment-producing actinomycete was screened from purple soil in Sichuan Basin, PRC. According to the morphological, physiological and biochemical characteristics and 16s rDNA molecular sequence, the strain LS-2 was identified as Streptomyces parvulusand named as LS-2. The pigment was purified by column chromatography and showed excellent antibacterial activity against Escherichia coli (G-) and Staphylococcus aureus (G+). Through the analysis of UV-vis absorption spectrum, infrared absorption spectrum (IR) and liquid chromatography-mass spectrometry (LC-MS) , the yellow pigment was identified as actinomycin D. To increase the fermentation yield of actinomycin D, the factors affecting the fermentation system were optimized, such as basic culture medium, culture temperature, culture pH, and inoculation amount. It was found that 14% inoculum was the optimal fermentation culture system in Gause’s synthetic medium of pH=6.5 at 34 ℃.
Conclusions
In this research, a yellow pigment-producing strain was screened from purple soil in Sichuan Basin, PRC. Based on the results of molecular sequencing and physiological characteristics analysis, strain LS-2 was identified as Streptomyces parvulus, which is likely to be a new strain that has not been published. The fermentation production was purified by column chromatography, and the yield of pigment was about 540 mg/L. The results of spectral analysis showed that the yellow pigment produced by the strain was actinomycin D, and itshowed excellent and extensive antibacterial activity against Staphylococcus aureus (G+) and Escherichia coli(G-).
Coating of SnO2 -NiO nanoparticles with ultrathin graphite nanosheets as a high-performance anode material for lithium-ion batteries
Authors: Ye Wenbin , Lei Jinxuan , Jiang Chaokui , Feng Zuyong , Xiong Deping , He Miao 
Published: May 2023

Abstract
The lithium-ion battery anodes have always sought out the best possible properties with regards to large capacity, high rate, as well as long-term cycling stability. For this work, a straightforward hydrothermal and high-speed ball mill procedure was employed to create the SnO2-NiO-C anode material. Ion cycling and embedding are ideal for NiO nanoparticles with a unique hexagonal crystal structure, which can stabilize the structure and prevent SnO2 from becoming coarser. The graphite encapsulated in the outer layer can effectively prevent volume expansion during the cycle as well. According to the findings, the SnO2-NiO-C composite exhibits a significant reversible capacity of 1224.3 mAh g− 1 after 300 cycles at 0.2 A g− 1 and from the fourth cycle onwards, the Cullen efficiency remains above 97%. And it also possesses a long-term cycling stability of 820.1 mAh g− 1 after 1000 cycles at 1.0 A g− 1. Also, a significant rate property can reach 507.1 mAh g− 1 at 5.0 A g− 1. Therefore, the SnO2-NiO-C anode material for Li-ion batteries is promising on account of its excellent electrochemical performance.
Factors pertaining to road traffic injuries; a systematic scoping review and meta-analysis
Authors: Mohammadi Esmaeil , Rashidi Mohammad-Mahdi , Koolaji Sogol , Azadnajafabad Sina , Rezaei Negar , Abbasi-Kangevari Mohsen , Ghamari Hadi , Shabanan Sedigheh Hosseini , Rezaei Nazila , Djalalinia Shirin , Farzadfar Farshad 
Published: May 2023

Abstract
Background
Many factors have been associated with road traffic injuries (RTI) while no study has cumulatively gathered and pooled them.
Methods
A comprehensive search was carried out in PubMed, World of Sciences, and Scopus based on predefined keywords. Two independent reviewers performed screening the search findings and data extraction procedure. Risk of bias was checked based on the Newcastle–Ottawa Scale. Odds ratios (OR) were extracted and pooled by meta-analysis to reach the overall effect.
Results
In all, 34 studies were included that summed 277,943 individuals, reporting at least one factor pertaining to RTI. The factors related to an increased rate of RTIs (OR 1.49, 95% confidence interval 1.35–1.64). Based on the included publications, factors could be grouped as alcohol consumption (1.74, 1.32–2.30), experienced driving and self-confidence (106, 0.94–1.20), seatbelt fastening incompliance (1.45, 1.39–1.51), driving in poor roads and rural areas (1.31, 1.03–1.42), lower education level (1.30, 1.17–1.44), lower income (1.23, 1.13–1.33), malfunctioned vehicle (1.77, 1.52–2.05), and driving with psychological tensions (1.20, 1.11–1.30).
Conclusion
Almost all the discovered factors in this study were among the modifiable factors that highlight the need for preventive and debarment measures.
Psychometric Assessment of an Adapted Social Provisions Survey in a Sample of Adults with Prediabetes
Authors: Wilson Kathryn E. , Michaud Tzeyu L. , Sweet Cynthia Castro , Katula Jeffrey A. , Almeida Fabio A. , Brito Fabiana A. , Schwab Robert , Estabrooks Paul A. 
Published: May 2023

Abstract
Background: The relevance of social support for weight management is not well documented in people with prediabetes. An important consideration is the adequate assessment of social provisions related to weight management in this population.
Purpose: To assess the factor structure and measurement invariance of an adapted Social Provisions Scale specific to weight management (SPS-WM).
Methods: Participants of a diabetes prevention trial (n=599) completed a demographic survey, and the SPS-WM. Confirmatory analyses tested the factor structure of the SPS-WM, and measurement invariance was assessed for gender, weight status, education level, and age.
Results: Removal of two collinear items resulted in acceptable model fit, supporting six correlated factors for social provisions specific to weight management. Measurement invariance was supported across all subgroups.
Conclusion: Results support score interpretations for these scales reflecting distinct components of social support specific to weight management in alignment with those of the original survey.