bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping temporal evolution through spatial distances: exploring the diachronic variation in Chinese analytic causative constructions across seven centuries
Authors: Tian Xiaoyu , Speelman Dirk , Zhang Weiwei
Published: November 2024

Previous research has extensively discussed the grammaticalisation of Chinese analytic causative markers, yet no study has empirically examined the contextual features that constrain their choice over different historical periods. In light of this gap in the research, this study uses three exploratory quantitative methods, namely Hierarchical Cluster Analysis, Multi-dimensional Scaling Analysis, and Multiple Correspondence Analysis, to analyse 10,817 observations of analytic causative constructions with shi ([Formula: see text]), ling ([Formula: see text]), jiao1 ([Formula: see text]) and jiao2 ([Formula: see text]) as causative markers from the fourteenth to the twentieth century. Our analyses reveal distinct usage patterns of these markers and we effectively delineate their contextual features through the incorporation of eight syntactic and semantic variables. Our findings not only enhance the understanding of Chinese analytic causative constructions from the fourteenth to the twentieth century, but also provide corroborative evidence for previous research on synchronic variation.
Mujeres y diálogo de saberes para la soberanía alimentaria en comunidades mexicanas
Authors: Chávez Mejía María Cristina , Guadarrama Martínez Noemi , Hutrón Gutiérrez Liliana
Published: November 2024

Ante la crisis ambiental, dietas homogenizadas y pérdida de conocimientos tradicionales, es importante entender el papel de las mujeres para la conservación de agrobiodiversidad y la soberanía alimentaria. El objetivo fue identificar el diálogo de saberes entre mujeres rurales e instituciones de educación y desarrollo, para revalorizar y visibilizar sus conocimientos tradicionales en torno a la agrobiodiversidad, así como su contribución a la soberanía alimentaria. La investigación se llevó a cabo en ocho comunidades del municipio de Ixtlahuaca, mediante técnicas etnográficas, se observó el uso y manejo de la agrobiodiversidad a partir del diálogo de saberes. Los resultados muestran que el diálogo de saberes permite innovar en la producción de alimentos, rescatar plantas alimenticias locales y visibilizar los conocimientos tradicionales femeninos. El diálogo de saberes es clave para valorar y aprovechar estos conocimientos tradicionales femeninos a nivel local para la conservación de la agrobiodiversidad como parte de la soberanía alimentaria
Design and evaluation of a ball spline wasp-inspired needle
Authors: Bloemberg Jette , Fung-A-Jou Zola , Breedveld Paul , Sakes Aimée
Published: November 2024

In percutaneous interventions, needles are used to reach target locations inside the body. However, when the needle is pushed through the tissue, forces arise at the needle tip and along the needle body, making the needle prone to buckling. Recently, needles that prevent buckling inspired by the ovipositor of female parasitic wasps have been developed. Building on these needle designs, this study proposes a manual actuation unit that allows the operator to drive the wasp-inspired needle through stationary tissue. The needle consists of six 0.3-mm spring steel wires, of which one is advanced while the others are retracted. The advancing needle segment has to overcome a cutting and friction force while the retracting ones experience a friction force in the opposite direction. The actuation unit moves the needle segments in the required sequence using a low-friction ball spline mechanism. The moving components of the needle have low inertia, and its connection to the actuation unit using a ball spline introduces a small friction force, generating a small push force on the needle that facilitates the needle’s propulsion into tissue while preventing needle buckling. Experimental testing evaluated the needle’s ability to move through stationary 15-wt% gelatin tissue phantoms for different actuation velocities. It was found that the needle moved through the tissue phantoms with mean slip ratios of 0.35, 0.31, and 0.29 for actuation velocities of π, 2π, and 3π rad/s, respectively. Furthermore, evaluation in 15-wt%, 10-wt%, and 5-wt% gelatin tissue phantoms showed that decreasing the gelatin concentration decreased the mean slip ratios from 0.35 to 0.19 and 0.18, respectively. The needle actuation system design is a step forward in developing a wasp-inspired needle for percutaneous procedures that prevents buckling.
Antibiotics combined with vaginal probiotics in the embryo transfer cycle of infertile patients with chronic endometritis
Authors: Hu Ping , Chen Mengyue , Zhu Lu , Song Bing , Wang Chao , He Xiaojin , Li Guanjian , Cao Yunxia
Published: November 2024

Introduction

Chronic endometritis (CE) is a prolonged, mild inflammation of the endometrial lining. This study investigated the impact of the impact of antibiotic treatment combined with vaginal Lactobacillus on pregnancy outcomes in infertile patients with CE during frozen embryo transfer (FET) cycles.

Methods

A retrospective analysis was performed on the clinical data of 7,385 patients who underwent FET. After applying the inclusion and exclusion criteria, 254 patients diagnosed with CE were eligible for inclusion. Of these, 119 patients received antibiotics alone, whereas 135 were treated with a combination of doxycycline and vaginal Lactobacillus. All patients underwent embryo transfer within 6 months following treatment. The general characteristics and pregnancy outcomes of the first FET cycle post-treatment were compared between the two groups.

