bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of glucose variability on the assessment of the glycemia risk index (GRI) and classic glycemic metrics
Authors: Pérez-López Paloma , Férnandez-Velasco Pablo , Bahillo-Curieses Pilar , de Luis Daniel , Díaz-Soto Gonzalo 
Published: September 2023

Abstract
Objective
To evaluate the impact of glucose variability on the relationship between the GRI and other glycemic metrics in a cohort of pediatric and adult patients with type 1 diabetes (T1D) using intermittent scanning continuous glucose monitoring (isCGM).

Methods
We performed a cross-sectional study of 202 patients with T1D under intensive insulin treatment (25.2% CSII) using isCGM. Clinical, metabolic, and glycemic metrics were collected, and the GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. The correlation between the GRI and other classical glycometrics in relation to the coefficient of variation (CV) was evaluated.

Results
A total of 202 patients were included (53% male; 67.8% adults) with a mean age of 28.6 ± 15.7 years and 12.5 ± 10.9 years of T1D evolution (TIR 59.0 ± 17.0%; CV 39.8 ± 8.0%; GMI 7.3 ± 1.1%). The mean GRI was 54.0 ± 23.3 with a CHypo and CHyper component of 5.7 ± 4.8 and 23.4 ± 14.3, respectively. A strong negative correlation was observed between the GRI and TIR (R = −0.917; R2 = 0.840; p < 0.001), showing differences when dividing patients with low glycemic variability (CV < 36%) (R = −0.974; R2 = 0.948; p < 0.001) compared to those with greater CV instability (≥36%) (R = −0.885; R2 = 0.784; p < 0.001). The relationship of GRI with its two components was strongly positive with CHyper (R = 0.801; R2 = 0.641; p < 0.001) and moderately positive with CHypo (R = 0.398; R2 = 0.158; p < 0.001). When the GRI was evaluated with the rest of the classic glycemic metrics, a strong positive correlation was observed with HbA1c (R = 0.617; R2 = 0.380; p < 0.001), mean glucose (R = 0.677; R2 = 0.458; p < 0.001), glucose standard deviation (R = 0.778; R2 = 0.605; p < 0.001), TAR > 250 (R = 0.801; R2 = 0.641; p < 0.001), and TBR < 54 (R = 0.481; R2 = 0.231; p < 0.001).

Conclusions
The GRI correlated significantly with all the glycemic metrics analyzed, especially with the TIR. Glycemic variability (GV) significantly affected the correlation of the GRI with other parameters and should be taken into consideration.
Expression and function of CCN2-derived circRNAs in chondrocytes
Authors: Kato Soma , Kawata Kazumi , Nishida Takashi , Mizukawa Tomomi , Takigawa Masaharu , Iida Seiji , Kubota Satoshi 
Published: September 2023

AbstractCellular communication network factor 2 (CCN2) molecules promote endochondral ossification and articular cartilage regeneration, and circular RNAs (circRNAs), which arise from various genes and regulate gene expression by adsorbing miRNAs, are known to be synthesized from CCN2 in human vascular endothelial cells and other types of cells. However, in chondrocytes, not only the function but also the presence of CCN2-derived circRNA remains completely unknown. In the present study, we investigated the expression and function of CCN2-derived circRNAs in chondrocytes. Amplicons smaller than those from known CCN2-derived circRNAs were observed using RT-PCR analysis that could specifically amplify CCN2-derived circRNAs in human chondrocytic HCS-2/8 cells. The nucleotide sequences of the PCR products indicated novel circRNAs in the HCS-2/8 cells that were different from known CCN2-derived circRNAs. Moreover, the expression of several Ccn2-derived circRNAs in murine chondroblastic ATDC5 cells was confirmed and observed to change alongside chondrocytic differentiation. Next, one of these circRNAs was knocked down in HCS-2/8 cells to investigate the function of the human CCN2-derived circRNA. As a result, CCN2-derived circRNA knockdown significantly reduced the expression of aggrecan mRNA and proteoglycan synthesis. Our data suggest that CCN2-derived circRNAs are expressed in chondrocytes and play a role in chondrogenic differentiation.
Graphical abstract
Politics and Psychology
Authors: Busch-Jensen Peter , Røn-Larsen Maja 
Published: September 2023

