bluuebunny/crossref_metadata_2025_split huggingface dataset:
Food Insecurity and Children's Problem Behaviors: The Mediating Role of Parental Relationship Quality and Parenting Stress
Authors: Gong Qiujie , Ju Sehyun 
Published: June 2024

Abstract:

Objective:
Food insecurity, identified as a critical stressor for many families, can directly and indirectly influence children's development through interparental relationships and parenting. This study examines how food insecurity relates to children's problem behaviors and the mediating roles of interparental relationship quality and parenting stress. It also investigates the association between parents' perception of relationship quality and both their own and their partner's parenting stress.

Method:
The study included 2095 children from the Future of Families and Child Wellbeing Study. The actor partner interdependence model was used to explore the actor and partner influence of relationship quality on parents' parenting stress. To examine the association pathways from food insecurity to children's problem behaviors, a structural equation model was conducted.

Results:
Results suggest that fathers' perception of couple relationship quality predicted both their own and their partner's parenting stress while mothers' perception of couple relationship quality only predicted their own, but not fathers', parenting stress. In the positive association between food insecurity and children's problem behaviors, there was a serial mediation through mothers' perception of relationship quality and mothers' parenting stress. In addition, food insecurity was negatively correlated with mothers' perception of relationship quality, but not with that of fathers.

Conclusion:
This study highlights the pathway from food insecurity to children's problem behaviors through mothers' perceptions of interparental relationship quality and parenting stress. Results provide support for the family stress theory and offer valuable insights for the formulation of potential prevention and intervention programs.
Comprehensive profiling of lipid metabolic reprogramming expands precision medicine for HCC
Authors: Liu Qingbin , Zhang Xiangyu , Qi Jingjing , Tian Xinchen , Dovjak Eva , Zhang Jiaqi , Du Honghuan , Zhang Ni , Zhao Jing , Zhang Yiming , Wang Lijuan , Wei Yangang , Liu Chenqiao , Qian Ruikun , Xiang Longquan , Li Weiyang , Xiu Peng , Ma Changlin , Yu Yong , Jiang Shulong 
Published: June 2024

Background and Aims:
Liver HCC is the second leading cause of cancer-related deaths worldwide. The heterogeneity of this malignancy is driven by a wide range of genetic alterations, leading to a lack of effective therapeutic options. In this study, we conducted a systematic multi-omics characterization of HCC to uncover its metabolic reprogramming signature.

Approach and Results:
Through a comprehensive analysis incorporating transcriptomic, metabolomic, and lipidomic investigations, we identified significant changes in metabolic pathways related to glucose flux, lipid oxidation and degradation, and de novo lipogenesis in HCC. The lipidomic analysis revealed abnormal alterations in glycerol-lipids, phosphatidylcholine, and sphingolipid derivatives. Machine-learning techniques identified a panel of genes associated with lipid metabolism as common biomarkers for HCC across different etiologies. Our findings suggest that targeting phosphatidylcholine with saturated fatty acids and long-chain sphingolipid biosynthesis pathways, particularly by inhibiting lysophosphatidylcholine acyltransferase 1 (LPCAT1) and ceramide synthase 5 (CERS5) as potential therapeutic strategies for HCC in vivo and in vitro. Notably, our data revealed an oncogenic role of CERS5 in promoting tumor progression through lipophagy.

Conclusions:
In conclusion, our study elucidates the metabolic reprogramming nature of lipid metabolism in HCC, identifies prognostic markers and therapeutic targets, and highlights potential metabolism-related targets for therapeutic intervention in HCC.
Development and validation of a deep learning model for predicting gastric cancer recurrence based on CT imaging: a multicenter study
Authors: Cao Mengxuan , Hu Can , Li Feng , He Jingyang , Li Enze , Zhang Ruolan , Shi Wenyi , Zhang Yanqiang , Zhang Yu , Yang Qing , Zhao Qianyu , Shi Lei , Xu Zhiyuan , Cheng Xiangdong 
Published: June 2024

Introduction:
The postoperative recurrence of gastric cancer (GC) has a significant impact on the overall prognosis of patients. Therefore, accurately predicting the postoperative recurrence of GC is crucial.