Results

There were no statistically significant differences between the two groups in terms of general characteristics, clinical pregnancy rate, early miscarriage rate, and ectopic pregnancy rate. Patients who received a combination of doxycycline and Lactobacillus showed a higher biochemical pregnancy rate compared to those who received doxycycline alone, though this difference was not statistically significant (70.37% vs. 64.71%, P=0.313). Furthermore, the incidence rate of premature rupture of membranes was lower in the doxycycline-Lactobacillus group than in the doxycycline group (50.00% vs 33.33%, P=0.037).

Conclusions

Although this study observed the potential benefits of the antibiotic and vaginal probiotic treatment regimen in increasing the biochemical pregnancy rate and reducing the incidence of premature rupture of membranes, the current findings are insufficient to recommend the combined use of antibiotics and vaginal Lactobacillus as an intervention to improve reproductive outcomes in infertile patients with CE.
Effect of high-intensity intermittent rehabilitation training on physical function, gut microbiome and metabolite after percutaneous coronary intervention in patients with coronary heart disease
Authors: Jiang Lei , Liu Pu , Wang Mei , Deng Qiufeng , Wang Jiangpeng , Jiang Yan , Zhu Ye , Meng Haoyu , Lu Xiao , Kong Xiangqing , Chen Leilei
Published: November 2024

Background

Postoperative rehabilitation exercise training after percutaneous coronary intervention (PCI) is crucial for coronary heart disease (CHD) patients in restoring health and preventing recurrence, including high-intensity interval training (HIIT). However, the impact of HIIT on cardiopulmonary function, gut microbiome and metabolite remains underexplored.

Methods

This study included 60 patients with CHD who underwent percutaneous coronary intervention (PCI). Participants were divided into two groups: 33 in the moderate-intensity continuous training (MCT) group and 27 in the high-intensity interval training (HIIT) group. We assessed difference between two training in cardiopulmonary function, 6-minute walk test (6MWT) performance, biochemical indicators, plasma metabolites, and gut microbiome feature at baseline and after 3 months training. Furthermore, we analyzed 6MWT association to gut microbiome and metabolites with group differences.

Results

The 6MWT showed significantly greater improvement in the HIIT group compared to the MCT group (P = 0.0024). Both groups showed reductions in low-density lipoprotein (LDL) levels and increases in peak oxygen uptake (VO2 peak) after training, but the HIIT group demonstrated a larger effect size in these measures. Moreover, subgroup analysis revealed that patients with a history of myocardial infarction (MI) in the HIIT group experienced a more substantial increase in VO2 peak compared to the MCT group (P = 0.04). In addition, we identified 29 gut microbial species and 30 plasma metabolites that were differentially enriched between the two groups, with some showing a significant impact on 6MWT performance.

Conclusions

High-intensity interval training significantly improves 6MWT performance and exercise tolerance in cardiac rehabilitation patients, particularly enhancing VO2 peak in those with a history of MI. HIIT also appears to modulate the gut microbiome, increasing the abundance of Clostridiales and decreasing traumatic acid content, which may contribute to the observed improvements in exercise tolerance.
Enhancing sentiment and intent analysis in public health via fine-tuned Large Language Models on tobacco and e-cigarette-related tweets
Authors: Elmitwalli Sherif , Mehegan John , Gallagher Allen , Alebshehy Raouf
Published: November 2024

Background

Accurate sentiment analysis and intent categorization of tobacco and e-cigarette-related social media content are critical for public health research, yet they necessitate specialized natural language processing approaches.

Objective

To compare pre-trained and fine-tuned Flan-T5 models for intent classification and sentiment analysis of tobacco and e-cigarette tweets, demonstrating the effectiveness of pre-training a lightweight large language model for domain specific tasks.

Methods

Three Flan-T5 classification models were developed: (1) tobacco intent, (2) e-cigarette intent, and (3) sentiment analysis. Domain-specific datasets with tobacco and e-cigarette tweets were created using GPT-4 and validated by tobacco control specialists using a rigorous evaluation process. A standardized rubric and consensus mechanism involving domain specialists ensured high-quality datasets. The Flan-T5 Large Language Models were fine-tuned using Low-Rank Adaptation and evaluated against pre-trained baselines on the datasets using accuracy performance metrics. To further assess model generalizability and robustness, the fine-tuned models were evaluated on real-world tweets collected around the COP9 event.

Results

In every task, fine-tuned models performed much better than pre-trained models. Compared to the pre-trained model's accuracy of 0.33, the fine-tuned model achieved an overall accuracy of 0.91 for tobacco intent classification. The fine-tuned model achieved an accuracy of 0.93 for e-cigarette intent, which is higher than the accuracy of 0.36 for the pre-trained model. The fine-tuned model significantly outperformed the pre-trained model's accuracy of 0.65 in sentiment analysis, achieving an accuracy of 0.94 for sentiments.

Conclusion

The effectiveness of lightweight Flan-T5 models in analyzing tweets associated with tobacco and e-cigarette is significantly improved by domain-specific fine-tuning, providing highly accurate instruments for tracking public conversation on tobacco and e-cigarette. The involvement of domain specialists in dataset validation ensured that the generated content accurately represented real-world discussions, thereby enhancing the quality and reliability of the results. Research on tobacco control and the formulation of public policy could be informed by these findings.
Leaving against medical advice: a mixed method study to explore the prevalence, causes, and challenges in the emirates health services' hospitals
Authors: Alshamsi Amna I. , Abuquta Alaa , Ibrahim Alaedin , AlSaadi Amna , Altaee Esam , AlAli Najlaa
Published: November 2024

Objective

This study investigated the common reasons for leaving against medical advice (LAMA) at Emirates Health Services (EHS) by comparing electronic medical records (EMR) with healthcare professionals' (HCPs) stated reasons and understanding the challenges faced by HCPs in such cases. We also explored patient-related factors associated with LAMA based on HCP interviews to improve patients' outcome.

