bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Review on Graph Neural Networks for Predicting Synergistic Drug Combinations
Authors: Besharatifard Milad , Vafaee Fatemeh 
Published: September 2023

Abstract
Combinational therapies with synergistic effects provide a powerful treatment strategy for tackling complex diseases, particularly malignancies. Discovering these synergistic combinations, often involving various compounds and structures, necessitates exploring a vast array of compound pairings. However, practical constraints such as cost, feasibility, and complexity hinder exhaustive in vivo and in vitro experimentation. In recent years, machine learning methods have made significant inroads in pharmacology. Among these, Graph Neural Networks (GNNs) have gained increasing attention in drug discovery due to their ability to represent complex molecular structures as networks, capture vital structural information, and seamlessly handle diverse data types. This review aims to provide a comprehensive overview of various GNN models developed for predicting effective drug combinations, examining the limitations and strengths of different models, and comparing their predictive performance. Additionally, we discuss the databases used for drug synergism prediction and the extraction of drug-related information as predictive features. By summarizing the state-of-the-art GNN-driven drug combination prediction, this review aims to offer valuable insights into the promising field of computational pharmacotherapy.
Purification of ionic liquid stable Aspergillus assiutensis VS34 cellulase, and generation of nanobiocatalysts for potential biomass conversion to biofuel
Authors: Sharma Vishal , Nargotra Parushi , Sharma Surbhi , Bangotra Ridhika , Bajaj Monika , Kapoor Nisha , Mahajan Ritu , Singh Akhlash P , Bajaj Bijender Kumar 
Published: September 2023

Abstract
Ionic liquids (ILs) have gained immense attention as eco-friendly solvents for pretreatment of lignocellulosics for their potential bioconversion to biofuels, bio-chemicals, and other products. However, for saccharification of IL-pretreated biomass IL-stable cellulases are desired. IL-stable cellulase and xylanase enzyme preparation developed from a previously isolated Aspergillus assiutensis VS34 was used for saccharification of IL-pretreated biomass. Current study reports the purification of IL-stable cellulase (CMCase) from A. assiutensis VS34 based on salt precipitation and ion exchange chromatography. Functionality of the purified cellulase (2.10-fold) was observed by native-PAGE and zymography, and the molecular weight (27 kDa) was assayed by SDS-PAGE. Though optimum temperature and pH of CMCase was 50℃ and 6.0, respectively, but the enzyme showed considerable activity and stability over a wide range of temperature (40–80℃, 72–99%) and pH (3–11, 60–95%). The activity of enzymes was enhanced by certain metal ions (Ca2+, Cu2+, Mn2+, Mg2+, and Co2+), but decreased considerably with Hg2+. Km and Vmax of CMCase were 6.996 mg/ml and 16.103 µmol/min/mg, respectively. Process-apt properties of A. assiutensis VS34 CMCase reflect its application potential for a variety of processes including biomass conversion. Submerged fermentation was executed using A. assiutensis VS34 in wheat bran medium and a combined cellulase and xylanase preparation developed was acetone-concentrated. The nanobiocatalysts were prepared by immobilization of concentrated cellulase/xylanase enzyme preparation on magnetic nanoparticles (efficiency 78.04% and 58.44%, respectively), and were examined for their saccharification potential for IL-pretreated sugarcane bagasse for repeated cycles.
Habituation to threats in times of crisis: Lessons from the temporal trajectory of risk perceptions throughout COVID-19
Authors: Grillo Tito L.H. , Henderson Ty , Ward Adrian F. 
Published: September 2023

