bluuebunny/crossref_metadata_2025_split huggingface dataset:
CMIP6 precipitation and temperature projections for Chile
Authors: Salazar Alvaro , Thatcher Marcus , Goubanova Katerina , Bernal Patricio , Gutiérrez Julio , Squeo Francisco 
Published: June 2023

Abstract
Precipitation and near-surface temperature and from an ensemble of 36 new state-of‐the‐art climate models under the Coupled Model Inter‐comparison Project phase 6 (CMIP6) are evaluated over Chile´s climate. The analysis is focused on four distinct climatic subregions: Northern Chile, Central Chile, Northern Patagonia, and Southern Patagonia. Over each of the subregions, first, we evaluate the performance of individual global climate models (GCMs) against a suit of precipitation and temperature observation-based gridded datasets over the historical period (1986–2014) and then we analyze the models’ projections for the end of the century (2080–2099) for four different shared socioeconomic pathways scenarios (SSP). Although the models are characterized by general wet and warm mean bias, they reproduce realistically the main spatiotemporal climatic variability over different subregions. However, none of the models is best across all subregions for both precipitation and temperature. Moreover, among the best performing models defined based on a Taylor skill score, one finds the so-called “hot models” likely exhibiting an overestimated climate sensitivity, which suggest caution in using these models for accessing the future change in Chile. We found robust (90% of models agree in the direction of change) projected end-of-the-century reductions in mean annual precipitation for Central Chile (~-20% to ~-40%) and Northern Patagonia (~-10% to ~-30%) under scenario SSP585, but changes are strong from scenario SSP245 onwards, where precipitation is reduced by 10–20%. Northern Chile and Southern Patagonia show non-robust changes across the models. Future near-surface temperature warming presented high inter-model agreement across subregions with the greatest increments occurring along the Andes Mountains. Northern Chile displays the strongest increment of up to ~ 6°C in SSP585, followed by Central Chile (up to ~ 5°C), both Northern and Southern Patagonia show a corresponding increment by up to ~ 4°C. We also briefly discuss the environmental and socio-economic implications of these future changes for Chile.
Diagnostic model for Alzheimer's disease based on PANoptosis-related genes
Authors: Zhang Erdong , Dai Fengqiu , Chen Tingting , Tao Ling , Shen Xiangchun 
Published: June 2023

AbstractBackground:The pathophysiology of Alzheimer's disease (AD) involves the interplay of three different processes: pyroptosis, apoptosis, and necroptosis. However, the role of PANoptosis, a novel pro-inflammatory programmed cell death pathway, in AD remains unexplored.Result:Our study utilized tissue expression profile data from AD patients to construct three distinct PANoptosis patterns, each with unique molecular and clinical characteristics. We have created a risk scoring system called the PANscore, which can analyze patterns specific to each AD patient. Additionally, we observed significantly lower levels of follicular helper T cells (Tfh) in the high PANscore and AD patients. Further analysis revealed a significant negative correlation of Tfh withGSDMDandMLKL.Conclusion:These findings provide a roadmap for personalized patient stratification, enabling clinicians to develop personalized treatment plans for AD patients and advance the field of precision medicine.
Protocol for a Prospective Study Evaluating Circulating Tumour Cells Status to Predict Radical ProstatectomyTreatment Failure in Localised Prostate Cancer Patients (C- ProMeta-1)
Authors: Al-Hammouri Tarek , Almeida-Magana Ricardo , Lawrence Rachel , Duffy Tom , White Laura , Burke Edwina , Kudahetti Sakunthala , Collins Justin , Rajan Prabhakar , Berney Daniel , Gabe Rhian , Shaw Greg , Lu Yong-Jie 
Published: June 2023