Methods

This mixed-method study used EMR data and HCP interviews from four EHS public hospitals with LAMA rates of >2%. EMR variables, including nationality, personal and social reasons, financial reasons, sex, and triage classifications, were dummy-coded and tested using the chi-squared test. Twenty interviews were conducted and analyzed using thematic analysis (TA).

Results

Quantitative data revealed that 5,521 patients left against medical advice in the four hospitals over 6 months. The average age of these patients was 35.1 years (SD = 22.4), and 61.3% were male. Personal and social reasons accounted for 65.7% of the patients who opted for LAMA, and 69.9% were classified as triage 3. There was a significant association between Emiratis and non-Emiratis LAMA and triage category reasons X2 (1) = 138.1, p ≤ 0.001. The odds ratios indicated that Emiratis with triage 3–5 were 2.7 times more likely to leave (95% confidence interval: 2.37–3.38) than non-Emiratis. TA identified two main themes as strategies for managing LAMA: reasons for LAMA and outcomes of LAMA.

Discussion

The results highlight the perspective of HCPs on the reasons for LAMA, providing insights for developing interventions to influence patient decisions and enhance health outcomes. Interventions may include enhancing HCP-patient communication and educating patients on adherence to medical advice. In conclusion, EHS needs strategies to improve LAMA among patients despite of their nationality.
Predicting patients with septic shock and sepsis through analyzing whole-blood expression of NK cell-related hub genes using an advanced machine learning framework
Authors: Du Chao , Tan Stephanie C. , Bu Heng-Fu , Subramanian Saravanan , Geng Hua , Wang Xiao , Xie Hehuang , Wu Xiaowei , Zhou Tingfa , Liu Ruijin , Xu Zhen , Liu Bing , Tan Xiao-Di
Published: November 2024

Background

Sepsis is a life-threatening condition that causes millions of deaths globally each year. The need for biomarkers to predict the progression of sepsis to septic shock remains critical, with rapid, reliable methods still lacking. Transcriptomics data has recently emerged as a valuable resource for disease phenotyping and endotyping, making it a promising tool for predicting disease stages. Therefore, we aimed to establish an advanced machine learning framework to predict sepsis and septic shock using transcriptomics datasets with rapid turnaround methods.

Methods

We retrieved four NCBI GEO transcriptomics datasets previously generated from peripheral blood samples of healthy individuals and patients with sepsis and septic shock. The datasets were processed for bioinformatic analysis and supplemented with a series of bench experiments, leading to the identification of a hub gene panel relevant to sepsis and septic shock. The hub gene panel was used to establish a novel prediction model to distinguish sepsis from septic shock through a multistage machine learning pipeline, incorporating linear discriminant analysis, risk score analysis, and ensemble method combined with Least Absolute Shrinkage and Selection Operator analysis. Finally, we validated the prediction model with the hub gene dataset generated by RT-qPCR using peripheral blood samples from newly recruited patients.

Results

Our analysis led to identify six hub genes (GZMB, PRF1, KLRD1, SH2D1A, LCK, and CD247) which are related to NK cell cytotoxicity and septic shock, collectively termed 6-HubGss. Using this panel, we created SepxFindeR, a machine learning model that demonstrated high accuracy in predicting sepsis and septic shock and distinguishing septic shock from sepsis in a cross-database context. Remarkably, the SepxFindeR model proved compatible with RT-qPCR datasets based on the 6-HubGss panel, facilitating the identification of newly recruited patients with sepsis and septic shock.

Conclusions

Our bioinformatic approach led to the discovery of the 6-HubGss biomarker panel and the development of the SepxFindeR machine learning model, enabling accurate prediction of septic shock and distinction from sepsis with rapid processing capabilities.
A comprehensive neuroimaging review of the primary and metastatic brain tumors treated with immunotherapy: current status, and the application of advanced imaging approaches and artificial intelligence
Authors: Liu Xiang , Chen Hongyan , Tan Guirong , Zhong Lijuan , Jiang Haihui , Smith Stephen M. , Wang Henry Z.
Published: November 2024

Cancer immunotherapy has emerged as a novel clinical therapeutic option for a variety of solid tumors over the past decades. The application of immunotherapy in primary and metastatic brain tumors continues to grow despite limitations due to the physiological characteristics of the immune system within the central nervous system (CNS) and distinct pathological barriers of malignant brain tumors. The post-immunotherapy treatment imaging is more complex. In this review, we summarize the clinical application of immunotherapies in solid tumors beyond the CNS. We provide an overview of current immunotherapies used in brain tumors, including immune checkpoint inhibitors (ICIs), oncolytic viruses, vaccines, and CAR T-cell therapies. We focus on the imaging criteria for the assessment of treatment response to immunotherapy, and post-immunotherapy treatment imaging patterns. We discuss advanced imaging techniques in the evaluation of treatment response to immunotherapy in brain tumors. The imaging characteristics of immunotherapy treatment-related complications in CNS are described. Lastly, future imaging challenges in this field are explored.
Scaling of bite force corresponds with ontogenetic niche shifts in coastal elasmobranchs
Authors: Cullen Joshua A. , Marshall Christopher D.
Published: November 2024

Introduction

Predators, such as sharks, play important ecological roles in coastal ecosystems when abundant and these roles change over ontogeny. However, these shifts in ecological role are often not evaluated in light of feeding performance. Bite force is an ecologically relevant metric of feeding performance that has been associated with a species’ foraging niche, which may serve as a key factor that constrains prey selection both within and among sympatric species.