AbstractThis article presents a discussion inspired by the invitation formed by Kevin Carriere’s book: “Psychology in Policy – Redefining Politics Through The Individual”. From a theoretical standpoint in culture psychology Carriere challenges the idea of politics as a particular practice carried out by mainly politicians. Instead, he attempts to anchor processes of politics in the everyday lives of individuals, directed at changing their worlds. In this article, we discuss how this ambition could evolve even further by relating it to other theoretical approaches working with similar ambitions.
Three Kinds of Arguments for Panpsychism
Authors: Jarocki Jacek 
Published: September 2023

AbstractPanpsychism may be roughly defined as a view that at least some of the properties constituting the fundamental level of reality are mental or proto-mental. Despite its long history, it has been revived in recent discussions as a solution to the problems raised by the mind, especially to the so-called hard problem of consciousness. Contemporary panpsychism differs significantly from incarnations known from the history of philosophy mainly due to the fact that the former is often combined with so-called Russellian monism. According to Russellian monism, the intrinsic properties of physical things remain unknown. This encourages panpsychists to argue that those properties are in fact mental. In my paper, I examine the three most common arguments for panpsychism: the Continuity Argument, the Hegelian Argument, and the Agnostic Argument. I take a closer look at each of them to assess their advantages and weaknesses. As I point out, the way in which one argues implies the version of panpsychism one adopts. This turns out to be especially important with regard to the Hegelian Argument and the Agnostic Argument. Both can be combined with Russellian monism, resulting in Russellian panpsychism. However, I claim that the philosophical consequences of these arguments are different, so it is legitimate to distinguish two kinds of Russellian panpsychism. In conclusion, I hold that there are reasons to prefer panpsychism based on the Agnostic Argument, which is more promising, as it responds to some general problems of panpsychism.
The Effectiveness of Low-Intensity Psychological Interventions for Comorbid Depression and Anxiety in Patients with Long-Term Conditions: A Real-World Naturalistic Observational Study in IAPT Integrated Care
Authors: Lee Chi Tak , Harty Siobhan , Adegoke Adedeji , Palacios Jorge , Gillan Claire M. , Richards Derek 
Published: September 2023

Abstract
Background
Low-intensity psychological interventions may be a cost-effective, accessible solution for treating depression and anxiety in patients with long-term conditions, but evidence from real-world service settings is lacking. This study examined the effectiveness of low-intensity psychological interventions provided in the Improving Access to Psychological Therapies programme in England for patients with and without long-term conditions.

Methods
A retrospective analysis was conducted on patients (total N = 21,051, long-term conditions n = 4024) enrolled in three low-intensity psychological interventions, i.e. Internet-delivered cognitive behavioural therapy (iCBT), guided self-help (GSH), and psychoeducational group therapy (PGT) within a Talking Therapies service from 2016 to 2020. Primary outcomes included pre–post-treatment changes in depression (Patient Health Questionnaire-9) and anxiety (Generalised Anxiety Disorder-7).

Results
Overall, both cohorts significantly improved on all outcomes post-treatment, with large effect sizes. Patients with long-term conditions experienced a greater reduction in depression while those without experienced a greater reduction in anxiety, but these differences were marginal (< 1 score difference on both measures). No difference between the cohorts was shown when comparing the differential effectiveness across interventions, but those engaging in iCBT showed greater reduction in depression and anxiety than those in GSH and PGT, while those in GSH improved more than PGT.

