bluuebunny/crossref_metadata_2025 huggingface dataset:
Balancing productivity and carbon emissions: the potential for carbon reduction in wheat fertilization practices in China
Authors: Qi Li , Li Yanan
Published: July 2024

The irrational application of chemical fertilizers in wheat cultivation not only threatens the agricultural ecosystem but also significantly contributes to carbon emissions, impeding the achievement of “carbon peaking” and “carbon neutrality” goals. The objective of this research is to assess the efficiency of chemical fertilizer use in wheat production across ten major wheat-producing provinces in China from 2004 to 2020. We employed a stochastic frontier production function to evaluate the technical efficiency of fertilizer use, determining feasible reduction levels. The Gini coefficient, kernel density estimation, and Markov chain analysis were further utilized to dissect the spatio-temporal dynamics of carbon emission reduction potential. Our findings provide a detailed analysis of the carbon emission reduction potential in wheat chemical fertilizer use across China’s ten major wheat-producing provinces from 2004 to 2020. The average carbon emission reduction potential is significant, at 251.1 kg CE/hm2, with considerable variation observed among regions. The western region, in particular, stands out with the highest potential, reaching up to 336.51 kg CE/hm2, which is notably higher compared to the eastern (230.05 kg CE/hm2) and central regions (158.28 kg CE/hm2). The spatial distribution of this potential is uneven, and the disparities are progressively increasing, primarily due to inter-regional differences. Despite a general decline in carbon reduction potential, the spatial distribution remains relatively consistent. To foster sustainable wheat production, it is imperative to prioritize the western region for targeted chemical fertilizer carbon reduction initiatives. Attention must also be given to the issue of regional disparities in low-carbon wheat production. Enhancing the role of soil testing and fertilizer recommendations is essential to increase the effectiveness of carbon reduction efforts. Additionally, a multi-faceted approach that incorporates various alternative measures is necessary to drive further reductions in chemical fertilizer-related carbon emissions.
Expression of a stress-inducible heme oxygenase-1 in NK cells is maintained in the process of human aging
Authors: Kaszubowska Lucyna , Kaczor Jan Jacek , Karnia Mateusz Jakub , Foerster Jerzy , Kmieć Zbigniew
Published: July 2024

Introduction

Heme oxygenase-1 (HO-1) is a stress-inducible heat shock protein (HSP32) that exerts cytoprotective effects against oxidative stress and inflammation, and is involved in the maintenance of cellular homeostasis. This study aimed to evaluate the expression of HO-1 in natural killer (NK) cells from individuals of different age groups after stimulation with various factors, and to analyze the relationships between the concentration of this cytoprotective protein and parameters corresponding to oxidative stress and inflammation, that is, NOD-like receptor protein 3 (NLRP3), glutathione (GSH), GSH disulfide (GSSG), and interleukin 6 (IL-6).

Methods

The study population comprised three age groups: young adults (age range, 19–23 years), older adults aged under 85 years (age range, 73–84 years), and older adults aged over 85 years (age range, 85–92 years). NLRP3, GSH, and GSSG concentrations were measured in serum, whereas the HO-1 concentration and IL-6 expression were studied in NK cells cultivated for 48 h and stimulated with IL-2, lipopolysaccharide (LPS), or phorbol 12-myristate 13-acetate (PMA) with ionomycin.

Results

The analysis of serum NLRP3, GSH, and GSSG concentrations revealed no statistically significant differences among the studied age groups. However, some typical trends of aging were observed, such as a decrease in GSH concentration and an increase in both GSSG level, and GSSG/GSH ratio. The highest basal expression of IL-6 and lowest basal content of HO-1 were found in NK cells of adults over 85 years of age. The NK cells in this age group also showed the highest sensitivity to stimulation with the applied factors. Moreover, statistically significant negative correlations were observed between HO-1 and IL-6 expression levels in the studied NK cells.

Conclusions

These results showed that NK cells can express HO-1 at a basal level, which was significantly increased in activated cells, even in the oldest group of adults. The reciprocal relationship between HO-1 and IL-6 expression suggests a negative feedback loop between these parameters.
PSGL-1, ADAM8, and selectins as potential biomarkers in the diagnostic process of systemic lupus erythematosus and systemic sclerosis: an observational study
Authors: San Antonio Esther , Silván Javier , Sevilla-Montero Javier , González-Sánchez Elena , Muñoz-Callejas Antonio , Sánchez-Abad Inés , Ramos-Manzano Alejandra , Muñoz-Calleja Cecilia , González-Álvaro Isidoro , Tomero Eva G. , García-Pérez Javier , García-Vicuña Rosario , Vicente-Rabaneda Esther F. , Castañeda Santos , Urzainqui Ana
Published: July 2024

