bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cell-type-specific response to silicon treatment in soybean leaves revealed by single nucleus RNA-sequencing and targeted gene-editing
Authors: Patil Gunvant , Devkar Vikas , D’Agostino Leonidas , Kshetry Arjun , Yong-Villalobos Lenin , Nadaf Altafhusain , Thirumalaikumar Venkatesh , Skirycz Aleksandra , Ma Jianxin , Stupar Robert , Herrera-Estrella Luis , Deshmukh Rupesh 
Published: July 2024

Abstract

In agriculture, mineral nutrient uptake and deposition profoundly influences plant development, stress resilience, and productivity. Despite its classification as a non-essential element, silicon (Si) uptake and deposition alters plant physiology and particularly improves defense response and stress mitigation. While genetic and molecular mechanisms of Si uptake and transport are well-studied in monocots, particularly rice, its role in dicot species, such as soybean, remains unclear at the cellular and molecular levels. Traditional bulk transcriptomics methods lack the resolution to uncover cellular heterogeneity. Here, we present a study utilizing single-nucleus RNA sequencing (snRNA-seq) to dissect cellular responses to Si accumulation in soybean leaves. Our analysis revealed distinct cellular populations, including a novel Si-induced cell cluster within vascular cells, suggesting a specific mechanism of Si distribution. Si treatment induced the expression of defense-related genes, particularly enriched in vascular cells, highlighting their specialized role in activating plant defense mechanisms. Moreover, Si modulated the expression of genes involved in RNA silencing, phytoalexin biosynthesis, and immune receptor signaling, suggesting transcriptional priming of genes involved in defense responses. We also investigated putative Si transporters, revealing differential expression patterns in response to Si treatment, suggesting presence of active and gradient-based transport mechanisms. Furthermore, by employing CRISPR/Cas9 genome editing we functionally validated the role of efflux Si transporters in composite soybean plants. Our findings shed light on the vital biotic stress regulatory networks governed by Si treatment in soybean leaves, paving potential strategies for enhancing stress tolerance and agronomic performance in crops.
Machine learning-based prediction of return to work within 12 months in acute myocardial infarction patients
Authors: Wu Xiaojun , Wang Shiyu , Cui Haoning , Zheng Xianghui , Hou Xinyu , Wang Zhuozhong , Li Qifeng , Liu Qi , Cao Tianhui , Zheng Yang , Wu Jian , Yu Bo 
Published: July 2024

Abstract

Return to work is a critical indicator of recovery after acute myocardial infarction (AMI), and accurate identification of patients with low return-to-work rates is critical for timely intervention. The aim of this study was to develop a machine learning (ML) model for predicting the return to work in AMI patients. A retrospective study of data from 1473 patients was conducted using the Incidence Rate of Heart Failure After Acute Myocardial Infarction With Optimal Treatment database. Patients were randomly divided into a training cohort and a validation cohort (7:3). A total of five ML models were developed based on the training cohort to predict return to work. Model performance was assessed according to numerous learning metrics, including the area under the receiver operating characteristic curve (AUC), accuracy, F1-score, and Brier score. The ML models were constructed using 12 features, including age, occupation, income, anterior wall AMI, hypertension, fasting plasma glucose (FPG), beta-blockers, marriage, aspartate transaminase (AST), body mass index (BMI), TG (triglyceride) and phase II cardiac rehabilitation (CR). Among the five ML models, the LR model achieved the best performance, with an AUC of 0.793 (95% CI, 0.712-0.874), an accuracy of 0.719 (95% CI, 0.642-0.787), an F1 score of 0.800, and a Brier score of 0.135, and was subsequently transformed into a nomogram. A new return-to-work prediction model was developed based on a machine learning algorithm, which may help identify patients with low return-to-work rates and may become an effective management tool for AMI patients.
Clinical trial registration: Clinical Trials.gov ID: NCT03297164.
Incidence of Diabetic Retinopathy and Predictors among Adult Diabetic Patients in Central and Southern Ethiopia: A Multicentre Retrospective Cohort Study.
Authors: Barata Tagese Yakob , Abiraham Awoke , Yakob Begidu , Menza Mesfin 
Published: July 2024

