bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of nutritional programming on the microbiota of different gut regions in Atlantic Salmon (Salmo salar) from first feeding in a 22-week feeding trial
Authors: Tawfik Marwa Mamdouh , Tocher Douglas R. , McMillan Stuart , Norambuena Fernando , Douglas Alex , Betancor Mónica B. , Martin Samuel A. M. 
Published: May 2024

Abstract

Increasing evidence suggests that gut microbiota is essential for regulating the development of the digestive system, aiding digestion, nutrient metabolism, growth, immune function, and disease resistance. Advances in high throughput sequencing technologies have allowed the development of a broader understanding of the complex gut microbiota in fish, especially in relation to the impact of dietary plant ingredients on gut health. However, to date, most studies have focused on the entire or distal gut in response to a plant-based diet. Moreover, the potential involvement of the microbiome in driving the adaptation of early-exposed Atlantic salmon to a plant-based diet during a later developmental stage, a phenomenon commonly referred to as ‘nutritional programming’, has yet to be demonstrated. The aim was to characterise and compare the microbiota composition and diversity in gut regions (pyloric caeca, middle and distal intestines) of Atlantic salmon (maintained for 22 weeks from first feeding in a recirculating aquaculture system) with and without nutritional programming using a plant-based diet. 16S rRNA amplicons sequencing was employed to monitor taxa and were identified as amplicon sequence variants. The study experiment followed a typical nutritional programming design with two experimental groups. Fish initially exposed to the plant-based diet for two weeks at first feeding and challenged later at 16 weeks post first-feeding for six weeks with a similar plant-based diet were considered the programmed group, whereas those initially fed a marine diet and challenged later with the plant-based diet were the control group. The alpha diversity was higher in the pyloric caeca than the distal intestine. Analysis of similarities showed that the microbiota of pyloric caeca differentiated in composition from each of middle and distal regions after nutritional programming in both high and low-abundant taxa. Ruminococcaceae (primarily anaerobic Clostridia) comprised the core taxa in 80% of fish in the programmed group across the three gut regions and is known to help ferment plant ingredients. Moreover, the internal environment of each gut region mainly selects their microbial assemblages. Additionally, sequencing of feed and water revealed their influence on the gut microbiota of programmed and control fish. Furthermore, Firmicutes, Proteobacteria, Actinobacteriota and Bacteroidota were the prevalent and dominant phyla regardless of the gut region. Further research is required to better understand the microbial programming and its functional consequences in carnivorous fish.
Agroeconomic and environmental implications of future labor market evolution
Authors: Zhao Xin , Sheng Di , Edmonds James , Patel Pralit , Stephanie Waldhoff , O'Neill Brian , Wise Marshall 
Published: May 2024

Abstract

Long-term labor market evolution shapes agricultural transformation through labor productivity growth and labor market transitions. Despite its importance in agricultural production, labor has been overlooked when exploring the agrifood-water-environment-climate nexus. Here, we incorporate evolving labor markets into multisector dynamic modeling to examine their agroeconomic and environmental implications. Our projections show that the recent decline of global agricultural employment persists, with an estimated decrease of over 40 million people per decade by 2100, strengthening the decoupling of labor from production. Exploring scenarios with varying labor productivity and supply factors, we illustrate a critical linkage between labor market dynamics and global environmental change, with a positive relationship between productivity-adjusted labor supply and agricultural emissions and more pronounced regional and sectoral responses. While highlighting the pressing need to capture labor dynamics in the integrated human-Earth systems, our study lays the foundation for further investigation into labor market responses and feedback in broader scenarios.
Multi-country evidence on societal factors to include in energy transition modeling
Authors: Fisch-Romito Vivien , Jaxa-Rozen Marc , Wen Xin , Trutnevyte Evelina 
Published: May 2024