Background

Early diagnosis and treatment of Systemic lupus erythematosus (SLE) and Systemic sclerosis (SSc) present significant challenges for clinicians. Although various studies have observed changes in serum levels of selectins between healthy donors and patients with autoimmune diseases, including SLE and SSc, their potential as biomarkers has not been thoroughly explored. We aimed to investigate serum profiles of PSGL-1 (sPSGL-1), ADAM8 (sADAM8) and P-, E- and L-selectins (sP-, sE- and sL-selectins) in defined SLE and SSc patient cohorts to identify disease-associated molecular patterns.

Methods

We collected blood samples from 64 SLE patients, 58 SSc patients, and 81 healthy donors (HD). Levels of sPSGL-1, sADAM8 and selectins were analyzed by ELISA and leukocyte membrane expression of L-selectin and ADAM8 by flow cytometry.

Results

Compared to HD, SLE and SSc patients exhibited elevated sE-selectin and reduced sL-selectin levels. Additionally, SLE patients exhibited elevated sPSGL-1 and sADAM8 levels. Compared to SSc, SLE patients had decreased sL-selectin and increased sADAM8 levels. Furthermore, L-selectin membrane expression was lower in SLE and SSc leukocytes than in HD leukocytes, and ADAM8 membrane expression was lower in SLE neutrophils compared to SSc neutrophils. These alterations associated with some clinical characteristics of each disease. Using logistic regression analysis, the sL-selectin/sADAM8 ratio in SLE, and a combination of sL-selectin/sE-selectin and sE-selectin/sPSGL-1 ratios in SSc were identified and cross-validated as potential serum markers to discriminate these patients from HD. Compared to available diagnostic biomarkers for each disease, both sL-selectin/sADAM8 ratio for SLE and combined ratios for SSc provided higher sensitivity (98% SLE and and 67% SSc correctly classified patients). Importantly, the sADAM8/% ADAM8(+) neutrophils ratio discriminated between SSc and SLE patients with the same sensitivity and specificity than current disease-specific biomarkers.

Conclusion

SLE and SSc present specific profiles of sPSGL-1, sE-, sL-selectins, sADAM8 and neutrophil membrane expression which are potentially relevant to their pathogenesis and might aid in their early diagnosis.
The role of innate immune cells in the colorectal cancer tumor microenvironment and advances in anti-tumor therapy research
Authors: Liu Wenxuan , Kuang Tianrui , Liu Li , Deng Wenhong
Published: July 2024

Innate immune cells in the colorectal cancer microenvironment mainly include macrophages, neutrophils, natural killer cells, dendritic cells and bone marrow-derived suppressor cells. They play a pivotal role in tumor initiation and progression through the secretion of diverse cytokines, chemokines, and other factors that govern these processes. Colorectal cancer is a common malignancy of the gastrointestinal tract, and understanding the role of innate immune cells in the microenvironment of CRC may help to improve therapeutic approaches to CRC and increase the good prognosis. In this review, we comprehensively explore the pivotal role of innate immune cells in the initiation and progression of colorectal cancer (CRC), alongside an extensive evaluation of the current landscape of innate immune cell-based immunotherapies, thereby offering valuable insights for future research strategies and clinical trials.
Fertility issues in women of childbearing age with spondyloarthritis
Authors: Bindoli Sara , Cozzi Giacomo , Lorenzin Mariagrazia , Sfriso Paolo , Doria Andrea , Scagnellato Laura , Ramonda Roberta
Published: July 2024

The topic of fertility in women with spondyloarthritis (SpA) has been scarcely investigated to date. Recent systematic reviews and registry studies have brought renewed attention to the plight of women of childbearing age with rheumatic diseases, in particular SpA. Fertility may be impacted by physical impairment, hormonal imbalances and psychological distress. Several studies observed a reduction in anti-Müllerian hormone in women with SpA, reflecting a reduced ovarian reserve (OR). Furthermore, disease activity and the use of certain therapies can alter fertility, and this is reflected in a prolonged time-to-pregnancy (TTP), a validated outcome measure that can evaluate the status of subfertility. The employment of glucocorticoids or non-steroidal anti-inflammatory drugs has also been linked to reduced fertility, whereas the use of biologics, especially tumour necrosis factor inhibitors (TNFi), is not associated with a prolonged TTP. In all women of childbearing age with rheumatic diseases, preconception counselling is paramount, and a referral to a reproductive specialist should be considered in the presence of multiple factors that may influence fertility. A comprehensive evaluation involving a multidisciplinary team of rheumatologists, gynaecologists, and often psychologists is warranted. In this narrative review, we collected the currently available literature focusing on fertility issues in women affected by SpA, providing data on fertility outcomes, hormonal imbalance, and therapeutic concerns.
High-light pronounced the effects of stocking density on photosynthesis and nutrients uptake of the bloom-forming green alga, Ulva linza
Authors: Bao Menglin , Zhang Qi , Xu Zihan , Li Baoqi , Wu Hongyan , Zang Shasha , Yan Fang , Xu Zhiguang , Liu Ning
Published: July 2024