Abstract

Background
Diabetic retinopathy (DR) is emerging as a global public health issue that may result in visual impairment. It has become the leading cause of blindness among working-age adults globally, despite established treatments that can reduce the risk by 60%. Disease progression, as indicated by longitudinal HbA1c measurements, may affect the time of interest (retinopathy). Hence, poor glycemic control increases and hastens the risk of retinopathy.
Objective
This study aimed to determine the incidence of diabetic retinopathy and its predictors among adult diabetic patients in public hospitals in Central and Southern Ethiopia.
Methods
A retrospective follow-up study was conducted at selected hospitals in Central and Southern Ethiopia among newly diagnosed patients with adult diabetes between January 1, 2015, and June 30, 2022. A systematic random sampling technique was applied. The data were collected and entered into Epi-data version 4.6.0.2 and exported to STATA version 14 for analysis. Descriptive statistics of the variables were obtained. The Cox proportional hazard assumption was checked. The Cox regression model was used to quantify the effects of covariates on the time to diabetic retinopathy. A p value less than 0.25 was the cut-off point for selecting variables for the bivariable analysis and candidates for the final analysis. In the multivariable analysis, variables with a p value less than 0.05 and a corresponding 95% confidence interval in the final model were used. Model adequacy was checked.
Results
A total of 376 adult diabetic patients were followed for 45752 person-months. Overall, 96 (25.5%) patients developed diabetic retinopathy, with an incidence rate of 11.7 per 1000 person-months of observation. Positive proteinuria (AHR = 2.19: 95% CI: 1.18, 4.08), hypertension (Yes) (AHR = 2.23: 95% CI: 1.39, 3.55) and type II DM (AHR = 2.89: 95% CI: 1.19, 7.05) were identified as significant predictors of diabetic retinopathy.
Conclusion
The incidence rate of diabetic retinopathy was high. Hypertension, proteinuria and type of diabetes were identified as predictors of diabetic retinopathy. Aggressive management should be implemented, and DM patients with hypertension and positive proteinuria should be followed to optimize positive outcomes.
Investigating the Influence of Working Status Changes on Physical Activity and Non-Communicable Diseases in Korean Middle-Aged and Older Adults: Insights from a Longitudinal Panel Study
Authors: Park Jeong-Hui , Choe Ju-Pil , Kim Jisu , Hwang In-Whi , Lee Jung-Min 
Published: July 2024

Abstract

Purpose
The primary aim of the present study was to comprehensively elucidate the intricate interplay between alterations in working status, Non-Communicable Diseases (NCDs), and physical activity (PA) among Korean middle-aged and older adults, employing a longitudinal panel study design.
Methods
This study analyzed longitudinal data from the Korean Longitudinal Study of Aging (2006–2020) with 40,808 participants aged 45 years and older. Changes in working status were categorized, focusing on (1) yes – yes (e.g., indicative of sustained employment), (2) yes – no (e.g., denoting a transition from employment to non-employment), (3) no – yes (e.g., representing a shift from non-employment to employment), and (4) no – no (reflecting a continual non-employment status). The study examined prevalent NCDs (e.g., cardiovascular diseases, diabetes, cancer, chronic respiratory diseases) and their association with working status and PA using a chi-square test and random-effect multinomial logistic regression.
Results
Individuals currently employed (adjusted RRR = 0.688, p = 0.000) or transitioning to employment (adjusted RRR = 0.755, p = 0.000) had a heightened risk of physical inactivity. Those engaged in work exhibited an elevated risk of cardiovascular diseases (yes – yes: adjusted RRR = 1.653, p = 0.000; no – yes: adjusted RRR = 1.168, p = 0.000) and diabetes (yes – yes: adjusted RRR = 1.535, p = 0.000; no – yes: adjusted RRR = 1.124, p = 0.000) compared to those never employed. Furthermore, current workers demonstrated a heightened risk of cancer (yes – yes: adjusted RRR = 1.871, p = 0.000; no – yes: adjusted RRR = 1.089, p = 0.014) and chronic respiratory diseases (yes – yes: adjusted RRR = 1.467, p = 0.000; no – yes: adjusted RRR = 1.121, p = 0.029) than those never employed during the survey.
Conclusion
This longitudinal study revealed that individuals engaged in or transitioning to employment displayed a reduced likelihood of regular PA. Moreover, those with work history, transitioning, or consistently working, exhibited increased vulnerability to all NCDs compared to those without work experience.
Optimization of the elderly multimorbidity management model: A study on the mediating effect of health literacy on self-efficacy and health status
Authors: Li Linjin , Xu Zhaoyi , Zhang Dan 
Published: July 2024