Methods

This study applies an interdisciplinary approach to discern the ecomechanical relationships of sympatric bull (Carcharhinus leucas), blacktip (Carcharhinus limbatus), and bonnethead sharks (Sphyrna tiburo) using feeding biomechanics and bulk stable isotopes (δ13C, δ15N). We sought to (1) estimate theoretical bite force and scaling patterns over ontogeny of each species, (2) quantify niche breadth and overlap among species, and (3) characterize the relationship between ecological niche shifts and changes in bite force over ontogeny.

Results

Importantly, we found that smaller conspecifics exhibited positive allometric scaling of bite force, whereas larger conspecifics exhibited isometric scaling. Associations between bite force and ontogenetic niche shifts in habitat and diet were found in bull and bonnethead sharks, but not in blacktip sharks. Additionally, isotopic niche breadth was greatest in generalist bull sharks, followed by specialist bonnethead and blacktip sharks.

Discussion

These findings highlight animal performance measures as critical drivers ofecological relationships both within and among species. Size-based differences in bite force scaling should be considered when evaluating feeding performance in other taxa, which may be an important determinant of ontogenetic dietary shifts.
Analysis of factors affecting prognosis of the visual acuity and baseline risk factors for subretinal fibrosis in neovascular age-related macular degeneration patients
Authors: Liu Shihan , Zheng Minming , Sun Huixin , Pan Chunxing , Li Danting , Zhou Xiyuan , Zheng Zheng
Published: November 2024

Background

To evaluate factors affecting visual acuity prognosis in patients with neovascular age-related macular degeneration (nAMD) following anti-vascular endothelial growth factor (anti-VEGF) therapy via intravitreal injection and to identify baseline risk factors for subretinal fibrosis (SF).

Methods

A retrospective study of 64 nAMD eyes treated with intravitreal anti-VEGF treatment over 12 months of follow-up was conducted. Demographic and optical coherence tomography characteristics at baseline were recorded to explore the relevant factors affecting visual acuity outcome. Find baseline risk factors for SF development. The primary baseline measures included OCT qualitative and quantitative indicators, and optical coherence tomography angiography (OCTA) quantitative features.

Results

BCVA (logMAR) at 12 months was positively correlated with age (r = 0.258, p = 0.040), baseline BCVA (r = 0.749, p < 0.001), central macular thickness (CMT) (r = 0.413, p < 0.001), subretinal hyperreflective material (SHRM) (r = 0.304, p = 0.014), intraretinal fluid (IRF) (r = 0.423, p < 0.001), type 2 macular neovascularization (MNV) (r = 0.272, p = 0.029), and ellipsoidal zone breaks (r = 0.299, p = 0.016), and hyperreflective foci (HF) (r = 0.264, p = 0.035). Eyes with SF had worse baseline BCVA (p < 0.001), greater CMT (p = 0.009), and a higher prevalence of IRF (p = 0.005), type 2 MNV (p = 0.001), SHRM (p = 0.012), and HF (p = 0.028). Logistic binary regression analysis showed that baseline BCVA (logMAR) (OR = 0.02, 95% CI: 0.00–0.45, p = 0.013), HF (OR = 0.11, 95% CI: 0.01–0.95, p = 0.045), and type 2 MNV (OR = 0.08, 95% CI: 0.01–0.88, p = 0.039) were independent risk factors of subretinal fibrosis. As for quantitative OCTA parameters, eyes with subretinal fibrosis had a larger microvascular lesion size (p = 0.003), larger vessels area (p = 0.002), higher number of vessel junctions (p = 0.042) and endpoints (p = 0.024), longer total vessel length (p = 0.005), and lower vessel length density (p = 0.042).

Conclusion

This study enplores baseline OCT and OCTA characteristics associated with subretinal fibrosis in nAMD patients. This information can help predict the occurrence and progression of subretinal fibrosis, potentially leading to more personalized treatment approaches for nAMD patients.
Association of different inflammatory indices with risk of early natural menopause: a cross-sectional analysis of the NHANES 2013–2018
Authors: Zheng Mengyu , Li Junying , Cao Yushan , Bao Zhuo , Dong Xing , Zhang Pei , Yan Jinxiang , Liu Yixuan , Guo Yongzhen , Zeng Xianxu
Published: November 2024

Background

Early natural menopause, characterized by the cessation of ovarian function before the age of 45, has been a subject of prior research indicating that inflammation may predict the onset of menopause. However, the specific relationship between peripheral blood inflammatory parameters and early natural menopause remains ambiguous.

