bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of the minimum dietary diversity for women as a predictor of micronutrient adequacy among lactating women in Ethiopia
Authors: Menber Yonatan , Gashaw Selamawit , Belachew Tefera , Fentahun Netsanet 
Published: September 2024

BackgroundThe Minimum Dietary Diversity for Women (MDD-W) indicator is used as a proxy indicator for assessing micronutrient adequacy among women of the reproductive age group. Variations were observed in studies, and there was also a lack of evidence regarding the performance of this proxy indicator in Ethiopia, a country with diverse dietary consumption practices. This study aimed to validate the performance of the MDD-W in predicting micronutrient intake adequacy among lactating women in Ethiopia.Methods and materialsA community-based cross-sectional study was conducted among randomly selected 457 lactating women in Northwest Ethiopia from February 2 to 18, 2023. A multistage sampling technique was used to select 457 study participants. A single multiphasic interactive 24-h dietary recall was used to collect dietary intake data. Ten food groups were used to compute the Minimum Dietary Diversity for Women, and the Mean Adequacy Ratio was used to assess nutrient intake adequacy. Spearman’s rank correlation test, Cohen’s kappa statistics, and ROC curve analysis were conducted. The optimal cutoff points for Minimum Dietary Diversity for Women were determined by selecting the points that maximized the Youden index.ResultsMDD-W had poor positive correlation (ρ = 0.19, p &lt; 0.001) and poor predictive ability (AUC = 0.62, 95% CI: 0.56, 0.67) (p &lt; 0.001) with the Mean Adequacy Ratio in determining micronutrient intake adequacy. The sensitivity and specificity of the MDD-W in the ≥5 food groups standard cutoff were 25.2 and 82.3%, respectively. The optimal cutoff point for MDD-W to predict micronutrient intake adequacy was ≥3 food groups.ConclusionMinimum Dietary Diversity for Women had a poor correlation and poor predictive ability in predicting micronutrient intake adequacy. The variations noted in studies and differences from the Food and Agriculture Organization recommendations regarding the cutoff and level of performance of MDD-W in defining micronutrient adequacy warrant further investigation.
Association between smoking status and the prognosis of brain metastasis in patients with non-small cell lung cancer
Authors: Zhang Xiaofang , Zeng Weilin , Yan Xingyu , Wang Zheng , Xu Ke , Li Mo , Wang Tianlu , Song Yingqiu 
Published: September 2024

ObjectiveThis study aimed to explore the relationship between smoking status and the interval to brain metastasis in patients with non-small cell lung cancer (NSCLC) and its impact on survival time after brain metastasis.MethodsData were collected from patients with NSCLC with brain metastases who were treated at our centre between January 2005 and December 2017. Clinical indices such as clinicopathological features and smoking status were recorded, and patients were followed up until 1 September 2022. Based on our inclusion and exclusion criteria, 461 patients were analysed and matched using 1:1 propensity score matching. Three balanced groups were formed: non-smoking (n = 113), smoking cessation (n = 113), and smoking (n = 113). The interval to brain metastasis and overall survival were compared between the groups.ResultsThere was a statistically significant difference in the interval to brain metastasis between the non-smoking and smoking cessation groups (p = 0.001), as well as between the non-smoking and smoking groups (p &lt; 0.001). However, the difference between the smoking cessation and smoking groups was not statistically significant (p = 0.106). Multivariate and univariate analyses identified smoking status, clinical stage, lung cancer surgery, chemotherapy, and chest radiotherapy as independent predictors of the interval to brain metastasis. Additionally, the multivariate analysis showed that smoking status, driver gene mutations, and chest radiotherapy independently influenced survival after brain metastasis.ConclusionSmoking status in patients with NSCLC affects the interval to brain metastasis and survival after brain metastasis.
A clinical prediction model for distant metastases of pediatric neuroblastoma: an analysis based on the SEER database
Authors: Yan Zhiwei , Wu Yumeng , Chen Yuehua , Xu Jian , Zhang Xiubing , Yin Qiyou 
Published: September 2024

