bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid-FHR: a multi-modal AI approach for automated fetal acidosis diagnosis
Authors: Zhao Zhidong , Zhu Jiawei , Jiao Pengfei , Wang Jinpeng , Zhang Xiaohong , Lu Xinmiao , Zhang Yefei 
Published: January 2024

Abstract
Background
In clinical medicine, fetal heart rate (FHR) monitoring using cardiotocography (CTG) is one of the most commonly used methods for assessing fetal acidosis. However, as the visual interpretation of CTG depends on the subjective judgment of the clinician, this has led to high inter-observer and intra-observer variability, making it necessary to introduce automated diagnostic techniques.

Methods
In this study, we propose a computer-aided diagnostic algorithm (Hybrid-FHR) for fetal acidosis to assist physicians in making objective decisions and taking timely interventions. Hybrid-FHR uses multi-modal features, including one-dimensional FHR signals and three types of expert features designed based on prior knowledge (morphological time domain, frequency domain, and nonlinear). To extract the spatiotemporal feature representation of one-dimensional FHR signals, we designed a multi-scale squeeze and excitation temporal convolutional network (SE-TCN) backbone model based on dilated causal convolution, which can effectively capture the long-term dependence of FHR signals by expanding the receptive field of each layer’s convolution kernel while maintaining a relatively small parameter size. In addition, we proposed a cross-modal feature fusion (CMFF) method that uses multi-head attention mechanisms to explore the relationships between different modalities, obtaining more informative feature representations and improving diagnostic accuracy.

Results
Our ablation experiments show that the Hybrid-FHR outperforms traditional previous methods, with average accuracy, specificity, sensitivity, precision, and F1 score of 96.8, 97.5, 96, 97.5, and 96.7%, respectively.

Conclusions
Our algorithm enables automated CTG analysis, assisting healthcare professionals in the early identification of fetal acidosis and the prompt implementation of interventions.
The relationship between triglyceride-glucose index and prospective key clinical outcomes in patients hospitalised for coronary artery disease
Authors: Hao Benchuan , Lyu Lyu , Xu Juan , Zhu Xiaoqing , Xu Cui , Gao Weiyang , Qin Ji , Huang Taoke , Ding Yipu , Zhang Ziyue , Yang Yanhui , Liu Hongbin 
Published: January 2024

Abstract
Background
The triglyceride-glucose (TyG) index is regarded as a dependable alternative for assessing insulin resistance (IR), given its simplicity, cost-effectiveness, and strong correlation with IR. The relationship between the TyG index and adverse outcomes in patients with coronary heart disease (CHD) is not well established. This study examines the association of the TyG index with long-term adverse outcomes in hospitalized CHD patients.

Methods
In this single-center prospective cohort study, 3321 patients hospitalized with CHD were included. Multivariate Cox regression models were employed to assess the associations between the TyG index and the incidence of all-cause mortality and major adverse cardiovascular events (MACEs). To examine potential nonlinear associations, restricted cubic splines and threshold analysis were utilized.

Results
During a follow-up period of 9.4 years, 759 patients (22.9%) succumbed to mortality, while 1291 (38.9%) experienced MACEs. Threshold analysis demonstrated a significant “U”-shaped nonlinear relationship with MACEs, with different hazard ratios observed below and above a TyG index of 8.62 (below: HR 0.71, 95% CI 0.50–0.99; above: HR 1.28, 95% CI 1.10–1.48). Notably, an increased risk of all-cause mortality was observed only when the TyG index exceeded 8.77 (HR 1.53, 95% CI 1.19–1.96).

Conclusions
This study reveals a nonlinear association between the TyG index and both all-cause mortality and MACEs in hospitalized CHD patients with CHD. Assessing the TyG index, particularly focusing on individuals with extremely low or high TyG index values, may enhance risk stratification for adverse outcomes in this patient population.
Left main coronary artery morphological phenotypes and its hemodynamic properties
Authors: Wang Qi , Ouyang Hua , Lv Lei , Gui Long , Yang Songran , Hua Ping 
Published: January 2024

Abstract
Background
Atherosclerosis may be linked to morphological defects that lead to variances in coronary artery hemodynamics. Few objective strategies exit at present for generalizing morphological phenotypes of coronary arteries in terms of hemodynamics. We used unsupervised clustering (UC) to classify the morphology of the left main coronary artery (LM) and looked at how hemodynamic distribution differed between phenotypes.

