bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generating normative data from web-based administration of the Cambridge Neuropsychological Test Automated Battery using a Bayesian framework
Authors: Wragg Elizabeth , Skirrow Caroline , Dente Pasquale , Cotter Jack , Annas Peter , Lowther Milly , Backx Rosa , Barnett Jenny , Cree Fiona , Kroll Jasmin , Cormack Francesca 
Published: September 2024

IntroductionNormative cognitive data can distinguish impairment from healthy cognitive function and pathological decline from normal ageing. Traditional methods for deriving normative data typically require extremely large samples of healthy participants, stratifying test variation by pre-specified age groups and key demographic features (age, sex, education). Linear regression approaches can provide normative data from more sparsely sampled datasets, but non-normal distributions of many cognitive test results may lead to violation of model assumptions, limiting generalisability.MethodThe current study proposes a novel Bayesian framework for normative data generation. Participants (n = 728; 368 male and 360 female, age 18–75 years), completed the Cambridge Neuropsychological Test Automated Battery via the research crowdsourcing website Prolific.ac. Participants completed tests of visuospatial recognition memory (Spatial Working Memory test), visual episodic memory (Paired Associate Learning test) and sustained attention (Rapid Visual Information Processing test). Test outcomes were modelled as a function of age using Bayesian Generalised Linear Models, which were able to derive posterior distributions of the authentic data, drawing from a wide family of distributions. Markov Chain Monte Carlo algorithms generated a large synthetic dataset from posterior distributions for each outcome measure, capturing normative distributions of cognition as a function of age, sex and education.ResultsComparison with stratified and linear regression methods showed converging results, with the Bayesian approach producing similar age, sex and education trends in the data, and similar categorisation of individual performance levels.ConclusionThis study documents a novel, reproducible and robust method for describing normative cognitive performance with ageing using a large dataset.
Association between serum estradiol levels and abdominal aortic calcification in postmenopausal woman: a cross-sectional study
Authors: He Lan , Li Xu , Shen E , He Yong-Ming 
Published: September 2024

BackgroundThe association between Estradiol (E2) levels and abdominal aortic calcification (AAC) in postmenopausal women remains unclear.Methods614 postmenopausal women from the 2013-2014 NHANES survey cycle were included in this study. The study population was divided into 3 groups according to E2 tertiles: Tertile1 (2.12-3.57pg/mL), Tertile2 (3.60-7.04pg/mL), and Tertile3 (7.06-38.4pg/mL). Estrogen concentration data were natural logarithmically transformed. A Kauppila score &gt; 5 was regarded as prominent arterial calcification and was used to define (EAAC). Logistic regression models were used to assess the association between E2 levels and EAAC prevalence. Subgroup analyses were performed to test whether the association between E2 levels and EAAC prevalence was consistent in different groups. Sensitivity analyses tested the stability of the model in women older than 45 years.ResultsEAAC prevalence was significantly higher in Tertile1 (16.6%) than in Tertile2 (9.8%) and Tertile3 (8.3%). On a continuous scale, the adjusted model showed a 58% [OR (95%CI), 1.58 (1.02, 2.54)] increase in the risk of EAAC prevalence for per unit decrease in ln(E2). On a categorical scale, the adjusted model showed that Tertile1 and Tertile2 were 2.55 [OR (95%CI), 2.55 (1.10, 5.92)] and 1.31[OR (95%CI), 1.31(1.03, 2.57)] times higher risk of suffering from EAAC than Tertile3, respectively.ConclusionThis study found that a higher prevalence of AAC in postmenopausal women is closely associated with lower serum E2 levels. Our research further underscores the importance of E2 in maintaining cardiovascular health in postmenopausal women and suggests that monitoring E2 levels may aid in the early prevention and management of AAC and related cardiovascular diseases.
Associations between metabolic overweight/obesity phenotypes and mortality risk among patients with chronic heart failure
Authors: Zhou You , Xie Yingli , Dong Jingjing , He Kunlun 
Published: September 2024