Abstract

Integrated assessment and energy system models are challenged to account for societal transformation dynamics to produce feasible low-carbon pathways. Yet, empirical evidence is lacking on which factors should be incorporated, how and to what extent this would improve the quality and relevance of modeled pathways. Here, we include six societal factors related to (i) infrastructure dynamics, (ii) actors and decision making and (iii) societal and institutional context into an open-source simulation model of the national power system transition. We apply this model for 31 European countries and, using hindcasting (1990–2019), quantify which societal factors improved the modeled pathways. We find that, if well-chosen and in most cases, incorporating societal factors can improve the hindcasting performance by up to 24% in terms of modelled installed capacity of individual technologies, but there are also situations where hindcasting performance can become worse. The combinations of most relevant societal factors differ among countries and model outputs, but infrastructure lock-in, public acceptance and investment risks contribute more strongly and frequently to model performance improvement. Our study hence paves the road to evidence-based choice of societal factors to be included in energy transition modeling in a systematic and transparent way.
Clinicopathologic Features of Renal Neuroendocrine Neoplasms
Authors: Meng Lili , Jiang Zhenjian , Lin Shulan , Ni Zheng , Hu Shuying , Li Xiang , Guo Xinxin , Chen Shanghua , Ji Yuan , Hou Yingyong , Hou Jun 
Published: May 2024

Abstract

Primary renal neuroendocrine tumors (NENs) are a unique and rare type of tumor, with relatively limited research. In our retrospective study, we aimed to comprehensively investigate the clinicopathological features, biological behavior, and prognosis of patients that diagnosed as renal neuroendocrine tumors and treated at our center. Histological evaluations were meticulously conducted on archived diagnostic slides obtained from pathological examinations. Notably, all six cases of primary renal neuroendocrine tumors presented as solitary lesions, with a predilection for the left kidney in the majority (4/6) of cases. In accordance with the latest WHO classification, one case was diagnosed as neuroendocrine carcinoma (NEC), while the remaining five cases were identified as well-differentiated neuroendocrine tumors (NETs). Microscopically, the tumor cells exhibited distinctive organ-like structures. One case demonstrated characteristics of a large cell type, with mitotic images and visible necrosis. All tumor synaptophysin were diffusely stained, although chromogranin and CD56 staining patterns varied. Further molecular investigation using next-generation sequencing (NGS) in one case unveiled copy number amplification of the MCL-1 gene; however, no common molecular changes observed in gastroentero-pancreatic neuroendocrine tumors (GEPNEN), such as VHL, ATRX, and DAXX mutations. The limited knowledge regarding the molecular profile and survival outcomes of primary renal neuroendocrine tumors underscores the necessity for enhanced understanding of their behavior. In the process of clinical diagnosis, an improved awareness and accurate diagnosis are imperative to facilitate optimal treatment strategies for patients.
Multimodal Learning for Mapping the Genotype-Phenotype Dynamics
Authors: Khodaee Farhan , Zandie Rohola , Edelman Elazer 
Published: May 2024

Abstract

How complex phenotypes emerge from intricate gene expression patterns is a fundamental question in biology. Quantitative characterization of this relationship, however, is challenging due to the vast combinatorial possibilities and dynamic interplay between genotype and phenotype landscapes. Integrating high-content genotyping approaches such as single-cell RNA sequencing and advanced learning methods such as language models offers an opportunity for dissecting this complex relationship. Here, we present a computational integrated genetics framework designed to analyze and interpret the high-dimensional landscape of genotypes and their associated phenotypes simultaneously. We applied this approach to develop a multimodal foundation model to explore the genotype-phenotype relationship manifold for human transcriptomics at the cellular level. Analyzing this joint manifold showed a refined resolution of cellular heterogeneity, enhanced precision in phenotype annotating, and uncovered potential cross-tissue biomarkers that are undetectable through conventional gene expression analysis alone. Moreover, our results revealed that the gene networks are characterized by scale-free patterns and show context-dependent gene-gene interactions, both of which result in significant variations in the topology of the gene network, particularly evident during aging. Finally, utilizing contextualized embeddings, we investigated gene polyfunctionality which illustrates the multifaceted roles that genes play in different biological processes, and demonstrated that for VWF gene in endothelial cells. Overall, this study advances our understanding of the dynamic interplay between gene expression and phenotypic manifestation and demonstrates the potential of integrated genetics in uncovering new dimensions of cellular function and complexity.
Bayesian spatiotemporal modelling and mapping of malaria risk among children aged below 5 years in Ghana
Authors: Takramah Wisdom Kwami , Afrane Yaw Asare , Aheto Justice Moses K. 
Published: May 2024