Methods

This observational study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2013–2018. The age at menopause was ascertained through the Reproductive Health Questionnaire (RHQ), with early natural menopause defined as menopause occurring before the age of 45 years. Complete blood counts were derived from laboratory test data, and seven indices of inflammation were calculated, including lymphocyte count (LC), neutrophil count (NC), systemic immune inflammation index (SII), product of platelet and neutrophil count (PPN), platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and lymphocyte-monocyte ratio (LMR). A multivariate weighted logistic regression analysis was employed to estimate the association between these inflammatory indices and early natural menopause.

Results

A total of 2,034 participants were included in the analysis, of whom 460 reported experiencing menopause before the age of 45. Both Log2-NC and Log2-PPN were found to be positively correlated with early menopause, with odds ratios (OR) of 1.56 (95% CI: 1.16, 2.09; p = 0.005) and 1.36 (95% CI: 1.07, 1.72; p = 0.015), respectively. The results from models 1 and 2 were consistent with those from model 3. In the trend test, participants in the fourth quartile (Q4) of log2-LC exhibited a positive correlation with early menopause compared to those in the lowest quartile (Q1), with an OR of 1.41 (95% CI: 1.03, 1.93; p = 0.033). Similarly, the fourth quartile (Q4) of log2-NC and log2-PPN demonstrated a positive correlation with early menopause, with odds ratios (OR) of 1.76 (95% CI: 1.27–2.45; p < 0.001) and 1.66 (95% CI: 1.21–2.29; p = 0.002), respectively. In Model 3, log2-SII, log2-PLR, log2-NLR, and log2-LMR were not significantly associated with early menopause.

Conclusion

Our findings indicate that elevated levels of Log2-LC, Log2-NC, and Log2-PPN are positively correlated with an increased risk of early menopause among women in the United States.
Integrative multiomics analysis reveals association of gut microbiota and its metabolites with susceptibility to keloids
Authors: Li Dang , Li Minghao , Gao Hangqi , Hu Kailun , Xie Rongrong , Fan Jing , Huang Mingquan , Liao Chengxin , Han Chang , Guo Zhihui , Chen Xiaosong , Li Ming
Published: November 2024

Keloid scarring is a fibroproliferative disease of the skin, which can significantly impact one’s quality of life through cosmetic concerns, physical discomfort (itchy; painful), restricted movement, and psychological distress. Owing to the poorly understood pathogenesis of keloids and their high recurrence rate, the efficacy of keloid treatment remains unsatisfactory, particularly in patients susceptible to multiple keloids. We conducted fecal metagenomic analyzes and both untargeted and targeted plasma metabolomics in patients with multiple keloids (MK, n = 56) and controls with normal scars (NS, n = 60); tissue-untargeted metabolomics (MK, n = 35; NS, n = 32), tissue-targeted metabolomics (MK, n = 41; NS, n = 36), and single-cell sequencing analyzes (GSE163973). Differences in the gut microbiota composition, plasma metabolites, and tissue metabolites were observed between the MK and NS groups; the core gut microbiota, Oxalobacter formigenes, Bacteroides plebeius, and Parabacteroides distasonis, were identified via the gut microbiome co-occurrence network. Single-cell data helped clarify the specific cells affected by plasma metabolites. An area under the curve analysis using a random forest model based on fecal metagenomics, plasma metabolomics, and tissue metabolomics revealed that gut bacteria, plasma, and tissue metabolites were effective in distinguishing between MK and NS groups. Decreased Bacteroides plebeius could lower uracil levels, altering systemic lipid metabolism, which may change the metabolic phenotype of secretory reticular fibroblasts in wounds, potentially leading to MK. These findings may open new avenues for understanding the multifactorial nature of keloid formation from the gut-skin axis and highlight the potential for novel therapeutic strategies targeting keloid lesions and the underlying systemic imbalances affected by the gut microbiome.
Association between dietary niacin intake and abdominal aortic calcification among the US adults: the NHANES 2013–2014
Authors: Zhang Jiqian , Li Ming , Wang Xinyi , Wang Tongxin , Tian Wende , Xu Hao
Published: November 2024

Background

Abdominal aortic calcification (AAC) serves as a reliable predictor of future cardiovascular incidents. This study investigated the association between dietary niacin intake and AAC in US adults.

Methods

In this study, we conducted a cross-sectional study of 2,238 individuals aged 40 years and older using data from the National Health and Nutrition Examination Survey (NHANES) 2013–2014. AAC was evaluated using the Kauppila scoring system through dual-energy X-ray absorptiometry. Daily niacin intake was calculated by averaging the two dietary recalls and classified in tertiles for analysis. In this study, multiple regression analyses and smoothed curve fitting were used to examine the relationship between dietary niacin intake and AAC, subgroup analyses and interaction tests were used to assess the stability of this relationship across different segments of the population, and forest plots were used to present the results. In addition, we validated the predictive performance of dietary niacin intake on the risk of severe AAC through Receiver Operating Characteristic (ROC) curve analysis.

Results

Among 2,238 participants aged >40 years, the results showed that the higher dietary niacin intake group was associated with lower AAC score (β = −0.02, 95% CI: −0.04 – −0.01), and a lower risk of severe AAC (OR = 0.97, 95% CI: 0.96–0.99). In the fully adjusted model, the higher tertile group was associated with lower AAC score (β = −0.37, 95% CI: −0.73 – −0.02; P for trend = 0.0461) and a lower risk of severe AAC (OR = 0.60, 95% CI: 0.38–0.93; P for trend = 0.0234). The relationship between dietary niacin intake and AAC differed significantly between diabetic and non-diabetic population. The ROC curve analysis revealed that the area under the curve (AUC) for predicting severe AAC risk based on dietary niacin intake was 0.862, indicating good predictive performance.