BackgroundMetabolic disorders and overweight or obesity are highly prevalent and intricately linked in patients with chronic heart failure (CHF). However, it remains unclear whether there is an interactive effect between these conditions and the prognosis of heart failure, and whether such an interaction is influenced by stratification based on age and sex.MethodsA total of 4,955 patients with CHF were enrolled in this study. Metabolic status was assessed according to the presence or absence of metabolic syndrome (MetS). BMI categories included normal weight and overweight or obesity (BMI &lt; 24, ≥ 24 kg/m2). Patients were divided into four phenotypes according to their metabolic status and BMI: metabolically healthy with normal weight (MHNW), metabolically unhealthy with normal weight (MUNW), metabolically healthy with overweight or obesity (MHO), and metabolically unhealthy with overweight or obesity (MUO). The incidence of primary outcomes, including all-cause and cardiovascular (CV) death, was recorded.ResultsDuring a mean follow-up of 3.14 years, a total of 1,388 (28.0%) all-cause deaths and 815 (16.4%) CV deaths were documented. Compared to patients with the MHNW phenotype, those with the MUNW (adjusted hazard ratio [aHR], 1.66; 95% confidence interval [CI], 1.38–2.00) or MUO (aHR, 1.42 [95% CI, 1.24–1.63]) phenotypes had a greater risk of all-cause death, and those with the MHO phenotype (aHR, 0.61 [95% CI, 0.51–0.72]) had a lower risk of all-cause death. Moreover, the above phenomenon existed mainly among males and elderly females (aged ≥ 60 years). In nonelderly females (aged &lt; 60 years), the detrimental effects of MetS were lower (aHR, 1.05 [95% CI, 0.63–1.75] among MUNW group and aHR, 0.52 [95% CI, 0.34–0.80] among MUO group), whereas the protective effects of having overweight or obesity persisted irrespective of metabolic status (aHR, 0.43 [95% CI, 0.26–0.69] among MHO group and aHR, 0.52 [95% CI, 0.34–0.80] among MUO group). Similar results were obtained in the Cox proportional risk analysis of the metabolic overweight/obesity phenotypes and CV death.ConclusionsIn male and elderly female patients with CHF, the detrimental effects of MetS outweighed the protective benefits of having overweight or obesity. Conversely, in nonelderly females, the protective effects of having overweight or obesity were significantly greater than the adverse impacts of MetS.
Improving availability and utilization of forest inventory and land use map data using Linked Open Data
Authors: Giménez-García José M. , Vega-Gorgojo Guillermo , Ordóñez Cristóbal , Crespo-Lera Natalia , Bravo Felipe 
Published: September 2024

IntroductionModern forestry increasingly relies on the management of large datasets, such as forest inventories and land cover maps. Governments are typically in charge of publishing these datasets, but they typically employ disparate data formats (sometimes proprietary ones) and published datasets are commonly disconnected from other sources, including previous versions of such datasets. As a result, the usage of forestry data is very challenging, especially if we need to combine multiple datasets.Methods and resultsSemantic Web technologies, standardized by the World Wide Web Consortium (W3C), have emerged in the last decades as a solution to publish heterogeneous data in an interoperable way. They enable the publication of self-describing data that can easily interlink with other sources. The concepts and relationships between them are described using ontologies, and the data can be published as Linked Data on the Web, which can be downloaded or queried online. National and international agencies promote the publication of governmental data as Linked Open Data, and research fields such as biosciences or cultural heritage make an extensive use of Semantic Web technologies. In this study, we present the result of the European Cross-Forest project, addressing the integration and publication of national forest inventories and land cover maps from Spain and Portugal using Semantic Web technologies. We used a bottom-up methodology to design the ontologies, with the goal of being generalizable to other countries and forestry datasets. First, we created an ontology for each dataset to describe the concepts (plots, trees, positions, measures, and so on) and relationships between the data in detail. We converted the source data into Linked Open Data by using the ontology to annotate the data such as species taxonomies. As a result, all the datasets are integrated into one place this is the Cross-Forest dataset and are available for querying and analysis through a SPARQL endpoint. These data have been used in real-world use cases such as (1) providing a graphical representation of all the data, (2) combining it with spatial planning data to reveal the forestry resources under the management of Spanish municipalities, and (3) facilitating data selection and ingestion to predict the evolution of forest inventories and simulate how different actions and conditions impact this evolution.DiscussionThe work started in the Cross-Forest project continues in current lines of research, including the addition of the temporal dimension to the data, aligning the ontologies and data with additional well-known vocabularies and datasets, and incorporating additional forestry resources.
1,25-dihydroxyvitamin-D3 distinctly impacts the paracrine and cell-to-cell contact interactions between hPDL-MSCs and CD4+ T lymphocytes
Authors: Behm Christian , Miłek Oliwia , Schwarz Katharina , Rausch-Fan Xiaohui , Moritz Andreas , Andrukhov Oleh 
Published: September 2024