BackgroundPatients with distant metastases from neuroblastoma (NB) usually have a poorer prognosis, and early diagnosis is essential to prevent distant metastases. The aim was to develop a machine-learning model for predicting the risk of distant metastasis in patients with neuroblastoma to aid clinical diagnosis and treatment decisions.MethodsWe built a predictive model using data from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2018 on 1,542 patients with neuroblastoma. Seven machine-learning methods were employed to forecast the likelihood of neuroblastoma distant metastases. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for building machine learning models. Secondly, the subject operating characteristic area under the curve (AUC), Precision-Recall (PR) curves, decision curve analysis (DCA), and calibration curves were used to assess model performance. To further explain the optimal model, the Shapley summation interpretation method (SHAP) was applied. Ultimately, the best model was used to create an online calculator that estimates the likelihood of neuroblastoma distant metastases.ResultsThe study included 1,542 patients with neuroblastoma, multifactorial logistic regression analysis showed that age, histology, tumor size, tumor grade, primary site, surgery, chemotherapy, and radiotherapy were independent risk factors for distant metastasis of neuroblastoma (P &lt; 0.05). Logistic regression (LR) was found to be the optimal algorithm among the seven constructed, with the highest AUC values of 0.835 and 0.850 in the training and validation sets, respectively. Finally, we used the logistic regression model to build a network calculator for distant metastasis of neuroblastoma.ConclusionThe study developed and validated a machine learning model based on clinical and pathological information for predicting the risk of distant metastasis in patients with neuroblastoma, which may help physicians make clinical decisions.
Exploring bleeding in oral anticoagulant users: assessing incidence by indications and risk factors in the entire nationwide cohort
Authors: Jeong Jonghyun , Heo Kyu-Nam , Lee Suhyun , Ah Young-Mi , Min Sangil , Han Ji Min , Lee Ju-Yeun 
Published: September 2024

BackgroundOral anticoagulants (OACs) are essential for the prevention and treatment of thromboembolic disorders, but bleeding, a major complication, can have a fatal impact on the patient’s treatment.ObjectivesWe aimed to estimate the nationwide, real-world incidence rate of bleeding in patients taking OACs and confirm the incidence by indications and risk factors.MethodsThis cross-sectional study identified OAC users from April 1 to December 31, in both 2019 and 2020, using the HIRA-NPS database. The primary outcome variables were the incidence rate of major bleeding events during OAC treatment and within 30 days of treatment discontinuation. We estimated the adjusted incidence rate ratio (aIRR) in subpopulations.ResultsAmong 18,822 OAC users, the incidence rate of major bleeding was 27.9 (95% CI: 24.6–31.5) per 1,000 person-years. The incidence rate of major bleeding was higher in patients with a bleeding history, with an aIRR of 11.51; those at high bleeding risk (HAS-BLED score ≥3), with an aIRR of 1.51; those with high CCI scores ≥3, with an aIRR of 1.88; and those with liver disease, with an aIRR of 1.41. For indications, compared to patients with nonvalvular atrial fibrillation (NVAF), the aIRR of major bleeding was significantly higher at an aIRR of 2.35 in patients undergoing VTE treatment. Patients with ischemic stroke showed a higher incidence of major bleeding with an aIRR of 2.13 than NVAF patients. The aIRR of major bleeding in the oral anticoagulant group, compared to the matched control group, was 2.25 (95% CI: 1.93–2.63).ConclusionThese findings may be useful for implementing strategies to improve the evaluation and management of anticoagulation-related bleeding.
Construction of an interpretable model for predicting survival outcomes in patients with middle to advanced hepatocellular carcinoma (≥5 cm) using lasso-cox regression
Authors: Li Han , Yang Bo , Wang Chenjie , Li Bo , Han Lei , Jiang Yi , Song Yanqiong , Wen Lianbin , Rao Mingyue , Zhang Jianwen , Li Xueting , He Kun , Han Yunwei 
Published: September 2024