Conclusion

Higher dietary niacin intake group was associated with lower AAC score and a lower risk of severe AAC. Our findings suggest that dietary niacin intake has the potential to offer benefits in preventing AAC in the general population.
Risk factors of esophagojejunal anastomotic leakage after total gastrectomy for gastric and Siewert type II/III esophagogastric cancer: a retrospective analysis from a tertiary hospital
Authors: Liu Junjie , Hu Jinzhi , Fang Jiaming , Chen Yingliang , Chen Yonghe , He Jiasheng , Deng Zijian , Peng Junsheng , Lian Lei , Chen Shi
Published: November 2024

Background and objectives

To detect the risk factors associated with esophagojejunal anastomotic leakage (EJAL) after total gastrectomy for gastric and Siewert type II/III esophagogastric cancer.

Methods

The data for 609 patients underwent Roux-en-Y esophagojejunostomy after total gastrectomy between March 2015 and March 2021 were reviewed. Univariate and multivariate analyses were performed to evaluate the risk factors.

Results

EJAL was observed in 48 (7.9%) of 609 patients. Univariate analysis revealed that gender, the number of comorbidities (hypertension, diabetes mellitus, coronary heart disease and chronic obstructive pulmonary disease), postoperative serum albumin, tumor location, duration of operation were risk factors associated with EJAL. Patients who had the following factors including male, the number of comorbidities ≥2, postoperative serum albumin <35 g/L, tumor location was esophagogastric junction, duration of operation ≥260 min were more likely to develop EJAL than those who had not. Multivariate analysis revealed that the number of comorbidities (OR 3.464, 95% CI 1.178 – 10.189, p = 0.024) and duration of operation (OR 2.657, 95% CI 1.242 – 5.685, p = 0.012) were independent risk factors associated with EJAL.

Conclusions

More morbidities and prolonged operative duration were independently associated with EJAL after total gastrectomy for gastric and Siewert type II/III esophagogastric cancer. This study indicated the necessity for careful management of these high-risk patients.
Trajectories of adherence to intravenous biological treatment in patients with inflammatory bowel disease: a longitudinal analysis
Authors: Dong Xiuli , Zhu Suyan , Jin Yiyi , Ren Chaoqun , Chen Chunyan
Published: November 2024

Background

Long-term biological therapies for inflammatory bowel disease (IBD) include infliximab and vedolizumab, which are administered intravenously. Although highly effective, non-adherence to these biologics is common and is associated with adverse sequelae and loss of response.

Objective

In this study, we aim to characterize long-term intravenous biologic adherence trajectories among IBD patients and identify the factors linked with these trajectories.

Methods

We conducted a retrospective multicenter study of IBD patients over 2 years to assess their adherence to infliximab and vedolizumab. The date of infusion was determined based on medical and pharmacy records. Using group-based trajectory modeling (GBTM), adherence trajectories were identified based on patients’ 90-day coverage of days over time. The effect of relevant variables on adherence behavior was assessed using multinomial regression analysis.

Results

374 patients with IBD were included in the study, 68.2% males with a median age of 34.3 (IQR 28.0–44.4) years old. Three distinct adherence trajectories were identified for intravenous biologics: “consistent adherence” (n = 136, 36.4%), “slow decline” (n = 137, 36.6%) and “rapid decline” (n = 101, 27.0%). Compared with consistent adherence, concomitant use of aminosalicylates (OR 3.49, 95% CI 1.34–9.05) was associated with a significantly greater risk of rapid decline. Conversely, being married at the initiation of biologics (OR 0.43, 95% CI 0.19–0.95) and having been hospitalized within preceding years (OR 0.44, 95% CI 0.23–0.88) appeared to have a protective effect against rapid decline. Additionally, being male (OR 0.57, 95% CI 0.32–1.01) was found to be protective against slow decline.

Conclusion

Distinct adherence patterns for infusion biologics among IBD patients have been identified, offering valuable insights to refine the design and timing of adherence interventions. However, only limited factors were found to be associated with specific adherence trajectories, revealing the complex nature of adherence behavior.
Exercise combined with artificial gravity and exercise only countermeasures prevent organ and blood vessel morpholgical changes induced by 55 days HDT bedrest
Authors: Arbeille P. , Zuj K. , Guillon L.
Published: November 2024

Background

Changes in blood vessel properties have been identified with confinement, spaceflight, bedrest, and dry immersion. Subsequently, it was suspected that other organs may also be affected in these extreme environments. The purposes of the current study were to determine the effects of head-down bedrest (HDT) on cardiovascular and organ measurements made using ultrasound imaging similar to that currently available on the International Space Station, and to evaluate the efficacy of two different countermeasure protocols in preventing any observed changes in the ultrasound measurements with HDT.

Methods

Ultrasound measures were conducted on 24 individuals (3 groups of 8) pre HDT and on day 55 of the HDT. The control group (C°) remained in passive HDT for the 55 days, the C1 group performed aerobic exercise daily (EX), and the C2 group practiced aerobic exercise under artificial gravity conditions (EX-AG). Fifteen parameters were measured on 10 different organs and blood vessels including the right common carotid artery, abdominal aorta, right tibial artery, left ventricle, right jugular vein, portal vein, right kidney, cervical and lumbar vertebra, and the vastus intermedius muscle.