Methods:
This retrospective study gathered data from 2813 GC patients who underwent radical surgery between 2011 and 2017 at two medical centers. Follow-up was extended until May 2023, and cases were categorized as recurrent or nonrecurrent based on postoperative outcomes. Clinical pathological information and imaging data were collected for all patients. A new deep learning signature (DLS) was generated using pretreatment computed tomography images, based on a pretrained baseline (a customized Resnet50), for predicting postoperative recurrence. The deep learning fusion signature (DLFS) was created by combining the score of DLS with the weighted values of identified clinical features. The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. Survival curves were plotted to investigate the differences between DLFS and prognosis.

Results:
In this study, 2813 patients with GC were recruited and allocated into training, internal validation, and external validation cohorts. The DLFS was developed and assessed for its capability in predicting the risk of postoperative recurrence. The DLFS exhibited excellent performance with AUCs of 0.833 (95% CI: 0.809–0.858) in the training set, 0.831 (95% CI: 0.792–0.871) in the internal validation set, and 0.859 (95% CI: 0.806–0.912) in the external validation set, along with satisfactory calibration across all cohorts (P>0.05). Furthermore, the DLFS model significantly outperformed both the clinical model and DLS (P<0.05). High-risk recurrent patients exhibit a significantly poorer prognosis compared to low-risk recurrent patients (P<0.05).

Conclusions:
The integrated model developed in this study, focusing on GC patients undergoing radical surgery, accurately identifies cases at high-risk of postoperative recurrence and highlights the potential of DLFS as a prognostic factor for GC patients.
Association of triglyceride glucose index with stroke: from two large cohort studies and Mendelian randomization analysis
Authors: Jiang Yong’An , Shen Jing , Chen Peng , Cai JiaHong , Zhao YangYang , Liang JiaWei , Cai JianHui , Cheng ShiQi , Zhang Yan 
Published: June 2024

Introduction:
The triglyceride glucose index (TyG) is associated with cardiovascular diseases; however, its association with stroke remains unclear. This study aimed to elucidate this relationship by examining two extensive cohort studies using two-sample Mendelian randomization (MR).

Methods:
Using data from the 1999–2018 National Health and Nutrition Examination Survey (NHANES) and the Medical Information Mart for Intensive Care (MIMIC)-IV, the correlation between TyG (continuous and quartile) and stroke was examined using multivariate Cox regression models and sensitivity analyses. Two-sample MR was employed to establish causality between TyG and stroke using the inverse variance weighting method. Genome-wide association study catalog queries were performed for single nucleotide polymorphism-mapped genes, and the STRING platform used to assess protein interactions. Functional annotation and enrichment analyses were also conducted.

Results:
From the NHANES and MIMIC-IV cohorts, we included 740 and 589 participants with stroke, respectively. After adjusting for covariates, TyG was linearly associated with the risk of stroke death (NHANES: hazard ratio [HR] 0.64, 95% CI: 0.41–0.99, P=0.047; Q3 vs. Q1, HR 0.62, 95% CI: 0.40–0.96, P=0.033; MIMIC-IV: HR 0.46, 95% CI: 0.27–0.80, P=0.006; Q3 vs. Q1, HR 0.32, 95% CI: 0.12–0.86; Q4 vs. Q1, HR 0.30, 95% CI: 0.10–0.89, P=0.030, P for trend=0.017). Two-sample MR analysis showed genetic prediction supported a causal association between a higher TyG and a reduced risk of stroke (odds ratio 0.711, 95% CI: 0.641–0.788, P=7.64e-11).

Conclusions:
TyG was causally associated with a reduced risk of stroke. TyG is a critical factor for stroke risk management.
Three-dimensional deep learning model complements existing models for preoperative disease-free survival prediction in localized clear cell renal cell carcinoma: a multicenter retrospective cohort study
Authors: Xv Yingjie , Wei Zongjie , Jiang Qing , Zhang Xuan , Chen Yong , Xiao Bangxin , Yin Siwen , Xia Zongyu , Qiu Ming , Li Yang , Tan Hao , Xiao Mingzhao 
Published: June 2024

Background:
Current prognostic models have limited predictive abilities for the growing number of localized (stage I–III) ccRCCs. It is, therefore, crucial to explore novel preoperative recurrence prediction models to accurately stratify patients and optimize clinical decisions. The purpose of this study was to develop and externally validate a computed tomography (CT)-based deep learning (DL) model for presurgical disease-free survival (DFS) prediction.