Abstract
From epidemics to wars to economic recessions, societies all around the world are subject to extended periods of crisis. Understanding public perceptions of crisis-related risks is crucial for educating people about ongoing threats and protective behaviors and developing effective protective policies during crises. However, little is known about how risk perceptions change over time. During COVID-19, for more than a year, participants of a nationwide American panel provided periodic reports of their own estimated (i.e., perceived) probabilities that they could (i) get COVID-19, (ii) be hospitalized with COVID-19, and (iii) die of COVID-19. Examining these reports of subjective risks—and controlling for objective indicators of COVID-19 threats—we found robust habituation-to-threats patterns: although respondents perceived high levels of personal risk during the early days of the pandemic, risk perceptions declined over time despite rises in objective threat indicators. In fact, the passage of time was a substantially stronger predictor of risk perceptions than objective signs that COVID-19 was becoming more dangerous. This temporal trajectory of risk perceptions could help explain fluctuations in protective behaviors throughout the COVID-19 pandemic and may have implications for managing other widespread crises in the future.
Innovation Skills Assessment: A Cross-sectional Approach to Benchmarking Innovation Potential among Employees of a Tertiary Care Hospital in Pakistan
Authors: Tahir Hasan Nawaz , Sajid Haseeb , Sulaiman Mahreen , Raheem Ahmed , Khan Irfan , Ahsan Zeeshan , Mian Asad I. 
Published: September 2023

Abstract
Background: Health innovation can play a critical role in the socio-economic development of a nation. Healthcare organizations may claim to be innovative in their implementation of clinical care, but they lack an objective low cost and easy-to-use measure of their innovation capacity. Innovation dashboarding through a relevant tool may fill that gap.
Purpose:To facilitate low-cost, low-tech, and fast-tracked innovation by profiling the following four parameters at a tertiary care hospital in Pakistan: (I) low-cost innovative idea generation; (II) risk behavior ‘(III) relationship development; and (IV) pivoting from an idea to a tangible product.
Methods: This cross-sectional descriptive study included employees from a tertiary care hospital in the southern Punjab district of Pakistan, using non-probability purposive sampling. The study tool, the Innovation Skills Assessment (ISA), is a novel questionnaire adapted from the validated General Innovation Skills Aptitude Test 2.0. The ISA has structured closed-ended questions, focusing on four pillars of innovation: Pillar I - generating ideas, Pillar II - taking calculated risks and being entrepreneurial, Pillar III - developing and maintaining interpersonal relationships, and Pillar IV- turning ideas into products, processes, and services.
Results:Stratification of the 161 participants (60% males) into various age groups revealed that individuals aged 36 to 45 years had the highest scores (mean of 4.48) across all four pillars, outperforming other age groups. Additionally, male participants scored higher than females in Pillars I to IV. Participants with education up to the high school level exhibited the highest innovation scores for Pillars I, II, and IV.
Conclusion: The ISA can assess healthcare organizational innovation capabilities to establish a baseline. The age group of 36 to 45 emerges as a pivotal period for fostering a healthcare innovation-driven culture in LMICs like Pakistan. The ISA's insights may guide tailored strategies, driving impactful health innovation globally.
MESH TERMS: Hospital Innovation, creativity, entrepreneurship, innovation dashboarding, innovation skills, innovation benchmarking, health service delivery, health system, South Asia, LMIC.
Précis:This cross-sectional study utilized the Innovation Skills Assessment tool to analyze idea generation, risk-taking behavior, and the ability to pivot ideas to products among employees in a tertiary care hospital in Pakistan. The findings emphasize the importance of the 36 to 45 years age group in leading the innovation culture and stress the need for evaluating low-cost innovative programs for effectiveness.
A novel method to monitor rheumatoid arthritis prevalence using hospital and medication databases
Authors: Koller-Smith Louise , Mehdi Ahmed , March Lyn , Tooth Leigh , Mishra Gita D. , Thomas Ranjeny 
Published: September 2023

Abstract

Background
Most estimates of rheumatoid arthritis (RA) prevalence, including all official figures in Australia and many other countries, are based on self-report. Self-report has been shown to overestimate RA, but the ‘gold standard’ of reviewing individual medical records is costly, time-consuming and impractical for large-scale research and population monitoring. This study provides an algorithm to estimate RA cases using administrative data that can be adjusted for use in multiple contexts to provide the first approximate RA cohort in Australia that does not rely on self-report.
Methods
Survey data on self-reported RA and medications from 25 467 respondents of the Australian Longitudinal Study on Women’s Health (ALSWH) were linked with data from the national medication reimbursement database, hospital and emergency department (ED) episodes, and Medicare Benefits codes. RA prevalence was calculated for self-reported RA, self-reported RA medications, dispensed RA medications, and hospital/ED RA presentations. Linked data were used to exclude individuals with confounding autoimmune conditions.
Results
Of 25 467 survey respondents, 1367 (5·4%) women self-reported disease. Of the 26 840 women with hospital or ED presentations, 292 (1·1%) received ICD-10 codes for RA. There were 1038 (2·8%) cases by the medication database definition, and 294 cases (1·5%) by the self-reported medication definition. After excluding individuals with other rheumatic conditions, prevalence was 3·9% for self-reported RA, 1·9% based on the medication database definition and 0·5% by self-reported medication definition. This confirms the overestimation of RA based on self-reporting.
Conclusions
We provide an algorithm for identifying individuals with RA, which could be used for population studies and monitoring RA in Australia and, with adjustments, internationally. Its balance of accuracy and practicality will be useful for health service planning using relatively easily accessible input data.
Combining transfer learning and hyperspectral imaging to identify bruises of pears across different bruise types
Authors: Liu Dayang , Zhang Huiting , CongCong Wang , Lv Feng , Yanrong Tao , Zhu Liangkuan 
Published: September 2023