Methods
In this study, 76 LMs were obtained from 76 patients. After LMs were reconstructed with coronary computed tomography angiography, centerlines were used to extract the geometric characteristics. Unsupervised clustering was carried out using these characteristics to identify distinct morphological phenotypes of LMs. The time-averaged wall shear stress (TAWSS) for each phenotype was investigated by means of computational fluid dynamics (CFD) analysis of the left coronary artery.

Results
We identified four clusters (i.e., four phenotypes): Cluster 1 had a shorter stem and thinner branches (n = 26); Cluster 2 had a larger bifurcation angle (n = 10); Cluster 3 had an ostium at an angulation to the coronary sinus and a more curved stem, and thick branches (n = 10); and Cluster 4 had an ostium at an angulation to the coronary sinus and a flatter stem (n = 14). TAWSS features varied widely across phenotypes. Nodes with low TAWSS (L-TAWSS) were typically found around the branching points of the left anterior descending artery (LAD), particularly in Cluster 2.

Conclusion
Our findings demonstrated that UC is a powerful technique for morphologically classifying LMs. Different LM phenotypes exhibited distinct hemodynamic characteristics in certain regions. This morphological clustering method could aid in identifying people at high risk for developing coronary atherosclerosis, hence facilitating early intervention.
A novel methodological approach to participant engagement and policy relevance for community-based primary medical care research during the COVID-19 pandemic in Australia and New Zealand
Authors: Barnes Katelyn , Hall Dykgraaf Sally , O’Brien Kathleen , Douglas Kirsty , Eggleton Kyle , Bui Nam , Wong Sabrina T. , Etz Rebecca S. , Goodyear-Smith Felicity 
Published: January 2024

AbstractCommunity-based primary care, such as general practice (GP) or urgent care, serves as the primary point of access to healthcare for most Australians and New Zealanders. Coronavirus disease 2019 (COVID-19) has created significant and ongoing disruptions to primary care. Traditional research methods have contributed to gaps in understanding the experiences of primary care workers during the pandemic. This paper describes a novel research design and method that intended to capture the evolving impact of the COVID-19 pandemic on primary care workers in Australia and New Zealand. Recurrent, rapid cycle surveys were fielded from May 2020 through December 2021 in Australia, and May 2020 through February 2021 in New Zealand. Rapid survey development, fielding, triangulated analysis and dissemination of results allowed close to real-time communication of relevant issues among general practice workers, researchers and policy-makers. A conceptual model is presented to support longitudinal analysis of primary care worker experiences during the COVID-19 pandemic in Australia and New Zealand, and key learnings from applying this novel method are discussed. This paper will assist future research teams in development and execution of policy-relevant research in times of change and may inform further areas of interest for COVID-19 research in primary care.
A novel sub-regional radiomics model to predict immunotherapy response in non-small cell lung carcinoma
Authors: Peng Jie , Zou Dan , Zhang Xudong , Ma Honglian , Han Lijie , Yao Biao 
Published: January 2024

Abstract
Background
Identifying precise biomarkers of immunotherapy response for non-small cell lung carcinoma (NSCLC) before treatment is challenging. This study aimed to construct and investigate the potential performance of a sub-regional radiomics model (SRRM) as a novel tumor biomarker in predicting the response of patients with NSCLC treated with immune checkpoint inhibitors, and test whether its predictive performance is superior to that of conventional radiomics, tumor mutational burden (TMB) score and programmed death ligand-1 (PD-L1) expression.

Methods
We categorized 264 patients from retrospective databases of two centers into training (n = 159) and validation (n = 105) cohorts. Radiomic features were extracted from three sub-regions of the tumor region of interest using the K-means method. We extracted 1,896 features from each sub-region, resulting in 5688 features per sample. The least absolute shrinkage and selection operator regression method was used to select sub-regional radiomic features. The SRRM was constructed and validated using the support vector machine algorithm. We used next-generation sequencing to classify patients from the two cohorts into high TMB (≥ 10 muts/Mb) and low TMB (< 10 muts/Mb) groups; immunohistochemistry was performed to assess PD-L1 expression in formalin-fixed, paraffin-embedded tumor sections, with high expression defined as ≥ 50% of tumor cells being positive. Associations between the SRRM and progression-free survival (PFS) and variant genes were assessed.