Methods:
Patients with localized ccRCC were retrospectively enrolled from six independent medical centers. Three-dimensional (3D) tumor regions from CT images were utilized as input to architect a ResNet 50 model, which outputted DL computed risk score (DLCR) of each patient for DFS prediction later. The predictive performance of DLCR was assessed and compared to the radiomics model (Rad-Score), the clinical model the authors built and two existing prognostic models (UISS and Leibovich). The complementary value of DLCR to the UISS, Leibovich, as well as Rad-Score were evaluated by stratified analysis.

Results:
Seven hundred seven patients with localized ccRCC were finally enrolled for models’ training and validating. The DLCR the authors established can perfectly stratify patients into low-risks, intermediate-risks, and high-risks, and outperformed the Rad-Score, clinical model, UISS and Leibovich score in DFS prediction, with a C-index of 0.754 (0.689–0.821) in the external testing set. Furthermore, the DLCR presented excellent risk stratification capacity in subgroups defined by almost all clinic-pathological features. Moreover, patients classified as low-risk by the UISS/Leibovich score/Rad-Score but as intermediate - or high-risk by DLCR were significantly more likely to experience ccRCC recurrence than those stratified as intermediate- or high-risk by UISS/Leibovich score/Rad-Score but as low-risk by DLCR (all Log-rank P-values<0.05).

Conclusions:
Our DL model, derived from preoperative CT, is superior to radiomics and current models in precisely DFS predicting of localized ccRCC, and can provide complementary values to them, which may assist more informed clinical decisions and adjuvant therapies adoptions.
Anatomical predispositions for silent cerebral infarction postcarotid artery stenting: a retrospective cohort
Authors: Li Tianhua , Yang Renjie , Wang Jie , Wang Tao , Liu Guangjie , Jin Jiaqi , Bai Xuesong , Xu Ran , Lu Taoyuan , Wang Yabing , Dmytriw Adam A. , Yang Bin , Jiao Liqun 
Published: June 2024

Background:
Silent cerebral infarction (SCI) that manifests following carotid artery stenting (CAS) has been postulated to correlate with cognitive decline, the onset of dementia, and an increased risk of subsequent cerebrovascular events. This investigation aimed to thoroughly examine the potential anatomical predispositions that are linked to the occurrence of SCI post-CAS, and further develop a predictive nomogram that could accurately forecast the risk of SCI post-CAS.

Methods:
The present investigation conducted a retrospective examination of datasets from 250 individuals presenting with carotid artery stenosis who had been subjected to CAS within a tertiary healthcare institution from June 2020 to November 2021. Stratified by the procedural date, participants were allocated into a training cohort and a validation cohort. A nomogram was constructed predicated on salient prognostic determinants discerned via a multivariate logistic regression analysis.

Results:
An aggregate of 184 patients were incorporated into the study, of which 60 (32.6%) manifested SCI, whereas 124 (67.4%) did not. Within the training cohort (n=123), age (OR 1.08, 95% CI: 1.01–1.16; P=0.034), aortic arch type (Type III vs. I: OR 10.79, 95% CI: 2.12–54.81; P=0.005), aortic arch variant (OR 47.71, 95% CI: 6.05–376.09; P<0.001), common carotid artery (CCA) ostium lesions (OR 6.93, 95% CI: 1.49–32.32; P=0.014), and proximal tortuosity index (TI) (OR 1.01, 95% CI: 1.00–1.02; P=0.029) were demarcated as standalone risk predispositions for SCI subsequent to CAS. The concordance index (C-index) for the training cohort's nomogram stood at 0.89 (95% CI: 0.84–0.95). Moreover, the said nomogram exhibited commendable efficacy within the validation cohort (C-index=0.94) as well as the entire participant base (C-index=0.90). Furthermore, the decision curve analysis illustrated the exemplary clinical applicability of the nomogram.

Conclusions:
The findings of this inquiry underscore that age, aortic arch type, aortic arch variant, CCA ostium lesions, and proximal TI serve as independent determinants linked with SCI post-CAS. The formulated nomogram, predicated on these risk factors, possesses robust prognostic significance, and might serve as a valuable adjunct to inform clinical decision-making.
Electronic symptom monitoring after lung cancer surgery: establishing a core set of patient-reported outcomes for surgical oncology care in a longitudinal cohort study
Authors: Yu Hongfan , Lei Cheng , Wei Xing , Wang Yaqin , Xu Wei , Tang Li , Dai Wei , Liao Jia , Pu Yang , Gong Ruoyan , Su Xueyao , Yu Qingsong , Zhang Jiayuan , Zhang Lijun , Huang Yanyan , Zhuang Xiang , Bai Jin , Wang Zhibiao , Li Qiang , Shi Qiuling 
Published: June 2024

Background:
Electronic symptom monitoring via patient-reported outcomes in surgical oncology is limited owing to lengthy instruments and non-specific items in common patient-reported outcome instruments. To establish electronic symptom monitoring through a clinically relevant and fit-for-purpose core set of patient-reported outcome in patients undergoing lung cancer surgery.