Abstract

Background
Malaria is a significant public health problem, particularly among children aged 6-59 months who bear the greatest burden of this disease. Malaria transmission is high and more pronounced in poor tropical and subtropical areas of the world. Climate change is positively correlated with the geographical distribution of malaria vectors. There is substantial evidence of spatial and temporal differences in under-five malaria risk. Thus, the study aimed to create intelligent maps of smooth relative risk of malaria in children under-5 years that highlights high and low malaria burden in space and time to support malaria prevention, control, and elimination efforts.
Method
The study extracted and merged the required data on malaria among children aged 6-59 months from 2014 Ghana Demographic and Health Surveys (GDHS), 2016 and 2019 Ghana Malaria Indicator Surveys (GMIS). The outcome variable of interest is the count of children aged 6-59 months with positive test on rapid diagnostic test (RDT) kit. Bayesian Hierarchical Spatiotemporal models were specified to estimate and map spatiotemporal variations in the relative risk of malaria. The existence of local clustering was assessed using local indicator of spatial association (LISA) and the points were mapped to display significant local clusters, hotpot, and cold spot communities.
Results
The number of positive malaria cases in children aged 6-59 months decreased marginally between the 2014 and 2019 DHS survey periods. Smooth relative risk of malaria among children aged 6-59 months has consistently increased in the Northern and Eastern regions between 2014 and 2019. Socioeconomic and climatic factors such as household size [Posterior Mean: -0.198 (95% CrI: 3.52, 80.95)], rural area [Posterior Mean: 1.739 (95% CrI: 0.581, 2.867)], rainfall [Posterior Mean: 0.003 (95% CrI: 0.001, 0.005)], and maximum temperature [Posterior Mean: -1.069 (95% CrI: -2.135, -0.009)] have all been shown as statistically significant predictors of malaria risk in children aged 6-59 months. Hot spot DHS clusters with a significantly high relative risk of malaria among children aged 6-59 months were repeatedly detected in the Ashanti region between 2014 and 2019.
Conclusion
The findings would provide policymakers with practical and insightful information for the equitable distribution of scarce health resources targeted at reducing the burden of malaria and its associated mortality among children under-five years.
Hazardous Impact of Prophetic Variables in The Development of Radicular Cyst and Associated Periapical Osteo-Invasion
Authors: Fareed Muhammad , Ahmad Shahzad , Iqbal Shazia , Ashraf Muhammad Abdul Basit , Anwar Malik Adeel , Lodhi Saood Khan 
Published: May 2024