BackgroundIn this retrospective study, we aimed to identify key risk factors and establish an interpretable model for HCC with a diameter ≥ 5 cm using Lasso regression for effective risk stratification and clinical decision-making.MethodsIn this study, 843 patients with advanced hepatocellular carcinoma (HCC) and tumor diameter ≥ 5 cm were included. Using Lasso regression to screen multiple characteristic variables, cox proportional hazard regression and random survival forest models (RSF) were established. By comparing the area under the curve (AUC), the optimal model was selected. The model was visualized, and the order of interpretable importance was determined. Finally, risk stratification was established to identify patients at high risk.ResultLasso regression identified 8 factors as characteristic risk factors. Subsequent analysis revealed that the lasso-cox model had AUC values of 0.773, 0.758, and 0.799, while the lasso-RSF model had AUC values of 0.734, 0.695, and 0.741, respectively. Based on these results, the lasso-cox model was chosen as the superior model. Interpretability assessments using SHAP values indicated that the most significant characteristic risk factors, in descending order of importance, were tumor number, BCLC stage, alkaline phosphatase (ALP), ascites, albumin (ALB), and aspartate aminotransferase (AST). Additionally, through risk score stratification and subgroup analysis, it was observed that the median OS of the low-risk group was significantly better than that of the middle- and high-risk groups.ConclusionWe have developed an interpretable predictive model for middle and late HCC with tumor diameter ≥ 5 cm using lasso-cox regression analysis. This model demonstrates excellent prediction performance and can be utilized for risk stratification.
Determinants of bone mineral density in various regions of the skeleton among smokers and non-smokers: the role of physical activity
Authors: Kopiczko Anna , Czapla Michał , Kubielas Grzegorz , Uchmanowicz Bartosz 
Published: September 2024

BackgroundThe adult human skeleton is composed of cortical and cancellous bone. The proportions of these two types of bone tissue differ in various parts of the skeleton. The aim of this cross-sectional study was to quantify the determinants of bone mineral density (BMD) and bone mineral content in various regions of interest (ROIs) in smokers and never-smokers.MethodsIn this study, 4,332 bone scans of three regions of interest (ROIs) were analyzed: the forearm (distal and proximal), femur, and lumbar spine. Body composition and bone parameters were measured using dual-energy X-ray absorptiometry. Smoking was measured using the Global Adult Tobacco Survey questionnaire. Body mass index (BMI) was calculated, and physical activity (PA) was characterized by the metabolic equivalent of task (MET).ResultsAmong women, the interaction between PA (positive β coefficient) and smoking (negative β coefficient) was a significant predictor of BMD in the distal and proximal forearm (adj. R2 = 0.40 and R2 = 0.58; p &lt; 0.001). The interaction of three variables—age, smoking (negative β), and MET (positive β)—was significant for total hip BMD (adj. R2 = 0.54; p &lt; 0.001). The interaction between BMI and MET (positive β) and smoking (negative β) was significant for BMD in the lumbar spine (adj. R2 = 0.62; p &lt; 0.001). In men, the interaction between MET (positive β) and smoking (negative β) was significant for BMD in the forearm and lumbar spine (adj. R2 = 0.44, R2 = 0.46, and R2 = 0.49; p &lt; 0.01). Smoking alone was a significant negative predictor of total hip BMD (adj. R2 = 0.34; p &lt; 0.001).ConclusionAmong both women and men, never-smokers had significantly better bone parameters than smokers. Smoking was a significant negative predictor for BMD in the various ROIs in both women and men. Physical activity was a significant positive predictor of BMD, with a strong association with bone parameters.
A survey of cranberry fruit rots in commercial production beds in Oregon and Washington
Authors: Valentine Don C. , Bouska Cassie , Stockwell Virginia O. 
Published: September 2024