Abstract

Background
Mechanical bruise is one of the most crucial factors affecting the quality of pears, which has a huge influence on postharvest transportation, storage, and sale of pears. To rapidly detect early bruises of pears across different bruise types, hyperspectral imaging technology coupled with transfer learning methods was performed in this study.
Results
Two transfer learning methods, i.e., transfer component analysis (TCA) and manifold embedded distribution alignment (MEDA), were applied for two tasks (impact bruise → crush bruise, crush bruise → impact bruise). Supporting vector machine (SVM) was set as a baseline to conduct analysis and comparison of the transferability of the models. The result showed that, for task 1 (impact bruise → crush bruise), MEDA and TCA-SVM model achieved a classification accuracy of 93.33% and 91.11% in target domain, individually. For task 2 (crush bruise → impact bruise), MEDA and TCA-SVM model achieved an accuracy of 88.89% and 85.19% in target domain, respectively. Both of the two models improved the accuracy compared with SVM models (84.44% for task 1; 77.04% for task 2).
Conclusion
Overall, the results indicated that transfer learning approaches could perform pear bruise detection across different bruise types. Hyperspectral imaging in combination with transfer learning methods is a promising possibility for the efficient and cost-saving field detection of fruit bruises among different bruise types.
Network preservation analysis to identify transcriptional biomarkers related to flowering in Crocus sativus
Authors: Eshaghi Mahsa , Rashidi-Monfared Sajad 
Published: September 2023

Abstract
Crocus sativus L. is known as an ornamental geophyte and a source of valuable spice and secondary metabolites. Network preservation module analysis is one of the best approaches to revealing special features of different conditions. It can determine patterns of divergence and conservation between transcriptome data. Herein, we explored the regulatory genes of the flowering process by RNA-Seq data containing flowering and non-flowering samples in gene expression profiles. Persevered module analysis revealed three significant non-persevered modules related to the flowering process, namely pink, green, and blue. Several hub genes associated with non-preserved modules such as PIA1, NAC90, ALY3, Sus3, MYB31, ARF5/MP, MYB31, HD-ZIP, SEP3d, OR_B, AGL6a, bZIP(TGA1) and GRAS were identified. These candidate genes can be considered key diagnostic biomarkers for the flowering process. Here, we also compare two approaches, WGCNA and NetRep for module preservation analysis. Totally, the results of these methods were consistent with non-preserved modules. NetRep was a faster (11 times) and more efficient (run more than 10000 permutations for each comparison) method than WGCNA module preservation. Differential expression genes (DEGs) screening showed that many hub genes were downregulated in non-flowering than flowering samples. Our finding revealed regulatory mechanisms of the flowering process in C. sativus as can be developed transcriptional biomarkers which could pave the way for promoting saffron yield via flowering induction.
Applications of Geospatial Technology and Water Quality Index in The Assessment of Groundwater Quality
Authors: MACHIREDDY SUNANDANA REDDY , B Bhargava , B Chennapa 
Published: September 2023