Abstract

Background: The long-standing pulpitis may result in apical periodontitis, which, if left untreated, will ultimately develop into a periapical cyst. Our study aimed to evaluate the hazardous impact of prophetic variables on the development of radicular cysts and associated periapical osteo-invasion.
Methodology: One hundred patients with radicular cysts and 100 samples of individuals with normal pulp were selected. For the analytical assessment, periapical tissue samples were obtained from patients experiencing periapical surgery. Tissue homogenate was prepared by using a Potter-Elvehjem homogenizer. The levels of antioxidants and pro-oxidants were assessed by their respective protocols. The anti-inflammatory status, levels of matrix metalloproteinases (MMPs), and bone remodeling biomarkers were determined by designated ELISA kits.
Results: Increased levels of pro-oxidants and inflammatory agents while a diminished quantity of antioxidants were observed in the patients with radicular cysts. The levels of MMPs and sRANKL levels were raised, whereas OPG levels were reduced, indicating the osteo-invasion process in radicular cyst patients.
Conclusions: The underlying mechanisms of progression of the radicular cyst into adjacent peri-apical bone provide interesting relationships among the biomarkers of oxidative stress, pro-inflammatory cytokines, and bone remodeling. Thus, novel therapies based on targeting MMPs through the action of TIMPs and abrogating sRANKL-RANK interactions can play a significant role in preventing radicular cyst proliferation.
The hospital frailty risk score effectively predicts adverse outcomes in patients with atrial fibrillation in the intensive care unit
Authors: Li Xinya , Cheng Hongtao , Tang Yonglan , Tan Shanyuan , Bai Zihong , Li Tanjian , Luo Meilin , Wang yu , Jun Lyu 
Published: May 2024

Abstract

Background
Atrial fibrillation (AF) and frailty are significant global public health problems associated with advancing age. However, the relationship between frailty and older patients with AF in the intensive care unit (ICU) has not been thoroughly investigated. This study aimed to investigate whether the hospital frailty risk score (HFRS) is associated with adverse outcomes in older patients with AF in the ICU.
Methods
This was the first retrospective analysis of older patients with AF admitted to the ICU between 2008 and 2019 at a tertiary academic medical center in Boston. The HFRS was used to measure frailty severity. The outcomes of interest were in-hospital and 30-day mortality and the incidence of sepsis and ischemic stroke.
Results
There were 7,792 participants aged approximately 80 years, almost half (44.9%) of whom were female. Among this group, 2,876 individuals were identified as non-frail, while 4,916 were classified as frail. The analysis revealed a significantly greater incidence of in-hospital (18.8% compared to 7.6%) and 30-day mortality (24.5% versus 12.3%) in the frail group. After accounting for potential confounding factors, a multivariate Cox proportional hazards regression analysis revealed that frail participants had a 1.56-fold greater risk of mortality within 30 days (95% CI = 1.38–1.76, p < 0.001).
Conclusions
Frailty is an independent risk factor for adverse outcomes in older patients with AF admitted to the ICU. Therefore, prioritizing frailty assessment and implementing specific intervention strategies to improve prognostic outcomes are recommended.
Discussion on the prediction model of early judgment of critical risk in emergency patients
Authors: Li Xurui , Lv Jian , Li Hongling , Guo Hui , Zhao Qian , Li Jianguo 
Published: May 2024

Abstract

Objective: To establish a predictive model for early assessment of critical risk in emergency patients and evaluate its clinical clinical benefits.
Method: Clinical data of 3859 patients who visited the emergency department at Hebei General Hospital from November 2021 to December 2021 were selected. The enrolled patients were randomly divided into a training set (2703 cases) and a validation set (1156 cases) in a 7:3 ratio. In the training set, a predictive model was established based on the results of multivariate logistic stepwise regression analysis. At the same time, risk levels were divided, and the predictive efficacy and clinical benefits of the predictive model were verified.
Result: There was no statistically significant difference in clinical data between the training and validation set (P>0.05), indicating comparability between the two groups. Multivariate logistic stepwise regression analysis showed that Gender, age, HR, R, SBP, SPO2, consciousness, pupil, mental state, and pain score were independent risk factors for early assessment of critical risk (P<0.05), and a predictive model was established based on this. Using conditional inference tree, critical risks are classified into low risk (P≤0.075), medium risk (0.075＜P≤0.656), and high risk (P>0.656). Furthermore, the prediction model was internally validated in both the training and validation sets, with a training set AUC of 0.926 [95% CI (0.912-0.939), P<0.001] and a validation set AUC of 0.911 [95% CI (0.886-0.936), P<0.001], indicating good discrimination of the prediction model; The calibration curve of the training set fits the standard curve, while the calibration curve of the validation set model slightly deviates from the standard curve. In the Hosmer Limeshow test, the results of the two groups were P=0.180 and P=0.546, respectively, indicating good calibration of the predicted model; The DCA curve suggests that both groups of people can achieve good clinical benefits.
Conclusion: Establishing a predictive model for early assessment of emergency critical risk is helpful for early identification and intervention of emergency critical patients.
Micrometastases in axillary lymph nodes in breast cancer, post-neoadjuvant systemic therapy
Authors: Lee Janghee , Park Seho , Bae Soong June , Ji Junghwan , Kim Dooreh , Kim Jee Ye , Park Hyung Seok , Ahn Sung Gwe , Kim Seung Il , Park Byeong-Woo , Jeong Joon 
Published: May 2024