Results
Eleven sub-regional radiomic features were employed to develop the SRRM. The areas under the receiver operating characteristic curve (AUCs) of the proposed SRRM were 0.90 (95% confidence interval [CI] 0.84−0.96) and 0.86 (95% CI 0.76−0.95) in the training and validation cohorts, respectively. The SRRM (low vs. high; cutoff value = 0.936) was significantly associated with PFS in the training (hazard ratio [HR] = 0.35 [0.24−0.50], P < 0.001) and validation (HR = 0.42 [0.26−0.67], P = 0.001) cohorts. A significant correlation between the SRRM and three variant genes (H3C4, PAX5, and EGFR) was observed. In the validation cohort, the SRRM demonstrated a higher AUC (0.86, P < 0.001) than that for PD-L1 expression (0.66, P = 0.034) and TMB score (0.54, P = 0.552).

Conclusions
The SRRM had better predictive performance and was superior to conventional radiomics, PD-L1 expression, and TMB score. The SRRM effectively stratified the progression-free survival (PFS) risk among patients with NSCLC receiving immunotherapy.
Risk factors for postoperative delirium in patients with Stanford type A aortic dissection: a systematic review and meta-analysis
Authors: Lu Shan , Jiang Yi , Meng Fangfang , Xie Xiaoli , Wang Dongjin , Su Yunyan 
Published: January 2024

Abstract
Background
Delirium is a common postoperative complication among patients who undergo Stanford Type A aortic dissection (TAAD). It is associated with increased mortality, as well as other serious surgical outcomes. This study aimed to analyze the risk factors for delirium in TAAD patients.

Methods
Pubmed, Web of science, Embase, the Cochrane Library and CINAHL were searched by computer to collect literatures on risk factors for postoperative delirium (POD) after TAAD. The retrieval period was from the establishment of the database to September 2022. After literature screening, two reviewers independently assessed the quality of the included studies using the Newcastle–Ottawa Scale (NOS). Data were extracted according to standard protocols, and then meta-analysis was performed using Revman 5.3 software.

Results
A total of 9 articles, comprising 7 case–control studies and 2 cohort studies, were included in this analysis. The sample size consisted of 2035 patients. POD was associated with increased length of ICU stay (MD 3.24, 95% CI 0.18–6.31, p = 0.04) and length of hospital stay (MD 9.34, 95% CI 7.31–11.37, p < 0.0001) in TAAD patients. Various perioperative risk factors were identified, including age (MD 4.40, 95% CI 2.06–6.73, p = 0.0002), preoperative low hemoglobin levels (MD − 4.44, 95% CI − 7.67 to − 1.20, p = 0.007), body mass index (MD 0.92, 95% CI 0.22–1.63, p = 0.01), history of cardiac surgery (OR 3.06, 95% CI 1.20–7.83, p = 0.02), preoperative renal insufficiency (OR 2.50, 95% CI 1.04–6.04, p = 0.04), cardiopulmonary bypass (CPB) duration (MD 19.54, 95% CI 6.34–32.74, p = 0.004), surgery duration (MD 44.88, 95% CI 5.99–83.78, p = 0.02), mechanical ventilation time (SMD 1.14, 95% CI 0.34–1.94, p = 0.005), acute physiology and chronic health evaluation (APACHE II) score (MD 2.67, 95% CI 0.37–4.98, p = 0.02), postoperative renal insufficiency (OR 2.82, 95% CI 1.40–5.68, p = 0.004), electrolyte disturbance (OR 6.22, 95% CI 3.08–12.54, p < 0.0001) and hypoxemia (OR 3.56, 95% CI 1.70–7.44, p = 0.0007).