Abstract

Groundwater is one of the naturally occurring resources, which is valuable and essential for water supply to the nations. To come across the demand rate it is pivotal to recognize the water resources. Groundwater Quality has direct implication for domestic industrial and drinking purpose. The Water Quality Index is the most productive to collaborate the information of water quality. The objective of the research work is to assess and prepare the spatial distribution maps of groundwater quality of Nandyal Mandal by using geographical information system techniques. This research work is deliberated to evaluate the Water Quality Index of the project area. The Water Quality Index of the study explains overall quality of certain locations based on several physico-chemical parameters with the help of spatial distribution of geographic information system applications. Water samples were collected and tested for several physico-chemical parameters like pH, TDS, Chlorides, Total alkalinity, Total Hardness, Electro Conductivity and Dissolved oxygen.
S100A8 enhances development of glioblastoma by activation of ANXA1- mediated NF-κB pathway
Authors: Da Zheng , Zhou Yeming , Xu Jie , Zhi Zhongwen , Chen Rui 
Published: September 2023

Abstract
Background
Glioblastoma (GBM) is one of the most malignant tumors of human. S100A8 has emerged as vital mediators in cancer. However, the expression and function of S100A8 in GBM and the mechanism involved were unclear.
Methods
The expression of S100A8 was detected in glioma tissue by CGGA, TCGA database and clinical sample. CCK-8, Edu, and Colony information were used to detect cell proliferation. Wound healing and Transwell assays were used to detect cell migration and invasion, respectively. We used Xenograft model to observe the effect of S100A8 on tumor growth in vivo. Finally, immunoblotting and related biological experiments were used to detected the mechanism of S100A8 regulating the development of GBM.
Results
We reported that S100A8 was upregulated in GBM tissues and cells, and S100A8 expression level was correlated with the survival time of GBM patients. Knockdown S100A8 in U87 promoted the cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), whereas ectopic expression of S100A8 in LN229 decreased these activities of GBM. We also showed that knockdown S100A8 decreased tumor growth of GBM in vivo, and induced survival time of mice with GBM. Mechanistically, we found that S100A8 interacted with ANXA1, and decreased ubiquitination and degradation of ANXA1, thereby inducing NF-κB activation.
Conclusion
This study indicated that S100A8 promoted the development of GBM via ANXA1/NF-κB pathway, suggesting that S100A8 was a potential therapeutic target for GBM.
Spatiotemporal characteristics of drought in the Nanpan River Basin, Yunnan Province, China, from 1956 to 2016
Authors: Hu Fenglin , Yu Hang , Pan Mengnan , Pei Ding , Yang Rui , Wang Long 
Published: September 2023

Abstract
Investigating the spatiotemporal characteristics of drought is crucial for developing effective water resource and drought risk management strategies throughout basins. In this study, PCA, run theory, the MK test, and KORE and EEMD methods were used to systematically explore the spatiotemporal characteristics of drought in the Nanpan River Basin in Yunnan, China, based on the SPI6 series of 33 stations over 61 years. The results indicated that: (1)The Nanpan River Basin to be divided into three homogeneous regions (northern, southwestern and southeastern areas). The drought duration varied among the three subregions and was the shortest (5.30 months) in the southwestern region and the longest (6.25 months) in the southeastern region. The drought magnitude was similar in the different subregions (approximately − 4.0).(2)The long-term drought variation trend showed that the Nanpan River Basin became drier over the studied period. The variation trends of drought duration and drought magnitude in the same subregion were similar. In the southeastern region, the drought duration significantly increased whereas the drought magnitude apparently decreased. There were no obvious trends in the drought duration and magnitude in the northern and southwestern regions.(3)Over the 61 years, the drought yearly occurrence rate showed an overall upward trend, indicating that the frequency of drought events with a moderate drought and above in the Nanpan River Basin increased, even though the drought yearly occurrence rate in the three homogeneous regions fluctuated in different periods.(4)The drought cycles in the Nanpan River Basin were mainly less than 10a, and the quasi-cycles in the three subregions were all 3a; these results passed the significance test at the 80% confidence level. On a period scale of more than 10a, only the southwestern region showed quasi-15a and quasi-31a cycles, which passed the significance test at the 95% and 90% confidence levels, respectively.
Development of risk prediction nomogram for neonatal sepsis in Group B Streptococcus-colonized mothers: A retrospective study
Authors: Wu MengQi , Luo XiaoMing , Deng YanBing , Wang XinYe , He BaoMei , Wei FangQiang , Zhang Ying 
Published: September 2023