IntroductionHuman periodontal ligament-derived mesenchymal stromal cells (hPDL-MSCs) possess a strong ability to modulate the immune response, executed via cytokine-boosted paracrine and direct cell-to-cell contact mechanisms. This reciprocal interaction between immune cells and hPDL-MSCs is influenced by 1,25-dihydroxyvitamin-D3 (1,25(OH)2D3). In this study, the participation of different immunomodulatory mechanisms on the hPDL-MSCs-based effects of 1,25(OH)2D3 on CD4+ T lymphocytes will be elucidated using different co-culture models with various cytokine milieus.Material and methodshPDL-MSCs and CD4+ T lymphocytes were co-cultured indirectly and directly with inserts (paracrine interaction only) or directly without inserts (paracrine and direct cell-to-cell contact interaction). They were stimulated with TNF-α or IL-1β in the absence/presence of 1,25(OH)2D3. After five days of co-cultivation, the CD4+ T lymphocyte proliferation, viability, and cytokine secretion were analyzed. Additionally, the gene expression of soluble and membrane-bound immunomediators was determined in hPDL-MSCs.ResultsIn the indirect and direct co-culture model with inserts, 1,25(OH)2D3 decreased CD4+ T lymphocyte proliferation and viability. The direct co-culture model without inserts caused the opposite effect. 1,25(OH)2D3 mainly decreased the CD4+ T lymphocyte-associated secretion of cytokines via hPDL-MSCs. The degree of these inhibitions varied between the different co-culture setups. 1,25(OH)2D3 predominantly decreased the expression of the soluble and membrane-bound immunomediators in hPDL-MSCs to a different extent, depending on the co-culture models. The degree of all these effects depended on the absence and presence of exogenous TNF-α and IL-1β.ConclusionThese data assume that 1,25(OH)2D3 differently affects CD4+ T lymphocytes via the paracrine and direct cell-to-cell contact mechanisms of hPDL-MSCs, showing anti- or pro-inflammatory effects depending on the co-culture model type. The local cytokine microenvironment seems to be involved in fine-tuning these effects. Future studies should consider this double-edged observation by executing different co-culture models in parallel.
Whole slide image-based weakly supervised deep learning for predicting major pathological response in non-small cell lung cancer following neoadjuvant chemoimmunotherapy: a multicenter, retrospective, cohort study
Authors: Han Dan , Li Hao , Zheng Xin , Fu Shenbo , Wei Ran , Zhao Qian , Liu Chengxin , Wang Zhongtang , Huang Wei , Hao Shaoyu 
Published: September 2024

ObjectiveDevelop a predictive model utilizing weakly supervised deep learning techniques to accurately forecast major pathological response (MPR) in patients with resectable non-small cell lung cancer (NSCLC) undergoing neoadjuvant chemoimmunotherapy (NICT), by leveraging whole slide images (WSIs).MethodsThis retrospective study examined pre-treatment WSIs from 186 patients with non-small cell lung cancer (NSCLC), using a weakly supervised learning framework. We employed advanced deep learning architectures, including DenseNet121, ResNet50, and Inception V3, to analyze WSIs on both micro (patch) and macro (slide) levels. The training process incorporated innovative data augmentation and normalization techniques to bolster the robustness of the models. We evaluated the performance of these models against traditional clinical predictors and integrated them with a novel pathomics signature, which was developed using multi-instance learning algorithms that facilitate feature aggregation from patch-level probability distributions.ResultsUnivariate and multivariable analyses confirmed histology as a statistically significant prognostic factor for MPR (P-value&lt; 0.05). In patch model evaluations, DenseNet121 led in the validation set with an area under the curve (AUC) of 0.656, surpassing ResNet50 (AUC = 0.626) and Inception V3 (AUC = 0.654), and showed strong generalization in external testing (AUC = 0.611). Further evaluation through visual inspection of patch-level data integration into WSIs revealed XGBoost’s superior class differentiation and generalization, achieving the highest AUCs of 0.998 in training and robust scores of 0.818 in validation and 0.805 in testing. Integrating pathomics features with clinical data into a nomogram yielded AUC of 0.819 in validation and 0.820 in testing, enhancing discriminative accuracy. Gradient-weighted Class Activation Mapping (Grad-CAM) and feature aggregation methods notably boosted the model’s interpretability and feature modeling.ConclusionThe application of weakly supervised deep learning to WSIs offers a powerful tool for predicting MPR in NSCLC patients treated with NICT.
Prognostic implications of tumor-infiltrating lymphocytes in non-small cell lung cancer: a systematic review and meta-analysis
Authors: Yan Qin , Li Shuai , He Lang , Chen Nianyong 
Published: September 2024