Abstract
Background: Treatment decisions in prostate cancer (PCa) rely on disease stratification between localised and metastatic stages, but current imaging staging technologies are not sensitive to micro-metastatic disease. Circulating tumour cells (CTCs) status is a promising tool in this regard. The Parsortix® CTC isolation system employs an epitope-independent approach based on cell size and deformability to increase the capture rate of CTCs. Here, we present a protocol for prospective evaluation of this method to predict post radical prostatectomy (RP) PCa cancer recurrence.
Methods: We plan to recruit 294 patients diagnosed with unfavourable intermediate, to high and very high-risk localised PCa. Exclusion criteria include synchronous cancer diagnosis or prior PCa treatment, including hormone therapy. RP is performed according to the standard of care. Two blood sample (20ml) are collected before and again 3-months after RP. The clinical team are blinded to CTC results and the laboratory researchers are blinded to clinical information. Treatment failure is defined as a PSA ≥ 0.2 mg/ml, start of salvage treatment or imaging-proven metastatic lesions. The CTC analysis entails enumeration and RNA analysis of gene expression in captured CTCs. The primary outcome is the accuracy of CTC status to predict post-RP treatment failure at 4.5 years. Observed sensitivity, positive and negative predictive values will be reported. Specificity will be presented over time.
Discussion: CTC status may reflect the true potential for PCa metastasis and may predict clinical outcomes better than the current PCa progression risk grading systems. Therefore establishing a robust biomarker for predicting treatment failure in localized high-risk PCa would significantly enhance guidance in treatment decision-making, optimizing cure rates while minimizing unnecessary harm from overtreatment.
Trial registration: ISRCTN17332543
What is important to the GP in recognizing acute appendicitis in children: a Delphi study
Authors: Blok Guus C.G.H. , Berger Marjolein Y. , Holtman Gea A. 
Published: June 2023

Abstract
BACKGROUND: For diagnostic research on appendicitis in registration data, insight is needed in the way GPs generate medical records. We aimed to reach a consensus on the features that GPs consider important in the consultation and medical records when evaluating a child with suspected appendicitis.
METHODS: We performed a three-round Delphi study among Dutch GPs selected by purposive sampling. An initial feature list was created based on a literature search and features in the relevant Dutch guideline. Finally, using a vignette describing a child who needed later reassessment, we asked participants to complete an online questionnaire about which consultation features should be addressed and recorded.
RESULTS: A literature review and Dutch guideline yielded 95 consultation features. All three rounds were completed by 22 GPs, with the final consensus list containing 26 symptoms, 29 physical assessments and signs, 2 additional tests, and 8 further actions (including safety-netting, i.e., informing the patient about when to contact the GP again). Of these, participants reached consensus that 37 should be actively addressed and that 20 need to be recorded if findings are negative.
CONCLUSIONS:
GPs agreed that negative findings do not need to be recorded for most features and that records should include the prognostic and safety-netting advice given. The results have implications in three main domains: for research, that negative findings are likely to be missing; for medicolegal purposes, that documentation cannot be expected to be complete; and for clinical practice, that safety-netting advice should be given and documented.
The relationship between circulating stem cells and stromal cell derived factor-1 with disease severity in patients with liver cirrhosis
Authors: Mansoursamaei Ali , Forough Zahra , Sadeghi Amir Mohammad , Abhari Hani Khalili , Vahedi Hamid , Atashi Amir 
Published: June 2023