IntroductionFungal fruit rots are a perennial threat to the production of cranberries. Eleven genera of fungi have been reported to cause cranberry rot in the field and/or during cold storage. Oregon and Washington rank fourth and fifth in the production of cranberries in the USA, but much of the research on cranberry fruit rots has been conducted in Wisconsin, New Jersey, and Massachusetts.ObjectiveThe primary objective of this project was to describe the current composition of cranberry fruit rot complex in Oregon and Washington.MethodsA survey of fungal fruit rot pathogens was conducted over four years in commercial cranberry farms located in the Pacific Ocean coastal zone in Oregon and Washington.ResultsYield, rot incidence, and fungal pathogens isolated varied year-to-year. Pathogens isolated frequently from field-rotted cranberries included the cranberry fruit rot genera described in other cranberry production regions of the USA, such as Colletotrichum, Coleophoma, and Physalospora. Neofabraea actinidiae, a recently described cranberry fruit rot, was isolated consistently from field-rotted cranberries from beds with specific fungicide usage patterns. N. actinidiae also was one of the more common storage rot pathogens in this region, alongside other well-established storage rots like Coleophoma and black rots caused by Allantophomopsis cytisporea, A. lycopodina, and Strasseria geniculata.ConclusionsThese findings may have important implications for Washington cranberry production because a large proportion of the crop is dry-harvested, placed in cold storage, and then sold as fresh cranberries. Climatic differences among the cranberry production areas across the United States may affect the disease incidence and prevalence of different genera of cranberry fruit rot pathogens, as summer months in Oregon and Washington are often much cooler and dryer than in Wisconsin and east coast states and may account for differing presence of various cranberry fruit rot fungi.
Root exudates facilitate the regulation of soil microbial community function in the genus Haloxylon
Authors: Wu Deyan , He Xuemin , Jiang Lamei , Li Wenjing , Wang Hengfang , Lv Guanghui 
Published: September 2024

IntroductionRoot exudates act as the "language" of plant-soil communication, facilitating crucial interactions, information exchange, and energy transfer between plants and soil. The interactions facilitated by root exudates between plants and microorganisms in the rhizosphere are crucial for nutrient uptake and stress resilience in plants. However, the mechanism underlying the interaction between root exudates and rhizosphere microorganisms in desert plants under drought conditions remains unclear, especially among closely related species.MethodsTo reveal the ecological strategies employed by the genus Haloxylon in different habitats. Using DNA extraction and sequencing and UPLC-Q-Tof/MS methods, we studied root exudates and soil microorganisms from two closely related species, Haloxylon ammodendron (HA) and Haloxylon persicum (HP), to assess differences in their root exudates, soil microbial composition, and interactions.ResultsSignificant differences were found in soil properties and root traits between the two species, among which soil water content (SWC) and soil organic carbon (SOC) in rhizosphere and bulk soils (P &lt; 0.05). While the metabolite classification of root exudates was similar, their components varied, with terpenoids being the main differential metabolites. Soil microbial structure and diversity also exhibited significant differences, with distinct key species in the network and differential functional processes mainly related to nitrogen and carbon cycles. Strong correlations were observed between root exudate-mediated root traits, soil microorganisms, and soil properties, although the complex interactions differed between the two closely relative species. The primary metabolites found in the network of HA include sugars and fatty acids, while HP relies on secondary metabolites, steroids and terpenoids.DiscussionThese findings suggest that root exudates are key in shaping rhizosphere microbial communities, increasing microbial functionality, fostering symbiotic relationships with hosts, and bolstering the resilience of plants to environmental stress.
Healthcare can’t stop evolving: innovation as the catalyst for unleashing the managerial potential of value-based healthcare by stimulating intangible assets and enhancing organizational resilience
Authors: Gaspary João Francisco Pollo , Gerhardt Vinícius Jaques , de Freitas Michelin Claudia , Lopes Luis Felipe Dias , Rosa Carmen Brum , Siluk Julio Cezar Mairesse 
Published: September 2024