Materials and methods:
One qualitative (Cohort 1) and two prospective studies (Cohorts 2 and 3) were conducted between 2018 and 2022. Patients undergoing lung cancer surgery were recruited. Items of symptoms and daily functioning were generated through extensive interviews in Cohort 1 and incorporated into a smartphone-based platform to establish the electronic Perioperative Symptom Assessment for Lung surgery (ePSA-Lung). This instrument was finalized and validated in Cohort 2. Patients in Cohort 3 were longitudinally monitored for the first-year post-surgery using the validated ePSA-Lung.

Results:
In total, 1037 patients scheduled for lung cancer surgery were recruited. The 11-item draft PSA-Lung was generated based on qualitative interview with 39 patients and input from a Delphi study involving 42 experts. A 9-item ePSA-Lung was finalized by assessing 223 patients in the validation cohort; the results supported the instrument’s understandability, reliability, sensitivity, and surgical specificity. In Cohort 3 (n=775), compliance ranged from 63.21 to 84.76% during the 1-year follow-up after discharge. Coughing, shortness of breath, and disturbed sleep were the most severe symptoms after discharge. Longitudinally, patients who underwent single-port video-assisted thoracic surgery had a lower symptom burden than those who underwent multi-port video-assisted thoracic surgery or thoracotomy (all symptoms, P<0.001).

Conclusions:
The ePSA-Lung is valid, concise, and clinically applicable as it supports electronic symptom monitoring in surgical oncology care. The need for long-term extensive care was identified for patients after discharge, even in early-stage cancer with potential curative treatment.
Unaccounted for Pitch Volume Among Adolescent Baseball Pitchers During a Travel Baseball Season
Authors: Salamh Paul A. , Entler Kalie , Parks Meredith , Vrbancic Cassandra , Usui Takumi , Hegedus Eric J. , Cook Chad E. , Bullock Garrett S. 
Published: June 2024

Objective:
The primary aim was to compare differences in live game pitch counts (LGPCs) with all pitch counts (APCs) over the course of a youth baseball season.

Design:
Prospective longitudinal study.

Setting:
Midwest youth travel baseball.

Participants:
Ten male baseball players part of a youth baseball travel team.

Variables:
Demographic data, pitch counts (practice, game, warm-up, and bullpen), innings pitched, and recommended rest days.

Main Outcome Measures:
Live pitch counts compared with APCs and the relationship to recommended rest days.

Results:
During the season, 7866 pitches were recorded among 9 pitchers. By using the LGPC method alone, 42.5% of the pitches were unaccounted for. When considering age-specific rest days suggested by Pitch Smart Guidelines (PSGs), there were 104 rest days unaccounted for by using the live game pitch method.

Conclusion:
There is a high number of unaccounted for pitches and an underestimation of rest days per outing when using live game methods. Revisions to the PSGs that include all pitches should be considered to accurately reflect pitching volume, which may be associated with the rising rate of injuries among these athletes.
Inflammatory Cytokines in Middle Ear Effusion of Patients With Asthma, Chronic Rhinosinusitis With Nasal Polyps With or Without NSAID Intolerance
Authors: Suikkila Anna , Lyly Annina , Savinko Terhi , Vento Seija I. , Saarinen Riitta , Hafrén Lena 
Published: June 2024

Objective
To measure the inflammatory cytokines of middle ear effusion (MEE) in otitis media (OM) associated with asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) with or without nonsteroidal anti-inflammatory drug (NSAID) sensitivity to strengthen our assumption that OM is part of the same inflammatory entity. The potential individual differences between MEE inflammatory cytokines could be used in clinical practice for more individual characterization of the inflammation.

Study Design
Case-control study.

Setting
Tertiary referral center

Patients
Convenience sample of 24 case patients with otitis media with effusion (OME) or chronic otitis media (COM), asthma, and CRSwNP, 14 of whom had NSAID intolerance, and 8 controls with OME but no history of asthma, CRSwNP, or NSAID intolerance.