Conclusions
POD can prolong ICU stay and hospital stay in TAAD patients. This study identified a number of risk factors for POD after TAAD, suggesting the possibility of early identification of high-risk patients using relevant data.
Poly-3-hydroxybutyrate-co-3-hydroxyvalerate(PHBV)-Polyethylene glycol 20k(PEG20k) as a promising delivery system for PT2399 in the treatment of disc degeneration
Authors: Li Zhencong , Zhang Weilin , Huang Shengbang , Dai Zhiwen , Liang Jinguo , Qiu Qiulan , Chen Siyuan , Guo Weixiong , Wang Zhongwei , Wei Jinsong 
Published: January 2024

AbstractDisc degeneration often leads to a highly prevalent symptom known as low back pain. Healthy nucleus pulposus tissue exhibited a hypoxic environment devoid of blood vessels, while degenerated nucleus pulposus experienced hypoxic deterioration and the formation of new blood vessels. In this study, the expression of important genes like HIF-2α was found to vary between normal and degenerated nucleus pulposus cells when compared to the hypoxic surroundings. The aim of this study was to examine how HIF-2α is controlled in nucleus pulposus cells under hypoxic conditions and its role in angiogenic mechanisms. To assess the impact of gradual inhibition of HIF-2α on disc degeneration, we utilized PHBV-based synthetic materials loaded with inhibitors of HIF-2α. Specifically, we employed LPS and PT2399 loaded PHBV-PEG20k (PP20) to intervene with human nucleus pulposus cells. Additionally, we treated APD rat models with PT2399 loaded PP20 to evaluate its effects. The expression levels of target markers in nucleus pulposus cells were detected using PCR, WB, and immunofluorescence. Additionally, the effect of drugs on disc degeneration was identified through HE staining. The findings indicated that HIF-2α, CAIX, PPP1R15A, VEGFA, and EGLN3 could potentially serve as new indicators of disc degeneration. Additionally, HIF-2α might contribute to the progression of disc degeneration through involvement in angiogenesis and the regulation of hypoxia. Furthermore, the utilization of PT2399 loaded PHBV-PEG20k (PP20) could potentially offer a fresh alternative for treating disc degeneration.
Risk factors for tick attachment in companion animals in Great Britain: a spatiotemporal analysis covering 2014–2021
Authors: Arsevska Elena , Hengl Tomislav , Singleton David A. , Noble Peter-John M. , Caminade Cyril , Eneanya Obiora A. , Jones Philip H. , Medlock Jolyon M. , Hansford Kayleigh M. , Bonannella Carmelo , Radford Alan D. 
Published: January 2024

Abstract
Background
Ticks are an important driver of veterinary health care, causing irritation and sometimes infection to their hosts. We explored epidemiological and geo-referenced data from > 7 million electronic health records (EHRs) from cats and dogs collected by the Small Animal Veterinary Surveillance Network (SAVSNET) in Great Britain (GB) between 2014 and 2021 to assess the factors affecting tick attachment in an individual and at a spatiotemporal level.

Methods
EHRs in which ticks were mentioned were identified by text mining; domain experts confirmed those with ticks on the animal. Tick presence/absence records were overlaid with a spatiotemporal series of climate, environment, anthropogenic and host distribution factors to produce a spatiotemporal regression matrix. An ensemble machine learning spatiotemporal model was used to fine-tune hyperparameters for Random Forest, Gradient-boosted Trees and Generalized Linear Model regression algorithms, which were then used to produce a final ensemble meta-learner to predict the probability of tick attachment across GB at a monthly interval and averaged long-term through 2014–2021 at a spatial resolution of 1 km. Individual host factors associated with tick attachment were also assessed by conditional logistic regression on a matched case–control dataset.

Results
In total, 11,741 consultations were identified in which a tick was recorded. The frequency of tick records was low (0.16% EHRs), suggesting an underestimation of risk. That said, increased odds for tick attachment in cats and dogs were associated with younger adult ages, longer coat length, crossbreeds and unclassified breeds. In cats, males and entire animals had significantly increased odds of recorded tick attachment. The key variables controlling the spatiotemporal risk for tick attachment were climatic (precipitation and temperature) and vegetation type (Enhanced Vegetation Index). Suitable areas for tick attachment were predicted across GB, especially in forests and grassland areas, mainly during summer, particularly in June.

Conclusions
Our results can inform targeted health messages to owners and veterinary practitioners, identifying those animals, seasons and areas of higher risk for tick attachment and allowing for more tailored prophylaxis to reduce tick burden, inappropriate parasiticide treatment and potentially TBDs in companion animals and humans. Sentinel networks like SAVSNET represent a novel complementary data source to improve our understanding of tick attachment risk for companion animals and as a proxy of risk to humans.