Abstract
Introduction:
Stem cells have the ability to regenerate and transform into different cells. The chemokine stromal cell-derived factor 1 (SDF-1) plays an important role in hematopoietic stem cell mobilization, implantation, survival, and proliferation. In this study, we aimed to investigate the relationship between the number of stem cells in the blood and the blood concentration of stromal cell-derived factor 1 with disease severity in cirrhotic patients.
Methods
15 patients with cirrhosis and 15 healthy individuals aged 18 to 65 years were randomly selected between January 2016 and July 2017. The number of circulating stem cells and SDF-1 levels were compared in the patient group and the healthy control group. The correlation between circulating stem cells and SDF-1 concentration with disease severity was evaluated.
Results
33% of cirrhotic patients were classified as severity B and 67% as severity C by the Child-Pugh method. The percentage of stem cells and mean SDF-1 concentration in patients with cirrhosis was approximately 2.8 (p < 0.00) and 1.81 (P < 0.001) times higher than in healthy individuals, respectively. Although, there was no significant association between disease severity and the percentage of circulating stem cells in cirrhotic patients (P = 0.46), a significantly higher concentrations of SDF-1 was observed in more severe forms of the disease (p = 0.04).
Conclusion
The percentage of stem cells and the concentration of SDF-1 in the serum of patients with cirrhosis were higher in patients with cirrhosis. The severity of the disease was significantly related to the SDF-1 concentration.
Comparison of Machine Learning Models in Predicting In-hospital Mortality of Patients with Acute Paraquat Poisoning
Authors: Tang Guo , Jiang Zhen , Wei Wei , Yang Ying , Yang Sha , Yao Rong 
Published: June 2023

Abstract
Aims
To evaluate the predictive capabilities of various machine learning models for in-hospital mortality in patients diagnosed with acute paraquat poisoning(APP).
Methods
From September 2010 to January 2022, patients were identified retrospectively from the emergency departments of West China Hospital, Sichuan University, People's Republic of China. A total of 724 patients were randomly divided into a training set (80% of subjects) and a validation set (20% of subjects). The least absolute shrinkage and selection operator (LASSO) method was utilized to identify significant features associated with APP, and nine machine learning models were constructed. Model evaluation was carried out in the validation set, using a range of evaluation metrics such as accuracy, precision, recall, F-measure, the area under the receiver operating characteristic curve(AUC), Precision-Recall curve (PRC), and Clinical decision curve analysis(DCA). The CatBoost model was employed to predict in-hospital mortality in patients with APP, and the ibreakdown and SHapley Additive exPlanations (SHAP) package in R were used to interpret the CatBoost model.
Results
A group of 724 individuals who had suffered from APP were enrolled, of whom 360 had passed away. During feature selection, six variables were chosen as predictive indicators for the model. In feature selection, 6 variables were selected as model predicting indicators. Compared with Adaptive Boosting(AdaBoost), CatBoost, Decision Tree(DT), Gradient Boosting Decision Tree(GBDT), Light Gradient Boosting Machine(LightGBM), Logistic Classification, Random Forest(RF), Support Vector Machine(SVM), eXtremeGradient Boosting(XGBoost) improved the classification prediction performance, respectively. CatBoost was the best-performing model (accuracy = 1, precision = 1, recall = 1, F-measure = 1, and AUC = 1). Furthermore, PRC and DCA indicated that the model had a excellent predictive performance.
Conclusions
By utilizing machine learning models, the likelihood of in-hospital mortality in patients with APP can be predicted with precision and dependability. Of the various ensemble learning models tested, including RF, AdaBoost, CatBoost, GBDT, LightGBM, and XGBoost, CatBoost exhibited nearly flawless performance. These results demonstrate the feasibility of integrating machine learning models into electronic health records to facilitate informed care and service planning.
A network pharmacology for predicting the key targets and potential mechanism of Paxlovid in treating COVID-19
Authors: Liu Heng-Jian , Lin Yuan , Qian Pei-Xia , He Jiang 
Published: June 2023