Abstract

Background
The prevalence of chronic diseases and chronic comorbidities among the elderly is increasing annually with the advent of an aging population, making health management for elderly patients with chronic conditions essential. Therefore, this study aims to analyze the relationship between self-efficacy, health literacy, and health status among elderly comorbid patients, and further explore the potential mechanisms by which self-efficacy and health literacy influence health status. The goal is to provide a scientific basis for optimizing the content of elderly comorbidity management models and improving the health status of patients.
Methods
Adopting a multistage stratified cluster random sampling method, elderly multimorbidity patients in communities of Shenzhen, Guangdong Province were selected as the survey subjects. Using the "Health Survey Questionnaire for Elderly Multimorbidity Patients" for face-to-face interviews, 1200 elderly individuals were surveyed, and 987 valid patient data were selected. Descriptive analysis was conducted on the self-efficacy, health literacy, and health status of elderly multimorbidity patients in Shenzhen, Guangdong Province. A structural equation model was constructed to analyze the mediating effect of health literacy between self-efficacy and health status.
Results
In the survey of 987 elderly multimorbidity patients in this study, the average score for self-efficacy was 8.07 ± 1.36, indicating a high level on average; the average score for health literacy was 32.16 ± 9.39, suggesting a possible inadequacy in health literacy level; and the average score for health status was 73.60 ± 19.70. The well-fitted structural equation model results demonstrate that self-efficacy and health literacy of elderly multimorbidity patients have a positive impact on health status. Specifically, the mediating effect of health literacy on the relationship between self-efficacy and health status accounts for 38.3% of the total effect, serving as a partial mediator with a significant mediating effect.
Conclusions
In the multimorbidity management model for the elderly, it is essential to incorporate interventions to enhance patient self-efficacy and improve health literacy in order to promote the health of patients.
Detection of gallstone-related disease using dual-energy CT and effective atomic number analysis
Authors: Lo Luzinda , Smith Callum , Hassam Shabeer 
Published: July 2024

Abstract

Introduction: This audit aims to evaluate the utility of dual-energy computed tomography (DECT) in accurately identifying gallstone-related disease. Preferred imaging modalities such as ultrasound (US) and magnetic resonance cholangiopancreatography (MRCP) have high sensitivity for identifying cholesterol stones which are radiolucent on conventional CT, however, are limited by their availability. This audit seeks to assess whether the analysis of post-processed dual energy datasets may be able to provide more thorough analysis of the biliary system and enhance gallstone visibility.
Methods: Retrospective audit series of dual energy contrast-enhanced CT abdomen examinations performed for acute abdominal pain at our hospital over 6 months. All CT studies were evaluated by two Radiology registrars for the presence of gallstone-related disease using conventional DECT and post processing material decomposition images. This was correlated with complementary modalities (US, MRCP and ERCP), to assess their effect in improving radiolucent gallstone visualisation.
Results: The final data set included 69 patients with gallstone related disease. Stone composition analysis identified 36 patients with poorly seen gallstone-related disease on DECT before post-processing; which included 28 patients with predominantly cholesterol-containing stones, 6 patients with sludge, and 2 patients with pigmented stones. Post-processing increased conspicuity in 50% of the examined patients (n=18).
Conclusion: DECT is underutilised at many Australian hospitals, including our own. Our findings demonstrate that post-processed DECT atomic number maps have the potential to enhance conspicuity of cholesterol gallstones in a subset of patients.
Informant Accuracy of IQCODE, AD8 and GPCOGi for diagnosis of dementia: Does your friend know best?
Authors: Chingono Jasmine , Creavin Samuel Thomas , Fish Mark , Cullum Sarah , Bayer Antony , Purdy Sarah , Ben-Shlomo Yoav 
Published: July 2024

Abstract

Background

Increasing numbers of people are requiring evaluation for possible dementia. There has been limited research exploring the accuracy of informant questionnaires in primary care.