Intervention
Diagnostic

Main Outcome and Measure
Inflammatory cytokines including interleukins (IL)-4, IL-5, IL-6, IL-13, and interferon gamma (IFN-γ) in middle ear effusion.

Results
The MEE mass fractions of IL-5 (p = 0.003) and IFN-γ (p = 0.048) were higher among our case patients with OME/COM than among the controls. For IL-4 and IL-13, the mass fractions were also higher among the case patients than the controls, but this difference was not statistically significant (p = 0.199 and p = 0.617, respectively). We found no difference between the IL-6 mass fractions of the groups. We found notable heterogeneity in individual patients' cytokine levels.

Conclusions
According to our findings, OM, when present, should be considered part of the respiratory inflammatory process associated with asthma and CRSwNP. The individual differences in MEE cytokine levels could be useful as biomarkers.
The Lactulose Breath Test Can Predict Refractory Gastroesophageal Reflux Disease by Measuring Bacterial Overgrowth in the Small Intestine
Authors: Xu Jing , Qu Qiu , Yang Yu , Yang Jie , Fang Ting , Yin Jiajia , Mo Qiquan , Wu Zihan , Zeng Linran , He Huiping , Fu Jinxiao , Zhou Hongjian , Huang Wei , Yang Hong Ju 
Published: June 2024

Objective:
The diagnosis of RGERD in patients typically involves 24-hour esophageal pH monitoring, but due to its invasiveness and low patient compliance, new screening methods are needed. In this study, a lactulose breath test (LBT) was conducted to detect the growth of small intestine bacteria (SIBO) and explore the potential relationship between LBT and RGERD to identify a new treatment method for RGERD.

Methods:
A total of 178 patients with gastroesophageal reflux were enrolled from June 2020 to December 2022 in the Gastroenterology Department, Building 3, the First Affiliated Hospital of Kunming Medical University; these patients included 96 patients with nonrefractory GERD (NRGERD) and 82 patients with RGERD. The Gerd Q score, reflux symptom index (RSI) score, gastroscopy results, clinical symptoms, and other related indicators were collected. Statistical methods were used to analyze the gathered data.

Results:
The incidence of acid reflux and heartburn in patients with RGERD was significantly greater than that in patients with NRGERD (67.10% vs. 42.70%, P<0.01 and 65.00% vs. 34.40%, P<0.01). The CH4 values of patients with RGERD were significantly greater than those of patients with NRGERD at each time point, and there was a correlation between the CH4 values at 60 min and RGERD (P<0.05). For patients with RGERD, the incidence of abdominal pain, acid regurgitation, and heartburn was greater in the CH4-positive group than in the CH4-negative group (61.90% vs. 57.50%, 69.05% vs. 65.00%, 69.05% vs. 57.50%, P>0.05). The incidence of nausea was also greater in the CH4-positive group than in the CH4-negative group (61.90% vs. 35.00%, P<0.05).

Conclusion:
Increased CH4 levels are correlated with RGERD. In addition, patients with RGERD may develop SIBO after long-term use of PPIs, and interventions involving SIBO could provide new ideas for the treatment of RGERD.
Syndromic genetic causes of pulmonary fibrosis
Authors: Borie Raphaël , Ba Ibrahima , Debray Marie-Pierre , Kannengiesser Caroline , Crestani Bruno 
Published: June 2024

Purpose of review
The identification of extra-pulmonary symptoms plays a crucial role in diagnosing interstitial lung disease (ILD). These symptoms not only indicate autoimmune diseases but also hint at potential genetic disorders, suggesting a potential overlap between genetic and autoimmune origins.

Recent findings
Genetic factors contributing to ILD are predominantly associated with telomere (TRG) and surfactant-related genes. While surfactant-related gene mutations typically manifest with pulmonary involvement alone, TRG mutations were initially linked to syndromic forms of pulmonary fibrosis, known as telomeropathies, which may involve hematological and hepatic manifestations with variable penetrance. Recognizing extra-pulmonary signs indicative of telomeropathy should prompt the analysis of TRG mutations, the most common genetic cause of familial pulmonary fibrosis. Additionally, various genetic diseases causing ILD, such as alveolar proteinosis, alveolar hemorrhage, or unclassifiable pulmonary fibrosis, often present as part of syndromes that include hepatic, hematological, or skin disorders.

Summary
This review explores the main genetic conditions identified over the past two decades.