Abstract
Background: Paxlovid has been widely used to treat COVID-19 in global pandemics. The aim of this study is to discover the main targets of SARS-CoV-2 and to explore therapeutic mechanism of Paxlovid.
Methods: The targets of Paxlovid were predicted by SwissTargetPrediction. Meanwhile, COVID-19 related targets were collected from GeneCards and OMIM. Then, PPI networks, GO and KEGG enrichment analysis were constructed to discover the potential mechanism by STRING, Cytoscape and DAVID. Finally, AutoDock Vina and Pymol were performed to visualize the interactions between Paxlovid and targets.
Results: A total of 22 Paxlovid-related targets of were collected, and 1191 remained therapeutic genes for COVID-19. 23 targets were retained for the further study by PPI network and data integration. The GO and KEGG indicated that 23 targets were significantly enriched to inflammatory response, immune response and so forth. Paxlovid was successfully docked to the active of ALB, CXCL8, HLA-A, IL1B, IL6, KNG1, TNF, VEGFA, CD8A and CTSL. In addition, Paxlovid easily bind with the active pocket of3CLpro and PLpro.
Conclusions: Paxlovid could directly target 3CLproand PLpro, and also regulate the immune system. Meanwhile, it may affect the interaction between spike protein RBD and ACE2.
The relationship between self-esteem and problematic smartphone use: the mediating role of aggressiveness
Authors: Zhang Lihua , Yang Bo , Zhu He 
Published: June 2023

Abstract
Background: Problematic smartphone use can negatively affect people on a cognitive and behavioral level. Some studies found a negative association between self-esteem and problematic smartphone use but there are different results. This may be due to a lack of differentiation between explicit and implicit self-esteem. Previous studies have also examined the relationship between self-esteem, aggressiveness, and problematic smartphone use, but it is unclear if aggressiveness plays a mediating role in self-esteem and problematic smartphone use. To address these gaps in knowledge, we conducted a study where we separately analyzed the relationships between explicit and implicit self-esteem and problematic smartphone use, and investigated whether aggressiveness acts as a mediator between them.
Method:A cross-sectional study with167 College students was carried out. The Rosenberg Self-Esteem Scale was used to measure the participants' explicit self-esteem. The Implicit Association Test was used to measure implicit self-esteem. The Smartphone Addiction Scale-Short Version was used to measure the participants' problematic smartphone use. The Chinese College Students' Version of the Buss-Perry Aggression Questionnaire was used to measure aggressiveness.
Results: The findings show a negative correlation between problematic smartphone use and explicit self-esteem, but not implicit self-esteem. The connection between explicit self-esteem and problematic smartphone use is totally mediated by aggressiveness.
Conclusion: This study emphasize the important role of aggressiveness in problematic smartphone use behaviors of people with low explicit self-esteem. Aggressiveness plays a completely mediating role between explicit self-esteem and problematic smartphone use. Our study provides a basis for future interventions for problematic smartphone use.
Systemic lupus erythematosus increases the risk of knee osteoarthritis: A Mendelian randomization study
Authors: Li Jin , Zhang Liheng , Li Jie , Jin Xi , Liu Sheng , Leng Xiangyang 
Published: June 2023

Abstract
Patients with systemic lupus erythematosus (SLE) often present with musculoskeletal system involvement, but the existence of a causal association between SLE and osteoarthritis remains unclear. Knee osteoarthritis (KOA) is the most common form of osteoarthritis. We used two-sample Mendelian randomization to analyze the potential causal relationship between SLE and KOA risk. We downloaded summary data on SLE and KOA from the IEU Open genome-wide association studies database and selected 52 single nucleotide polymorphisms that were independently associated with SLE as genetic IVs. Inverse variance weighted, MR-Egger, weighted median, simple model, and weighted model methods were selected for two-sample Mendelian randomization analysis. Pleiotropy was estimated using MR-Egger regression, MR-PRESSO, and Cochran's Q tests. Finally, sensitivity analysis was performed using the leave-one-out method. The results of all five models showed a significant causal association between SLE and KOA. SLE increased the risk of KOA (odds ratio = 1.012, 95% confidence interval = 1.002–1.023, P = 0.017 using inverse variance weighted analysis), and no significant polymorphism was found. Sensitivity analysis supported that the results were robust. In summary, our study reveals that SLE is an important risk factor for KOA and a potential causal association exists between SLE and KOA. Therefore, controlling SLE may be important for the prevention of KOA.
Framing protocol optimization in oncological Patlak parametric imaging with uKinetics
Authors: Ye Qing , Zeng Hao , Zhao Yizhang , Zhang Weiguang , Dong Yun , Fan Wei , Lu Yihuan 
Published: June 2023