In recent years, the periodic outbreak of green tides in the coastal areas of China, caused by the combined effects of environmental changes and human activities, has been attracting extensive attention due to the serious negative impacts on the coastal marine ecosystem. In the study, the samples of Ulva linza, a green tide species, were cultivated under two light intensities (LL: 80 μmol photons m-2 s-1; HL: 300 μmol photons m-2 s-1) and three stocking densities (LD: 0.2 g L-1; MD:1 g L-1; HD:2 g L-1) to explore the photosynthetic physiological responses and nutrients absorption capacity. The results showed that high light and low density significantly increased the growth rate of U. linza. Under the HLLD, the maximum growth rate of U. linza was 43.13% day-1 and the energy captured per unit reaction center for electron transfer (ET0/RC) was the highest. The higher density significantly decreased the maximum relative electron transfer rate (rETRmax) of U. linza, especially among groups subjected to high-light condition. Under HL condition, HD also significantly decreased light utilization efficiency (α) in U. linza. The contents of chlorophyll a, b and carotenoids of U. linza were significantly lower in HLLD group compared to other treatment groups. The P uptake of U. linza was prominently inhibited by higher density, and the maximum P uptake and minimum P uptake was 17.94 μM g-1 FW day-1 in LLLD group and 2.74 μM g-1 FW day-1 in LLHD group, respectively. Lower density improved N uptake of U. linza, but high light had no effect on it. These results suggest that high light and lower density synergistically promote the growth of U. linza, which is likely due to enhanced photosynthetic efficiency and nutrient uptake. And the inhibitory effects of higher densities on growth, particularly under high-light conditions, may be due to increased competition for light and nutrients. In the late stage of the green tides outbreak, an increase in accumulation density could help to suppress the sustained outbreak of the green tides, particularly in high-light condition.
Utilizing deep learning models in an intelligent eye-tracking system for autism spectrum disorder diagnosis
Authors: Alsharif Nizar , Al-Adhaileh Mosleh Hmoud , Al-Yaari Mohammed , Farhah Nesren , Khan Zafar Iqbal
Published: July 2024

Timely and unbiased evaluation of Autism Spectrum Disorder (ASD) is essential for providing lasting benefits to affected individuals. However, conventional ASD assessment heavily relies on subjective criteria, lacking objectivity. Recent advancements propose the integration of modern processes, including artificial intelligence-based eye-tracking technology, for early ASD assessment. Nonetheless, the current diagnostic procedures for ASD often involve specialized investigations that are both time-consuming and costly, heavily reliant on the proficiency of specialists and employed techniques. To address the pressing need for prompt, efficient, and precise ASD diagnosis, an exploration of sophisticated intelligent techniques capable of automating disease categorization was presented. This study has utilized a freely accessible dataset comprising 547 eye-tracking systems that can be used to scan pathways obtained from 328 characteristically emerging children and 219 children with autism. To counter overfitting, state-of-the-art image resampling approaches to expand the training dataset were employed. Leveraging deep learning algorithms, specifically MobileNet, VGG19, DenseNet169, and a hybrid of MobileNet-VGG19, automated classifiers, that hold promise for enhancing diagnostic precision and effectiveness, was developed. The MobileNet model demonstrated superior performance compared to existing systems, achieving an impressive accuracy of 100%, while the VGG19 model achieved 92% accuracy. These findings demonstrate the potential of eye-tracking data to aid physicians in efficiently and accurately screening for autism. Moreover, the reported results suggest that deep learning approaches outperform existing event detection algorithms, achieving a similar level of accuracy as manual coding. Users and healthcare professionals can utilize these classifiers to enhance the accuracy rate of ASD diagnosis. The development of these automated classifiers based on deep learning algorithms holds promise for enhancing the diagnostic precision and effectiveness of ASD assessment, addressing the pressing need for prompt, efficient, and precise ASD diagnosis.
The influence of eight cognitive training regimes upon cognitive screening tool performance in post-stroke survivors: a network meta-analysis
Authors: Zhou Liqin , Huang Xiaofeng , Wang Jieyu , Wang Fengming , Liu Jihong , Liu Nanhai
Published: July 2024

Background

Traditional meta-analysis offers only direct comparative evidence. The optimal cognitive training for poststroke cognitive impairment (PSCI) remains largely undetermined.