Results

HDT resulted in changes for many of the parameters investigated. Observed changes in carotid IMT and distensibility, cardiac ejection fraction, portal vein diameter, and vastus intermedius muscle thickness were attenuated with EX and EX-AG, with EX-AG having a greater effect than exercise alone on measures of carotid distensibility.

Conclusion

Results from this study indicate changes in many structures assessed with ultrasound imaging after 55 days of HDT bedrest with some changes being attenuated with the two investigated countermeasure protocols.
Phyllosphere bacterial community and metabolomic analysis revealed the mechanism of Cd tolerance in the bryophyte Tortella tortuosa (Hedw.) Limpr
Authors: Zhu Yongqi , Li Qiuge , Feng Lanlan , Dong Yijie , Zhang Yuanpei , Nurmaimaiti Nigati , Mamut Reyim
Published: November 2024

Introduction

Phytoremediation is a safe and green technology for the remediation of heavy metal pollution, a global environmental problem. Bryophytes are well known for their special physiological properties, but there is little research on the use of bryophytes for phytoremediation.

Methods

In this indoor experiment, the impacts of 40 days of Cd pollution (1 (T1), 5 (T2), 10 (T3) mg·L-1) on Cd absorption, growth and physiological characteristics, and phyllosphere bacterial diversity of Tortella tortuosa were explored.

Results

The results showed that the maximum Cd absorption capacity of T. tortuosa was 5.0135 mg·kg-1. The contents of leaf chlorophyll a (Chl a) and chlorophyll b (Chl b) in T. tortuosa decreased (p < 0.05) with the increase of Cd concentration. Especially, the Chl a and Chl b contents of the T3 treatment reduced by 88% and 91%, respectively compared with those of the CK (Cd: 0 mg·L-1). The catalase (CAT) and peroxidase (POD) activities of the T3 treatment reduced by 55% and 85%, respectively (p < 0.05), and the malondialdehyde (MDA) content increased by 167%, compared with those of the CK. Under Cd exposure, Cyanobacteria (63.49%) and Proteobacteria (26.62%) were the dominant bacterial phyla. The highly abundant phyllosphere bacteria were negatively correlated with the Cd concentration, antioxidant enzyme activity, and chlorophyll content in T. tortuosa, and positively correlated with the relative abundances of Neomycin and N-Acetyl-L-Glutamic acid.

Discussion

Although the severe Cd pollution could affect the physiological and metabolic characteristics of T. tortuosa, T. tortuosa had a strong absorption capacity for Cd. Therefore, it could be used for phytoremediation of heavy metal pollution. This study will provide a reference for the remediation of soil heavy metal pollution.
Explainable light-weight deep learning pipeline for improved drought stress identification
Authors: Patra Aswini Kumar , Sahoo Lingaraj
Published: November 2024

Introduction

Early identification of drought stress in crops is vital for implementing effective mitigation measures and reducing yield loss. Non-invasive imaging techniques hold immense potential by capturing subtle physiological changes in plants under water deficit. Sensor-based imaging data serves as a rich source of information for machine learning and deep learning algorithms, facilitating further analysis that aims to identify drought stress. While these approaches yield favorable results, real-time field applications require algorithms specifically designed for the complexities of natural agricultural conditions.

Methods

Our work proposes a novel deep learning framework for classifying drought stress in potato crops captured by unmanned aerial vehicles (UAV) in natural settings. The novelty lies in the synergistic combination of a pre-trained network with carefully designed custom layers. This architecture leverages the pre-trained network’s feature extraction capabilities while the custom layers enable targeted dimensionality reduction and enhanced regularization, ultimately leading to improved performance. A key innovation of our work is the integration of gradient-based visualization inspired by Gradient-Class Activation Mapping (Grad-CAM), an explainability technique. This visualization approach sheds light on the internal workings of the deep learning model, often regarded as a ”black box”. By revealing the model’s focus areas within the images, it enhances interpretability and fosters trust in the model’s decision-making process.

Results and discussion

Our proposed framework achieves superior performance, particularly with the DenseNet121 pre-trained network, reaching a precision of 97% to identify the stressed class with an overall accuracy of 91%. Comparative analysis of existing state-of-the-art object detection algorithms reveals the superiority of our approach in achieving higher precision and accuracy. Thus, our explainable deep learning framework offers a powerful approach to drought stress identification with high accuracy and actionable insights.
Beyond the denial of death: death meditation increases a sense of connectedness and appreciation of life
Authors: Das Enny , Fransen Marieke L. , Oliver Mary Beth
Published: November 2024

Introduction

The pervasive denial of death in modern society has created an unbalanced relationship with death that gets in the way of living a full life. To address this problem, the Lancet Commission on the Value of Death recently proposed principles of a healthier scenario for the future. In this ‘realistic utopia’, death is recognized as having value, and conversations about death and dying have become common. The present research examined if art could help to decrease death denial and increase life appreciation.