Abstract

Introduction:
The significance of minimal residual axillary disease, specifically micrometastases, following neoadjuvant systemic therapy (NST) remains largely unexplored. Our study aimed to elucidate the prognostic implications of micrometastases in axillary and sentinel lymph nodes following NST.
Methods
This retrospective study analyzed primary breast cancer patients who underwent surgery after NST from September 2006 through February 2018. All patients received axillary lymph node dissection (ALND), either with or without sentinel lymph node biopsy. Recurrence-free survival (RFS)-associated variables were identified using a multivariate Cox proportional hazard model.
Results
Of the 978 patients examined, 438 (44.8%) exhibited no pathologic lymph node involvement (ypN0) after NST, while 89 (9.1%) had micrometastases (ypNmi). Multivariate analysis revealed no significant association between ypNmi and RFS in patients post-NST (hazard ratio [HR], 1.02; 95% confidence interval [CI], 0.42–2.49; P = 0.958). Notably, over half of the patients with sentinel lymph node micrometastases (SLNmi) had additional metastases, nearly triple that of SLN-negative patients (P < 0.001). Furthermore, SLNmi patients experienced significantly worse RFS compared to SLN-negative patients (HR, 2.23; 95% CI, 1.12–4.46; P = 0.023). Additional metastases in SLNmi were more prevalent in patients with larger residual breast disease greater than 20 mm, HR-positive/HER2-negative subtype, and low Ki-67 LI (< 14%).
Conclusions
While ypNmi does not influence the prognosis compared to ypN0, SLNmi emerges as a significant negative prognostic factor and a robust predictor of additional metastases. Hence, additional ALND may be warranted to confirm axillary nodal status in patients with SLNmi.
Combination of albumin-lymphocyte score and skeletal muscle index predicts prognosis of ovarian patients after primary debulking surgery: A multicenter retrospective study
Authors: Gong Han , Kang Quanmin , Nie Dan , Zhang Peng , Zhou Xiaoxia , Li Zhaoci , He Xinlin , Hu Yulan , Li Zhengyu 
Published: May 2024

Abstract

Background Accumulating evidence underscores the significant aspects of inflammation and nutrition in the tumors. We aimed to assess related prognostic preoperative variables and their combined impact for ovarian cancer patients. Methods A retrospective research was proceeded among 347 primarily diagnosed ovarian cancer patients across multiple medical centers. They were divided into a discovery cohort (237 patients) and a validation cohort (110 patients). Serological tests and plain CT images were utilized to quantify ALS and SMI. We intended to inspect the impact of ALS, SMI, and their combined indicator-CAS grade on clinical features and prognosis of the patients. Results Patients illustrating decreased ALS and increased SMI demonstrated improved overall survival (OS) and recurrence-free survival (RFS). Upon stratification by CAS grade, distinct results were observed: grade 1 patients displayed higher body mass index (BMI) and the most favorable survival prognosis, while grade 3 patients were in connection with poorest OS and RFS. Independent variables for OS and RFS included residual disease and elevated CAS grades. These findings were also validated in another independent cohort. Conclusion The CAS grade - combination of ALS and SMI is a ponderable and independent predictor for prognosis in ovarian cancer patients.