Conclusions
Low-intensity psychological interventions, particularly iCBT, were effective in treating depression and anxiety in patients with long-term conditions in a real-world service setting. Our large-scale study supports the continued and increased implementation of low-intensity psychological interventions for this subpopulation via integrated care.
Coupled hydro-mechanical simulation in the carbonate reservoir of a giant oil field in southwest Iran
Authors: Saadatnia Narges , Sharghi Yousef , Moghadasi Jamshid , Ezati Mohsen 
Published: September 2023

AbstractThe Asmari reservoir in southwest Iran has been producing oil continuously for over 50 years. However, due to an essential pressure decline, the reservoir is now a potential candidate for injection projects. The geomechanical analysis is essential for a successful injection operation to enhance reservoir production and address possible challenges. An accurate estimation of the injection pressure is necessary to maintain optimal conditions during the injection process and reduce possible risks. In this work, a coupled reservoir-geomechanical model, as well as rock mechanical tests, is performed to evaluate not only pressure variation and the associated in situ stress changes but also their potential influences on fault reactivation, reservoir–caprock stability, and surface displacement. For geomechanical evaluation, empirical correlations are derived between static and dynamic rock properties based on core data and existing petrophysical logs for the studied reservoir–caprock system. Based on the hydro-mechanical results, the maximum displacement is limited to the vicinity of the injection wells, where the highest pressure changes occur. The geomechanical analysis of the reservoir–caprock system shows that this system is stable until the injection pressure reaches 4.3× the initial reservoir pressure. Also, the injection pressure is not high enough to compromise the integrity of faults, indicating that the loading on the fault planes is too low to reactivate the pre-existing faults. The approach followed in this study can be applied to future field development strategies and feasibility considerations for CO2 sequestration and underground gas storage projects.
The InsightsNet Climate Change Corpus (ICCC)
Authors: Volkanovska Elena , Tan Sherry , Duan Changxu , Bartsch Sabine , Stille Wolfgang 
Published: September 2023

AbstractThe discourse on climate change has become a centerpiece of public debate, thereby creating a pressing need to analyze the multitude of messages created by the participants in this communication process. In addition to text, information on this topic is conveyed multimodally, through images, videos, tables and other data objects that are embedded within documents and accompany the text. This paper presents the process of building a multimodal pilot corpus to the InsightsNet Climate Change Corpus (ICCC) and using natural language processing (NLP) tools to enrich corpus (meta)data, thus creating a dataset that lends itself to the exploration of the interplay between the various modalities that constitute the discourse on climate change. We demonstrate how the pilot corpus can be queried for relevant information in two types of databases, and how the proposed data model promotes a more comprehensive sentiment analysis approach.
Ceftazidime-avibactam alone or in combination with Aztreonam versus Polymyxins in the management of carbapenem-Resistant Klebsiella pneumoniae nosocomial Infections (CAPRI study): a retrospective cohort study from South India
Authors: Sree Racha Amarthya , Gupta Anand , Gupta Nitin , Veturi Sadhana , Reddy L. Siva Kumar , Begum Masrath , Shravani Etrouth , Challa HariPriya Reddy , Reddy Satti Santhosh , Singamsetty Adarsh , Arumilli Murthy , Reddy P. Naveen , Tirlangi Praveen Kumar 
Published: September 2023

Abstract
Introduction
Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections commonly cause hospital-acquired infections. The study aimed to compare the outcomes of CRKP infections between patients receiving ceftazidime avibactam +/− aztreonam and polymyxins in a hospital setting with a high prevalence of New Delhi Metallo Beta Lactamase production.

Methods
We conducted a retrospective cohort study from January 2020 to September 2022 in critically ill adult patients admitted to a non-COVID-19 medical intensive care unit with CRKP infection. The patients were followed up for a total of 30 days or death, whichever was later.

Results
Of a total of 106 patients included in the study, 65 patients received polymyxins and 41 patients received ceftazidime–avibactam +/− aztreonam. Higher 30-day mortality was noted in the polymyxin group (56.9% vs. 29.2%, P = 0.005). The mean time to event (mortality) in ceftazidime–avibactam +/− aztreonam was 23.9 + 1.5 days which was significantly higher compared to polymyxins (17.9 + 1.2 days, p = 0.006). On Cox regression analysis, after adjusting for the covariates, the hazard ratio for time to event with the use of polymyxin was 2.02 (95% CI: 1.03–3.9).