Objectives

This study aims to assess and compare the effectiveness of selected cognitive training methods for PSCI patients and to identify and rank the most effective intervention programs.

Methods

Searches were conducted in PubMed, Embase, Cochrane Library, Web of science, China National Knowledge Infrastructure, China Science and Technology Journal Database, Wanfang Database, and China Biomedical Database for randomized controlled trials up to September 30, 2023. Two researchers independently performed literature screening, data extraction, and quality assessment. Network meta-analysis was utilized to synthesize the main findings. The primary outcome focused on the intervention’s impact on subjective cognitive function, with secondary outcomes including effects on activities of daily living, motor function, and functional independence. This study is registered with PROSPERO (CRD42023463282).

Results

Fifty eligible randomized controlled trials were identified, revealing eight distinct interventions. These interventions collectively demonstrate efficacy in enhancing cognition. Traditional cognitive training significantly improves overall cognitive function, daily living function, motor function, and functional independence. In Loewenstein Occupational Therapy Cognitive Assessment, Barthel Index, Fugl-Meyer Assessment, and Functional Independence Measure scales, a combination of computer-based and traditional cognitive training outperformed the conventional control group MD = 29.97 (95%CI: 16.3, 44.2), MD = 18.67 (95%CI: 9.78, 27.45), MD = 28.76 (95%CI: 5.46, 51.79) and MD = 42.2 (95%CI: 5.25, 78.99). In the MMSE scale, virtual reality cognitive training combined with traditional training was most effective MD = 8.01 (95%CI: 3.6, 12.4). On the MoCA scale, the combination of exercise and cognitive training showed superior results MD = 6.68 (95%CI: 2.55, 10.78). Only the combined computer-based and traditional cognitive training, as well as traditional cognitive training alone, significantly enhanced functional independence, with no notable differences in other pairwise interventions.

Conclusion

The network meta-analysis suggests that augmenting traditional training with other modalities may enhance overall effectiveness. Specifically, interventions incorporating computer-based cognitive training appear to surpass other methods in improving cognition, daily living function, motor skills, and functional independence. The findings of this network meta-analysis provide evidence-based guidance for clinical decision-making.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier in PROSPERO (CRD42023463282).
EEG-based emotion recognition using graph convolutional neural network with dual attention mechanism
Authors: Chen Wei , Liao Yuan , Dai Rui , Dong Yuanlin , Huang Liya
Published: July 2024

EEG-based emotion recognition is becoming crucial in brain-computer interfaces (BCI). Currently, most researches focus on improving accuracy, while neglecting further research on the interpretability of models, we are committed to analyzing the impact of different brain regions and signal frequency bands on emotion generation based on graph structure. Therefore, this paper proposes a method named Dual Attention Mechanism Graph Convolutional Neural Network (DAMGCN). Specifically, we utilize graph convolutional neural networks to model the brain network as a graph to extract representative spatial features. Furthermore, we employ the self-attention mechanism of the Transformer model which allocates more electrode channel weights and signal frequency band weights to important brain regions and frequency bands. The visualization of attention mechanism clearly demonstrates the weight allocation learned by DAMGCN. During the performance evaluation of our model on the DEAP, SEED, and SEED-IV datasets, we achieved the best results on the SEED dataset, showing subject-dependent experiments’ accuracy of 99.42% and subject-independent experiments’ accuracy of 73.21%. The results are demonstrably superior to the accuracies of most existing models in the realm of EEG-based emotion recognition.
Fast multi-compartment Microstructure Fingerprinting in brain white matter
Authors: Dessain Quentin , Fuchs Clément , Macq Benoît , Rensonnet Gaëtan
Published: July 2024