Abstract
Background
Neonatal clinical sepsis is recognized as a significant health problem, This study sought to identify a predictive model of risk factors for clinical neonatal sepsis.
Methods
From October 2018 to April 2023, a retrospective study of maternal-newborn dichotomy was conducted in a large tertiary hospital in China. Neonates were divided into patients and controls according to whether neonatal sepsis occurred. A multivariable model was used to determine risk factors and construct models.
Results
A total of 339 pairs of mothers and their newborns were included in the study and divided into two groups: patients (n = 84, 24.78%) and controls (n = 255, 75.22%). Logistic regression analysis was performed to examine the relationship between various factors and outcome. The results showed that maternal age ＜26 years (odds ratio [OR] = 2.16, 95% confidence interval [CI] 1.06–4.42, p = 0.034), maternal gestational diabetes (OR 2.17, 95%CI 1.11–4.27, p = 0.024), no forceps assisted delivery (OR 0.21, 95%CI 0. 05–0.80, p = 0.023 ), no umbilical cord winding (OR 0.57, 95%CI 0.34–0.98, p = 0.041 ) and male neonatal sex (OR 1.59, 95%CI 1.00–2.62, p = 0.050 ) were identified as independent factors influencing the outcome of neonatal clinical sepsis. A main effects model was developed incorporating these five significant factors, resulting in an area under the curve (AUC) value of 0.71 (95% CI: 0.63–0.77) for predicting the occurrence of neonatal clinical sepsis.
Conclusion
A main effects model incorporating the five significant factors was constructed to help healthcare professionals make informed decisions and improve clinical outcomes.
STIM2 is involved in the regulation of apoptosis and cell cycle in normal and malignant monocytic cells
Authors: Djordjevic Stefan , Itzykson Raphaël , Hague Frederic , Lebon Delphine , Legrand Julien , Ouled-Haddou Hakim , Jedraszak Guillaume , Harbonnier Juliette , Collet Louison , Paubelle Etienne , Marolleau Jean-Pierre , Garçon Loïc , Boyer Thomas 
Published: September 2023

Abstract

Background
Calcium is a ubiquitous messenger that regulates a wide range of cellular functions including proliferation, cell migration and apoptosis. Abnormal expression of proteins involved in Ca2+ signaling has been associated with oncogenesis in many solid tumor models. However, its involvement in the pathophysiology of acute myeloid leukemia is less investigated. In this work, we aimed to identify actors of Ca2+ signaling involved in leukemogenesis.
Methods
From an analysis of TCGA and GTEx databases, we identified STIM2, a key sensor regulating Ca2+ capacitive entry, as highly expressed in AML with monocytic differentiation and negatively correlated with overall survival. This was confirmed on a validation cohort of 407 AML patients, showing an association of a high STIM2 expression with adverse risk group according to ELN17 classification. We then investigated the role of STIM2 in cell proliferation, differentiation and survival by modulating its expression in two leukemic cell lines with monocytic potential and in normal hematopoietic stem cells driven into monocytic differentiation.
Results
STIM2 expression increased at the RNA and protein levels upon monocyte differentiation. Phenotypically, STIM2 knockdown drastically inhibited cell proliferation and induced genomic stress with DNA double-strand breaks, as shown by increased p-H2AXγ, followed by activation of the p53 pathway, decreased expression of cell cycle regulators such as CDK1-cyclin B1 and the CDC25c phosphatase, and a decreased apoptosis threshold with a low antiapoptotic/proapoptotic protein ratio. This phenotype was not observed in two p53-deleted cell lines, HL60 and K562. Using a model of in vitro monocytic differentiation of peripheral blood-derived CD34+ cells, we observed higher STIM2 expression at the RNA level in differentiated cells. The acquisition of monocytic markers was faster after STIM2 forced expression, while STIM2 knockdown impaired CD14 expression and led to p-H2AXγ, p53 induction, apoptosis and cell cycle blockage, in agreement with data observed in leukemic cell lines.
Conclusions
In summary, we report STIM2 as a new actor regulating genomic stability and p53 response in terms of cell cycle and apoptosis of human normal and malignant monocytic cells. Considering the association of high STIM2 expression with an adverse prognosis in AML and the association of STIM2 with AML harboring monocytic/myelomonocytic differentiation.