Abstract
Purpose

Total-body PET imaging with ultra-high sensitivity makes high-temporal-resolution framing protocols possible for the first time, which allows to capture rapid tracer dynamic changes. However, whether protocols with higher number of temporal frames can justify the efficacy with substantially added computation burden for clinical application remains unclear. We have developed a kinetic modeling software package (uKinetics). The aim of this work is to verify the uKinetics with PMOD and to perform framing protocol optimization for the oncological Patlak parametric imaging.

Methods

Six different protocols with 100, 61, 48, 29, 19 and 12 temporal frames were applied to analyzing 60-min dynamic 18F-FDG PET scans of 10 patients, respectively. Voxel-based Patlak analysis coupled with image-derived input function was applied to generate parametric images. Normal tissues and lesions were segmented to perform correlation analysis and Bland-Altman plots. Different protocols were compared with the protocol of 100 frames as reference.

Results

Minor differences were found between uKinetics and PMOD in the Patlak parametric imaging. Compared with the protocol with 100 frames, the relative difference of the input function and quantitative kinetic parameters remained low for protocols with at least 29 frames, but increased for the protocols with 19 and 12 frames. Significant difference of lesion Ki values was found between the protocols with 100 frames and 12 frames.

Conclusion

uKinetics was proved providing equivalent oncological Patlak parametric imaging comparing to PMOD. Minor differences were found between protocols with 100 and 29 frames, which indicated that 29 frames is sufficient and efficient for the oncological 18F-FDG Patlak applications, and the protocols with more frames are not needed. The protocol with 19 frames yielded acceptable results, while that with 12 frames is not recommended.
The Impact of Learning Curve on Surgical Performance focused on Achieving Medial Support in Proximal Humeral Fracture: ORIF using locking plate for complex proximal humeral fracture
Authors: Lim Tae Kang , Koh Kyoung Hwan , Kim Hwa Pyung , Shon Min Soo 
Published: June 2023

Abstract
Background: Although the optimal treatment for proximal humeral fractures has not been established yet, open reduction and internal fixation (ORIF) using a locking plate is currently recommended as a viable option. However, such procedures in some cases are technically in demand, and it is more difficult than expected for less experienced beginner surgeons. This study aimed to evaluate with respect to whether the surgical performance, focused on achieving medial support, improved during their learning periods of novice surgeons for open reduction and internal fixation (ORIF) using locking plate of complex proximal humeral fracture.
Methods: This retrospective study was performed on 62 patients who underwent ORIF for complex proximal humeral fractures from three fellowship-trained shoulder specialists in same training institution, who had just started their own clinics in one of the three different institutions. Based on the periodic splitting of 2 groups between the first and subsequent 1-year during the learning curve, we assessed the achievement of medial support as a primary variable. Patient demographics, clinical outcomes, radiological outcomes including technical errors, and complications were also evaluated.
Results: Group A (32 patients) in the first and group B (30 patients) in subsequent 1-year of experience were included in this study. There were no statistically significant differences between the two groups in the demographic data, the distribution of fracture type, and the presence of medial comminution at the time of the injury. The interesting finding was that significant increases in cases that were achieved the medial support (p=0.027) and adequate position of the plate (p=0.008) were seen in Group B than in Group A. However, the periodic splitting of the two groups showed no difference in the clinical results and postoperative stiffness in the final follow-up.
Conclusions: The study showed that the surgical performance regarding the achievement of medial support was improved during the learning curve of the inexperienced surgeon for locking plate fixation in complex proximal humeral fracture. Its recognition as a reference for a significant learning curve effect will play a role in emphasizing the need to focus faster and safely overcome the learning curve.