BackgroundWith increasing healthcare service utilization and the introduction of costly therapies, healthcare organizations are pressured to deliver cost-effective services within constrained budgets. Rising costs and the need for efficient healthcare delivery are major concerns for governments, insurers, and health plans.ObjectivesIt aims to understand the impact of these intangible assets on creating value and organizational resilience in healthcare, informing better practices and strategies for VBHC implementation.MethodsAn applied research approach using the Work Breakdown Structure (WBS) methodology was adopted. The research was divided into seven interconnected Work Packages (WPs), each designed to investigate different aspects of the integration between VBHC and intangible assets, with a focus on enhancing organizational resilience through innovative health processes. Key methodologies included literature reviews and qualitative analyses, employing Open Innovation and Design Thinking.ResultsThe study revealed a dynamic interplay between VBHC, organizational resilience, and intangible assets. It showed that managerial effectiveness is influenced by direct patient outcomes and elements like intellectual capital and organizational reputation. Data integration from various Work Packages provided new insights into how intangible assets underpin VBHC strategies, proposing novel management approaches. Findings highlight the essential role of intangible assets in enhancing service delivery and fostering sustainable healthcare practices.DiscussionThe study highlights a significant oversight in the integration of intangible assets within healthcare organizations, despite their crucial role in optimizing VBHC. It supports literature emphasizing the importance of intellectual capital and organizational culture in enhancing healthcare management efficiency and resilience. A paradigm shift in VBHC to include these assets is needed for building a more adaptable and sustainable healthcare system. This integration can lead to better clinical outcomes, patient satisfaction, and overall healthcare efficiency, aligning more closely with VBHC goals.ConclusionRecognizing and effectively managing intangible assets are paramount for the successful implementation of VBHC and enhanced organizational resilience. Strategic integration of these assets into healthcare management practices can significantly improve patient outcomes and create a more sustainable, patient-centered, and resilient healthcare system. Future studies should develop methodologies for robust measurement and integration of these assets to fully realize the potential of VBHC.
Intron retention as an excellent marker for diagnosing depression and for discovering new potential pathways for drug intervention
Authors: Okada Norihiro , Oshima Kenshiro , Maruko Akiko , Sekine Mariko , Ito Naoki , Wakasugi Akino , Mori Eiko , Odaguchi Hiroshi , Kobayashi Yoshinori 
Published: September 2024

BackgroundPeripheral inflammation is often associated with depressive disorders, and immunological biomarkers of depression remain a focus of investigation.MethodsWe performed RNA-seq analysis of RNA transcripts of human peripheral blood mononuclear cells from a case-control study including subjects with self-reported depression in the pre-symptomatic state of major depressive disorder and analyzed differentially expressed genes (DEGs) and the frequency of intron retention (IR) using rMATS.ResultsAmong the statistically significant DEGs identified, the 651 upregulated DEGs were particularly enriched in the term “bacterial infection and phagocytosis”, whereas the 820 downregulated DEGs were enriched in the terms “antigen presentation” and “T-cell proliferation and maturation”. We also analyzed 158 genes for which the IR was increased (IncIR) and 211 genes for which the IR was decreased (DecIR) in the depressed subjects. Although the Gene Ontology terms associated with IncIR and DecIR were very similar to those of the up- and downregulated genes, respectively, IR genes appeared to be particularly enriched in genes with sensor functions, with a preponderance of the term “ciliary assembly and function”. The observation that IR genes specifically interact with innate immunity genes suggests that immune-related genes, as well as cilia-related genes, may be excellent markers of depression. Re-analysis of previously published RNA-seq data from patients with MDD showed that common IR genes, particularly our predicted immune- and cilia-related genes, are commonly detected in populations with different levels of depression, providing validity for using IR to detect depression.ConclusionDepression was found to be associated with activation of the innate immune response and relative inactivation of T-cell signaling. The DEGs we identified reflect physiological demands that are controlled at the transcriptional level, whereas the IR results reflect a more direct mechanism for monitoring protein homeostasis. Accordingly, an alteration in IR, namely IncIR or DecIR, is a stress response, and intron-retained transcripts are sensors of the physiological state of the cytoplasm. The results demonstrate the potential of relative IR as a biomarker for the immunological stratification of depressed patients and the utility of IR for the discovery of novel pathways involved in recovery from depression.