Methods

A diagnostic accuracy study to explore the influence of informant relationship type on the accuracy of IQCODE, AD8 and GPCOGi in primary care.
240 participants were recruited from 21 general practitioner (GP) surgeries in the South West of England.
The reference standard for a diagnosis of dementia was made against ICD-10 criteria based on specialist clinician assessment. A threshold of greater than 3.3 on IQCODE, greater or equal to 2 on AD8 and less than 5 on the informant component of GPCOG (GPCOGi) was used to indicate an abnormal test.

Results

Of 238 participants with informant data, 131 had dementia, 60 CIND, and 47 had normal cognition. Median informant age was 70 years (IQR 60 years to 78 years). 71% of informants were female and 56% of informants were spouses.
On all three questionnaires, compared to spouses, adult descendants tended to score participants more cognitively impaired, whereas friends scored participants less cognitively impaired. However, there was little evidence of difference by informant relationship type once fully adjusted.
Overall accuracy was similar for all three informant questionnaires with an AUROC of 0.67 (95% CI, 0.62 to 0.72) for IQCODE, 0.64 (95% CI, 0.60 to 0.69) for AD8 and 0.59 (95% CI, 0.56 to 0.63) for GPCOGi. Friends tended to have the highest AUROC at 0.89 (95% CI 0.78 to 1) for IQCODE, 0.88 (95% CI 0.77 to 0.99) for AD8 and 0.69 (95% CI 0.57 to 0.81) for GPCOGi. This difference was significant for IQCODE (p=0.0004) and AD8 (p=0.0001).

Conclusions

Most informants were either a spouse or adult descendant. Overall, informants, when using IQCODE, AD8 or GPCOGi may be useful at ruling out dementia but less useful for ruling it in. We found no evidence of difference between spouse or adult descendants but friends (while accounting for only 8% of informants) performed significantly better overall on IQCODE and AD8 due to an increase in specificity without loss of sensitivity.
Diffusion tensor imaging analysis of aged dogs with and without canine cognitive dysfunction
Authors: Henry Jamie , Ukai Masayasu , Antonakakis Markos , Zhou Tianjian , Moreno Julie A. , Burzynska Agnieszka Z. , McGrath Stephanie 
Published: July 2024

Abstract

Background
Canine cognitive dysfunction (CCD) is a naturally occurring disease in aged dogs that shares many behavioural and pathological similarities with Alzheimer’s disease. There has been little research on in vivo imaging of CCD, and to the best of our knowledge, no studies have investigated the use of diffusion tensor imaging (DTI) to visualize brain atrophy. The primary aim of this study was to determine the applicability of DTI for imaging various regions of the canine brain. A secondary aim was to determine whether DTI could be used to differentiate healthy aging dogs from dogs with CCD. We hypothesized that DTI could be used to image the canine brain, providing insight into the diffusivity of axons in various regions, and could reveal differences in DTI parameters between dogs with and without CCD. DTI was used to measure the mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD) and radial diffusivity (RD) in the corpus callosum (CC) and thalamus of the dogs.
Results
Our data revealed that DTI can be used to image the diffusivity of the CC and thalamus and revealed an overall decrease in the mean FA and increase in the mean MD, AxD, and RD in these two structures in dogs with CCD compared to healthy dogs. Further research is required to determine whether DTI has the ability differentiate aged dogs from dogs with CCD.
Conclusions
These results demonstrated that DTI could be used to evaluate white matter integrity in the canine brain with and without CCD, indicating that the use of DTI could provide valuable insight into neuropathological changes due to CCD, revealing further translational applicability of CCD as a model for AD.
Association of serum creatinine variability and risk of 1-year mortality among patients with cancer
Authors: Li Lin , Yang Huanhuan , Zhang Yi , Liu Jianchao , Li Shunfei , Wang Lijun , Liu Yunning , Li Wen-Qing , Chen Guo-Chong , Liu Wei , Li Zhihui 
Published: July 2024