Conclusion
Ceftazidime–avibactam + aztreonam is possibly associated with better clinical outcomes in patients infected with CRKP.
A modularity total environment network model for sustainable forest transportation
Authors: Tsiotas Dimitrios , Kantartzis Apostolos , Kolkos Georgios , Lemonakis Panagiotis , Arabatzis Garyfallos 
Published: September 2023

AbstractForest road network planning and development is important in providing accessibility to remote forest areas for timber harvesting, transportation to markets, and recreational activities, as well as preventing environmental degradation, soil erosion, water pollution, and an increased risk of forest fires and wildlife habitat fragmentation. Within the context that careful forest road transportation planning and design promotes sustainable forest management and development, this paper develops a multilayer network model for supporting sustainable forest transportation development. The model builds on a total environment conceptualization and the network paradigm, and it is composed of several layers, each containing information from an environmental aspect or a forest road network land use. By using community detection analysis from network science, the model provides insights into the decomposition of the forest network into functional areas, highlights the importance of places that connect different communities to maintain market integration, and provides a list of policies and good practices for the resulting communities. Overall, this paper presents a quantitative methodological framework that can be used for sustainable forest transportation.
Research on low-carbon evaluation of green buildings based on the whole life cycle theory
Authors: Jamaludin Farah Adilah Binti , Li Jiabo 
Published: September 2023

AbstractCities are highly dense areas with significant energy consumption and waste generation. Therefore, developing buildings with low energy consumption and reduced pollutant emissions is an important approach for China to achieve its goals of carbon neutrality, peak carbon emissions, and sustainable development. In this context, the concept and practice of green buildings have emerged. This research is based on the whole life cycle assessment method of the whole life cycle theory, integrating relevant indicators for calculating carbon emissions in buildings. It conducts a multidimensional evaluation and analysis of the low-carbon level of green buildings. Quantitative analysis is carried out based on five stages and five dimensions of the entire construction process. A conceptual model for the low-carbon evaluation of green buildings is established, and grey relational analysis and analytic hierarchy process are employed to rank and evaluate projects. The study aims to identify the key factors in the low-carbon evaluation of green buildings and discusses the focus and suggestions for future low-carbon management throughout the whole life cycle of green buildings.
Recent advances in efficient and scalable solar hydrogen production through water splitting
Authors: Zheng Yihao , Ma Ming , Shao Huaiyu 
Published: September 2023

AbstractSolar hydrogen production through water splitting is the most important and promising approach to obtaining green hydrogen energy. Although this technology developed rapidly in the last two decades, it is still a long way from true commercialization. In particular, the efficiency and scalability of solar hydrogen production have attracted extensive attention in the field of basic research. Currently, the three most studied routes for solar hydrogen production include photocatalytic (PC), photoelectrochemical (PEC), and photovoltaic-electrochemical (PV-EC) water splitting. In this review, we briefly introduce the motivation of developing green hydrogen energy, and then summarize the influential breakthroughs on efficiency and scalability for solar hydrogen production, especially those cases that are instructive to practical applications. Finally, we analyze the challenges facing the industrialization of hydrogen production from solar water splitting and provide insights for accelerating the transition from basic research to practical applications. Overall, this review can provide a meaningful reference for addressing the issues of efficiency improvement and scale expansion of solar hydrogen production, thereby promoting the innovation and growth of renewable hydrogen energy industry.
Graphical Abstract
An AI-driven Predictive Model for Pancreatic Cancer Patients Using Extreme Gradient Boosting
Authors: Chakraborty Aditya , Tsokos Chris P. 
Published: September 2023