BackgroundTumor-infiltrating lymphocytes (TILs) have demonstrated potential as prognostic biomarkers across various cancer types. However, their prognostic implications in non-small cell lung cancer (NSCLC) remain ambiguous.MethodsAn exhaustive electronic search was executed across the Pubmed, EMBASE, Web of Science, and Cochrane Library databases to locate relevant studies published up until December 19, 2023. Studies were eligible if they assessed the association between TILs and overall survival (OS) and disease-free survival (DFS) in NSCLC patients. The OS and DFS were subsequently extracted for analysis. The prognostic significance of TILs was evaluated by calculating the Pooled Hazard Ratios (HRs) and their corresponding 95% Confidence Intervals (CIs).ResultsThe meta-analysis incorporated 60 studies, which collectively included 15829 NSCLC patients. The collective analysis indicated that NSCLC patients exhibiting TILs infiltration demonstrated a significantly improved OS(HR: 0.67; 95%CI: 0.55-0.81). Subgroup analyses, based on TIL subtypes (CD8+, CD3+ and CD4+), consistently revealed a favorable prognostic impact on OS. However, it was observed that FOXP3+ was correlated with a poor OS (HR: 1.35; 95% CI: 0.87-2.11).ConclusionThis comprehensive systematic review and meta-analysis substantiate the prognostic significance of TILs in patients diagnosed with NSCLC. Notably, elevated TILs infiltration correlates with a favorable prognosis, particularly among CD8+, CD3+ and CD4+ subtypes.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023468089 PROSPERO, identifier CRD42023468089.
Assessing the accuracy of CMRtools software for diagnosing liver iron overload in thalassemia patients: influencing factors and optimisation strategies
Authors: Luo Chaotian , Peng Fei , Xu Fengming , Tang Cheng , Zhang Yanyan , Huang Chaojie , Liang Linlin , Ning Xiaojing , Peng Peng 
Published: September 2024

BackgroundCMRtools is a software package that can be used to measure T2* values to diagnose liver iron overload, however, its accuracy in terms is affected by multiple factors, including goodness-of-fit (R2 value), the number of echo time (TE) images, and the liver iron concentration (LIC). To investigate the effects of the R2 value, the number of TE images, and the LIC on the accuracy of CMRtools software for measuring T2* values to diagnose liver iron overload (LIO).Materials and methodsCMRtools software was used to measure liver T2* values among 108 thalassemia patients via the truncation method, and the R2 values, the number of TE images, and T2* values were recorded. These values were subsequently converted into liver iron concentration (LICT) values. The LICF (derived from MRI-R2/FerriScan) was used as a reference, and the diagnostic accordance rate (DAR) was compared between R2 value subgroups, between TE image number subgroups, and between LIC subgroups.ResultsThe greater the R2 value was, the greater the standardized DAR (SDAR) was (p &lt; 0.05). The SDAR are not identical between each TE image number subgroup (p &gt; 0.05). However, the relationship between TE image number subgroups and SDAR was analysed using Spearman’s correlation, and it was found to be positively correlated (rs = 0.729, p = 0.017). The SDAR are not identical between each LIC subgroup (p &gt; 0.05), furthermore, the relationship between LIC subgroup and SDAR was found irrelevant (p = 0.747).ConclusionThe accuracy of CMRtools software for diagnosing LIO in patients with thalassemia can be improved by artificially controlling the number of TE images to be fitted and selecting higher R2 values.
Evaluating the efficacy and safety of various flaps in Autologous Breast Reconstruction: a Bayesian network meta-analysis
Authors: Li Ling , Wu Di , Zhu Xiaohai 
Published: September 2024