Graphical Abstract
Response of rhizosphere soil physicochemical properties and microbial community structure to continuous cultivation of tobacco
Authors: Gong Bo , He Yi , Luo Zhenbao , Peng Huawei , Cai Heqing , Zhu Yuening , Bin Jun , Ding Mengjiao 
Published: January 2024

Abstract
Purpose
The health of rhizosphere soil microorganisms is an important indicator to evaluate soil quality. Therefore, understanding the response of rhizosphere soil microorganisms to tobacco crop succession is crucial for promoting the sustainable development of agriculture.

Methods
The microbial diversity and community structure of rhizosphere soil in continuous cropping and non-cropped tobacco for 7 years were analyzed by the Illumina platform.

Result
(1) Continuous cropping tobacco cause rhizosphere soil acidification and reduction in alkaline nitrogen (AN) and soil organic matter (SOM). (2) Continuous cropping tobacco reduces the diversity of rhizosphere soil microbial communities, increasing harmful functional microorganisms and declining beneficial ones. (3) The abundance of bacteria that perform nitrification and saprophytic fungi in the rhizosphere soil of continuous cropping areas decreases, inhibiting carbon and nitrogen cycling processes. (4) The composition and diversity of the soil rhizosphere microbial community are affected by the imbalance in the physicochemical property of the rhizosphere.

Conclusion
Continuous cropping tobacco cause rhizosphere soil acidification and nutrient imbalance, and the carbon and nitrogen cycles involved in microorganisms were damaged. Furthermore, the decreased diversity of rhizosphere soil microorganisms and the increased abundance of pathogenic fungi contribute to the continuous cropping obstacles of tobacco.
Comparative analysis of classical and Caputo models for COVID-19 spread: vaccination and stability assessment
Authors: Tassaddiq Asifa , Qureshi Sania , Soomro Amanullah , Arqub Omar Abu , Senol Mehmet 
Published: January 2024

AbstractSeveral epidemiological models use the Caputo fractional-order differential operator without establishing its significance. This study verifies a Caputo operator-based fractional-order epidemiological model of the SAIVR type. COVID-19 kills. Infection weakens the immune system. The fractional Caputo operator describes COVID-19 immunization. Fundamental system characteristics are determined using fractional calculus. Our analysis included the fractional system’s Hyers–Ulam–Rassias stability and stable states. The uniqueness and existence of fractional Caputo system solutions are explored. The least-squares approach determines system parameters. The Caputo fractional-orderαvalue is optimized to$6.757\text{e}{-}01$6.757e−01, indicating that the system best fits real-life medical data for infection. Caputo and classical systems were compared for absolute mean errors. The Box-Whisker chart case summaries show the Caputo operator superiority. When$\alpha \rightarrow 1$α→1, the memory traces and hereditary traits are also observed. Finally, the Caputo fractional framework simulates COVID-19 using strong numerical methods.
Food miles on the shelves: the share of local food products in the Hungarian retail sector
Authors: Kasza Gyula , Oláh Judit , Popp József , Lakner Zoltán , Fekete László , Pósa Enikő , Nugraha Widya Satya , Szakos Dávid 
Published: January 2024

AbstractShare of national food products in retail is a frequent subject of policy debates. Local food is often associated with national security, sustainability, and support of local economy, contributing to value-added production, employment, rural development, and preservation of local food culture. Despite its importance, relevant academic literature about the proportion of national food in retail is basically non-existent. This paper presents a unique study that fills this gap and gives an account of the proportion of the main national food products in the Hungarian retail sector. The study presents a comprehensive picture of the food supply situation of the 10 largest retail chains in Hungary in the second half of 2020 for 16 key product categories (representing 67% of total food sales in value in the country), based on the experience of research that covered the physical examination of nearly 40 thousand individual food products. The study found that 70.85% of the analysed food products were supplied by domestic companies. Proportion of national products was higher for fresh food (meat, milk, perishable meat and milk products, eggs, fruits, and vegetables) and honey, while imports were dominant in higher value-added categories. Domestic chains had 15.37% points more local products in stock than international ones. The exact results can be used for benchmarking between companies and sectors, indicating comparative advantages and disadvantages, and provide solid basis for economic development plans.