AbstractPancreatic cancer is one of the deadliest carcinogenic diseases affecting people all over the world. The majority of patients are usually detected at Stage III or Stage IV, and the chances of survival are very low once detected at the late stages. This study focuses on building an efficient data-driven analytical predictive model based on the associated risk factors and identifying the most contributing factors influencing the survival times of patients diagnosed with pancreatic cancer using the XGBoost (eXtreme Gradient Boosting) algorithm. The grid-search mechanism was implemented to compute the optimum values of the hyper-parameters of the analytical model by minimizing the root mean square error (RMSE). The optimum hyperparameters of the final analytical model were selected by comparing the values with 243 competing models. To check the validity of the model, we compared the model’s performance with ten deep neural network models, grown sequentially with different activation functions and optimizers. We also constructed an ensemble model using Gradient Boosting Machine (GBM). The proposed XGBoost model outperformed all competing models we considered with regard to root mean square error (RMSE). After developing the model, the individual risk factors were ranked according to their individual contribution to the response predictions, which is extremely important for pancreatic research organizations to spend their resources on the risk factors causing/influencing the particular type of cancer. The three most influencing risk factors affecting the survival of pancreatic cancer patients were found to be the age of the patient, current BMI, and cigarette smoking years with contributing percentages of 35.5%, 24.3%, and 14.93%, respectively. The predictive model is approximately 96.42% accurate in predicting the survival times of the patients diagnosed with pancreatic cancer and performs excellently on test data. The analytical methodology of developing the model can be utilized for prediction purposes. It can be utilized to predict the time to death related to a specific type of cancer, given a set of numeric, and non-numeric features.
Heterogeneity in strategies to maintain the teaching activities during SARS-CoV-2 pandemic
Authors: Hipler Noam M. , Prazienka Philipp , Wiesmann Crispin , Dieterich Daniela C. , Link Alexander 
Published: September 2023

Abstract
Introduction
During the SARS-CoV-2 pandemic, the training of medical students was severely disrupted. Government authorities imposed a second national lockdown, which lasted from December 2020 to May 2021, forcing medical schools to adapt their teaching strategies. Several surveys have assessed students’ perspectives, but there is limited data available to objectively assess and compare different strategies between medical faculties. The aim of this study was to evaluate the lecturer-based perspective to assess the impact on the theoretical and practical education of medical students before and during the second lockdown.

Methods
We developed a questionnaire focusing on theoretical and practical training during pandemic before and during the second lockdown. The questionnaire was sent by personal invitation in January 2021 to all responsible lecturers of gastroenterology and hepatology departments at university hospitals in Germany.

Results
The complete response rate was obtained from 52.5% (21/40) teaching centres representative of all regions in Germany. While the majority of respondents (62%) reported a limited impact of the lockdown on theoretical training, 90.5% reported a significant impact on practical training during the SARS-CoV-2 pandemic response. Several centres adapted virtual or hybrid education early during the pandemic, bedside teaching was down to 38.1% (8/21), particularly for students in the early phase of education, suggesting a substantial long-term impact on students' skills.

Conclusion
Our questionnaire-based data provide one of the first systematic evaluation of faculty-based assessments of the potential impact of the pandemic during lockdown on medical education. We observed considerable heterogeneity in strategies for maintaining teaching activities during the SARS-CoV-2 pandemic in Germany.
Assessing the ecological risk of representative wastewater based on a growth inhibition method with freshwater algae (Raphidocelis subcapitata)
Authors: Wang Aoxue , Li Hanqing , Liang Tao , Lian Gang , Gui Wenjun , Zhou Shengli , Li Shuying 
Published: September 2023

AbstractWastewater contains a vast number of pollutants that potentially threaten the ecosystem after being discharged into the environment. The present study aimed to develop a rapid and sensitive toxicity detection method for assessing the ecological risk of wastewater. Raphidocelis subcapitata was used as the test organism in the algal growth inhibition test, and the anti-interference capacity of R. subcapitata itself and three biomass measuring methods (spectrophotometer, electron particle counter and chlorophyll fluorescence) on sample color and sample particulate matter were examined. The results revealed that chlorophyll fluorometry was more suitable for determining biomass in the growth inhibition test. Furthermore, chlorophyll fluorometry was selected to evaluate the combined toxic effects and sensitivity of R. subcapitata to wastewater from different industries. Microalgae respond differently to the toxicity of wastewater from various sources. The LID values for chemical wastewater 2, urban sewage 1, pharmaceutical wastewater 1, electroplating effluent and pharmaceutical wastewater 2 were 4.0, 3.0, 2.7, 2.4 and 2.0, respectively. The present study investigated the toxicity response of R. subcapitata to wastewater from various industries by growth inhibition experiments to comprehend the possible ecological concerns of wastewater from diverse businesses. This study will provide a significant basis for the design of detection methods and a comprehensive evaluation of toxicity in surface water environments.
Graphical Abstract