AimThis analysis evaluates the efficacy and safety of different flap techniques for Autologous Breast Reconstruction by collecting all clinical trials employing these methods and applying a Bayesian network meta-analysis.Materials and methodsWe systematically searched PubMed, Embase, and Web of Science for relevant literature, focusing on outcomes such as total flap loss, donor site wound dehiscence, secondary corrections at the donor site, psychosocial well-being, satisfaction with breasts, and sexual well-being.ResultsOur analysis included 10 clinical studies involving 871 patients across six flap techniques. In terms of total flap loss, the TUG flap showed the highest SUCRA value (89.6%), followed by the TMG flap (64.8%). For donor site wound dehiscence, the DIEP flap ranked highest with a SUCRA value of 60.1%, followed by the PAP flap (48.6%). In secondary corrections at the donor site, the PAP flap was the leader (95.5%), followed by the DIEP flap (52.5%) and the TMG flap (41.4%). For outcomes related to psychosocial well-being, satisfaction with breasts, and sexual well-being, the Four-flap technique consistently ranked highest (81.3, 85.0, and 88.4%, respectively).ConclusionVarious flap techniques in Autologous Breast Reconstruction each present distinct benefits and risks. The Four-flap technique shows significant advantages in patient satisfaction, while the TUG flap excels in reducing total flap loss.
Gut microbiota-derived acetate promotes long-term recovery through angiogenesis guided by lymphatic ingrowth in older adults with stroke
Authors: Yuan Yujia , Li Linlin , Wang Jingjing , Myagmar Bat-Otgon , Gao Yuxiao , Wang Huan , Wang Zhao , Zhang Cong , Zhang Xiangjian 
Published: September 2024

IntroductionIschemic stroke is a leading cause of morbidity and mortality in older adults. Therefore, in this study, we sought to understand the interplay between the microbiota, gut, and brain in the context of stroke in older adults.ObjectiveTo determine whether gut microbiota from younger individuals promotes recovery through angiogenesis in both elderly stroke patients and aged stroke mice, we explored the changes in gut microbiota and the correlation between short-chain fatty acids (SCFAs) and angiogenesis in the aged stroke population. Then, we altered the gut microbiome in aged mice by transplanting microbiota from younger donors before inducing experimental stroke to explore the mechanism by which gut microbiota-derived SCFAs promote angiogenesis.MethodsPart I: We conducted a single-center, double-blind trial to compare gut microbiota diversity and SCFA levels in fecal samples from older stroke patients with those from younger stroke patients. Additionally, we measured levels of vascular endothelial growth factor (VEGF) and VEGFC levels in plasma to assess their correlation with SCFA levels. Part II: We performed fecal microbiota transplantation (FMT) 3 days before inducing ischemic stroke in aged male mice (16–18) via distal middle cerebral artery occlusion (dMCAO). The FMT was conducted using gut microbiomes from either young donors (2–3 months) or aged donors (16–18 months).ResultsIn older stroke patients, gut microbiota diversity was significantly reduced compared to that in younger stroke patients. Furthermore, levels of acetate, a bacterially derived SCFA, were lower and positively correlated with angiogenesis markers (VEGF and VEGF-C). In aged stroke mice, transplantation of young microbiota improved stroke outcomes by promoting angiogenesis, which was facilitated by lymphatic ingrowth into the cortex. This protective effect was linked to gut microbiota-derived acetate, which enhanced lymphangiogenesis by replenishing acetyl coenzyme A.Conclusions(a) Gut microbiota-derived acetate promotes angiogenesis post-stroke and (b) lymphatic ingrowth into the cerebral cortex was observed in post-dMCAO mice. These findings suggest that selectively promoting SCFA-producing bacteria, particularly acetate-producers, could be a promising therapeutic strategy to reduce functional impairments in older stroke subjects.