Abstract

Creatinine variability has a close and reciprocal relationship with cancer risk. However, the role of creatinine variability on mortality among cancer patients remains unclear. Thus, the objective here is to fill this gap. We conducted a multi-center study including all patients with solid tumors admitted to eight hospitals in China between January 1, 2013, and December 31, 2019, on their primary admission. The variability of blood creatinine was evaluated by the standard deviation (SD) and coefficient of variation(CV). All deaths and causes of death were identified from the Chinese National Center for Disease Control and Prevention (CDC) Surveillance Points System. Analyses were constructed by multiple Cox regression models. The study comprised a total of 41,911 cancer patients, of which 9,050 events were observed. Higher serum creatinine fluctuation was associated with an elevated risk of one-year mortality significantly, with a hazard ratio of 1.62 (95% confidence interval, 1.52-1.72; P <0.001) for the standard deviation of creatinine in quartile four compared with quartile one. Furthermore, the association persisted even though all creatinine was within the clinically normal range. The coefficient of variation of creatinine showed similar results. Higher serum creatinine fluctuation during hospital admission is associated with an elevated risk of one-year mortality among cancer patients, even if the fluctuation is within the clinically normal range.
Can self-rated health be useful to primary care physicians as a diagnostic indicator of metabolic dysregulations amongst patients with type 2 diabetes? A population-based study
Authors: Umeh Kanayo , Adaji S 
Published: July 2024

Abstract

Background
Although most of the management of type 2 diabetes (T2DM) occurs in primary care, and physicians are tasked with using a ‘whole person’ approach, there is currently a lack of research on psychosocial diagnostic indicators for detecting metabolic abnormalities in T2DM patients. This study examined relations between SRH and metabolic abnormalities in patients with type 2 diabetes, adjusting for metabolic comorbidity.
Method
A total of 583 adults with type 2 diabetes were identified from the 2019 HSE (Health Survey for England). Data on metabolic syndrome (MetS) was extracted, including lipids (high density lipoprotein cholesterol (HDL-C)), glycated haemoglobin (HbA1c), blood pressure (systolic/diastolic), and anthropometric measures (BMI, waist/hip ratio). Bootstrapped hierarchical regression and structural equation modelling (SEM) were used to analyse the data.
Results
Adjusting for metabolic covariates attenuated significant associations between SRH and metabolic abnormalities (HDL-C, HbA1c), regardless of MetS status. However, relations between SRH and HbA1c remained marginally significant, after metabolic adjustments (β = -0.15, p = 0.04). Analysis by gender uncovered covariate-adjusted associations between SRH and both HDL-C (in men) and HbA1c (in women) (p’s = 0.01). SEM revealed no indirect associations between SRH, metabolic abnormalities, and lifestyle factors.
Conclusions
SRH may help primary care physicians identify T2DM patients with HDL-C and HbA1c abnormalities, irrespective of comorbid metabolic biomarkers.
Design and development of metal-organic framework-based nanocomposite hydrogels for quantification of deferiprone in exhaled breath condensate
Authors: Moharami Reza , Karimzadeh Zahra , Soleymani Jafar , Jouyban-Gharamaleki Vahid , Khoubnasabjafari Maryam , Rahimpour Elaheh , Jouyban Abolghasem 
Published: July 2024

Abstract

In this study, a novel fluorescence nanoprobe based on MIL-101 metal-organic frameworks embedding into the agarose hydrogel was fabricated using a hydrothermal technique and used for sensitive quantification of deferiprone in exhaled breath condensate (EBC) samples. The morphology and characterization of MIL-101/agarose nanocomposite hydrogel was studied by transmission electron microscopy, dynamic light scattering instrument, powder X-ray diffraction analysis, and Fourier transform infrared spectroscopy. The probe showed a reasonable fluorescence intensity quenching in the presence of deferiprone due to the interactions between iron centers in MIL-101 (Fe) and deferiprone, which likely formed non-fluorescent complexes. The proposed nanoprobe demonstrated a linear calibration curve in the range from 0.005 to 1.5 µg mL− 1 with a detection limit of 0.003 µg mL− 1. The intra- and inter-day precision for determinations of deferiprone with concentration of 1.0 µg mL− 1were 0.3% and 0.4% (n = 5), respectively. This method demonstrated high sensitivity and specificity towards deferiprone in the EBC samples and also presented a sensing platform with simplicity, convenience, fast implementation, and cost-effective in medical monitoring.