Methods

An art installation invited visitors to confront thoughts of their own death in a guided meditation by visualizing the decay of their own dead body. Visitors’ responses were compared to those of a standard death reflection group and a neutral control group (N=229) at two time points. Feelings of being moved, connectedness to a higher power, and life appreciation were assessed immediately (T1); death reflection and life appreciation were assessed two weeks later (T2) (N=105).

Results

At T1, the art installation induced higher levels of being moved and connectedness to a higher power than the two control groups. At T2, the art installation induced more lingering reflection than the two control groups. Lingering reflection, in turn, increased appreciation of life.

Discussion

We show that art can be harnessed to promote a more balanced relationship with death, and greater appreciation of life. The art installation provided individuals with concrete, and more encompassing simulations of what death could be like. By placing death in this bigger perspective, the art installation encouraged conscious death reflection. Such a connected perspective is often lacking, but direly needed, in healthcare and in larger society.
Enhancing interpretability and accuracy of AI models in healthcare: a comprehensive review on challenges and future directions
Authors: Ennab Mohammad , Mcheick Hamid
Published: November 2024

Artificial Intelligence (AI) has demonstrated exceptional performance in automating critical healthcare tasks, such as diagnostic imaging analysis and predictive modeling, often surpassing human capabilities. The integration of AI in healthcare promises substantial improvements in patient outcomes, including faster diagnosis and personalized treatment plans. However, AI models frequently lack interpretability, leading to significant challenges concerning their performance and generalizability across diverse patient populations. These opaque AI technologies raise serious patient safety concerns, as non-interpretable models can result in improper treatment decisions due to misinterpretations by healthcare providers. Our systematic review explores various AI applications in healthcare, focusing on the critical assessment of model interpretability and accuracy. We identify and elucidate the most significant limitations of current AI systems, such as the black-box nature of deep learning models and the variability in performance across different clinical settings. By addressing these challenges, our objective is to provide healthcare providers with well-informed strategies to develop innovative and safe AI solutions. This review aims to ensure that future AI implementations in healthcare not only enhance performance but also maintain transparency and patient safety.
Persistent Social Inequality in Adolescent Health Indicators 1991–2022: Trend Study From Denmark
Authors: Holstein Bjørn E. , Damsgaard Mogens Trab , Pedersen Trine Pagh , Rasmussen Mette , Román Julie Ellegaard Ibáñez , Toftager Mette , Rich Madsen Katrine
Published: November 2024

Objectives

To examine trends in socioeconomic inequality in adolescent health over three decades, across fifteen health indicators: overweight, underweight, headache, stomachache, backpain, emotional symptoms, difficulties falling asleep, loneliness, low life satisfaction, low self-rated heath, smoking, drunkenness, physical inactivity, low vegetable intake, and inadequate toothbrushing.

Methods

The Health Behaviour in School-aged Children (HBSC) study in Denmark included nine identical surveys of 11–15-year-olds from 1991 to 2022, n = 35,423. For each health indicator, we measured absolute and relative socioeconomic inequality by prevalence differences and odds ratios between low and high socioeconomic groups.

Results

There was socioeconomic inequality in thirteen health indicators, e.g., the OR (95% CI) for overweight in low vs. high socioeconomic groups was 2.22 (1.95–2.49). This social inequality persisted across health indicators throughout the study period with two deviations: Underweight was not associated with socioeconomic background and drunkenness was persistently most prevalent in higher socioeconomic groups.

Conclusion

The political efforts to reduce socioeconomic inequality in health seems to have failed. It is important to improve monitoring of adolescent health and implement improved policies to tackle socioeconomic inequality in adolescent health.
Test, Modeling, and Vibration Control of a Novel Viscoelastic Multi-Dimensional Earthquake Isolation and Mitigation Device
Authors: Hu Zhong-Wei , Xu Zhao-Dong , Tian Yun , Chen Zheng-Han , He Jia-Xuan , Dai Jun , Miao Qi-Song , Du Xiu-Li
Published: November 2024

Earthquakes contain complex components in both the horizontal and vertical directions. However, most vibration control strategies work only in a single direction. The existing multi-dimensional isolation devices usually have complex designs and low damping ratios; hence, the stability of structures that incorporate the devices is currently insufficient. This study designs a novel multi-dimensional isolation and mitigation device based on viscoelastic damping technology (VE-MDIMD). The device consists of a core bearing and several cylindrical dampers, providing vibration control capacity in both the horizontal and vertical directions and a strong uplift resistance. To evaluate the device’s performance, a series of dynamic tests are conducted on the cylindrical damper utilized in the device. The results show that the damper’s mechanical properties exhibit a pronounced dependence on the frequency and amplitude, and its hysteresis curves become obviously nonlinear with increased deformation. Subsequently, to describe the behavior of the VE-MDIMD, a mechanical model is established which combines the construction of the device and the characteristics of the damper. Considering the limitations of existing models in fully capturing the nonlinear behavior of the damper, a novel multi-scale model is proposed based on the microstructure of viscoelastic material. The experimental verification confirms that the model can accurately capture the frequency and amplitude dependence, as well as the nonlinear hysteresis behavior, of the damper. Finally, the effectiveness of the VE-MDIMD is evaluated through the dynamic analysis of an actual structure. The arrangement of the device in the structure is optimized based on a multi-objective genetic algorithm available in Matlab (R2019b) and OpenSEES (Version 3.0.0). The results demonstrate the device’s superiority in controlling both horizontal and vertical vibrations in the superstructure.