We proposed two deep neural network based methods to accelerate the estimation of microstructural features of crossing fascicles in the white matter. Both methods focus on the acceleration of a multi-dictionary matching problem, which is at the heart of Microstructure Fingerprinting, an extension of Magnetic Resonance Fingerprinting to diffusion MRI. The first acceleration method uses efficient sparse optimization and a dedicated feed-forward neural network to circumvent the inherent combinatorial complexity of the fingerprinting estimation. The second acceleration method relies on a feed-forward neural network that uses a spherical harmonics representation of the DW-MRI signal as input. The first method exhibits a high interpretability while the second method achieves a greater speedup factor. The accuracy of the results and the speedup factors of several orders of magnitude obtained on in vivo brain data suggest the potential of our methods for a fast quantitative estimation of microstructural features in complex white matter configurations.
Association between dietary intake of niacin and stroke in the US residents: evidence from national health and nutrition examination survey (NHANES) 1999–2018
Authors: Qiu Jie-Yu , Zhang Wen-Hui , Zhu Xiao-Ming , Wu Li-Da , Huang Ji-Hua , Zhang Jie
Published: July 2024

Objective

This study aims to explore the association between niacin intake and stroke within a diverse, multi-ethnic population.

Methods

A stringent set of inclusion and exclusion criteria led to the enrollment of 39,721 participants from the National Health and Nutrition Examination Survey (NHANES). Two interviews were conducted to recall dietary intake, and the USDA’s Food and Nutrient Database for Dietary Studies (FNDDS) was utilized to calculate niacin intake based on dietary recall results. Weighted multivariate logistic regression was employed to examine the correlation between niacin and stroke, with a simultaneous exploration of potential nonlinear relationships using restricted cubic spline (RCS) regression.

Results

A comprehensive analysis of baseline data revealed that patients with stroke history had lower niacin intake levels. Both RCS analysis and multivariate logistic regression indicated a negative nonlinear association between niacin intake and stroke. The dose-response relationship exhibited a non-linear pattern within the range of dietary niacin intake. Prior to the inflection point (21.8 mg) in the non-linear correlation between niacin intake and stroke risk, there exists a marked decline in the risk of stroke as niacin intake increases. Following the inflection point, the deceleration in the decreasing trend of stroke risk with increasing niacin intake becomes evident. The inflection points exhibit variations across diverse populations.

Conclusion

This investigation establishes a negative nonlinear association between niacin intake and stroke in the broader American population.
Analyzing the impact of heavy metal exposure on osteoarthritis and rheumatoid arthritis: an approach based on interpretable machine learning
Authors: Fan Wenxuan , Pi Zhipeng , Kong Keyu , Qiao Hua , Jin Minghao , Chang Yongyun , Zhang Jingwei , Li Huiwu
Published: July 2024

Introduction

This investigation leverages advanced machine learning (ML) techniques to dissect the complex relationship between heavy metal exposure and its impacts on osteoarthritis (OA) and rheumatoid arthritis (RA). Utilizing a comprehensive dataset from the National Health and Nutrition Examination Survey (NHANES) spanning from 2003 to 2020, this study aims to elucidate the roles specific heavy metals play in the incidence and differentiation of OA and RA.

Methods

Employing a phased ML strategy that encompasses a range of methodologies, including LASSO regression and SHapley Additive exPlanations (SHAP), our analytical framework integrates demographic, laboratory, and questionnaire data. Thirteen distinct ML models were applied across seven methodologies to enhance the predictability and interpretability of clinical outcomes. Each phase of model development was meticulously designed to progressively refine the algorithm’s performance.

Results

The results reveal significant associations between certain heavy metals and an increased risk of arthritis. The phased ML approach enabled the precise identification of key predictors and their contributions to disease outcomes.

Discussion

These findings offer new insights into potential pathways for early detection, prevention, and management strategies for arthritis associated with environmental exposures. By improving the interpretability of ML models, this research provides a potent tool for clinicians and researchers, facilitating a deeper understanding of the environmental determinants of arthritis.
Swin-GA-RF: genetic algorithm-based Swin Transformer and random forest for enhancing cervical cancer classification
Authors: Alohali Manal Abdullah , El-Rashidy Nora , Alaklabi Saad , Elmannai Hela , Alharbi Saleh , Saleh Hager
Published: July 2024

Cervical cancer is a prevalent and concerning disease affecting women, with increasing incidence and mortality rates. Early detection plays a crucial role in improving outcomes. Recent advancements in computer vision, particularly the Swin transformer, have shown promising performance in image classification tasks, rivaling or surpassing traditional convolutional neural networks (CNNs). The Swin transformer adopts a hierarchical and efficient approach using shifted windows, enabling the capture of both local and global contextual information in images. In this paper, we propose a novel approach called Swin-GA-RF to enhance the classification performance of cervical cells in Pap smear images. Swin-GA-RF combines the strengths of the Swin transformer, genetic algorithm (GA) feature selection, and the replacement of the softmax layer with a random forest classifier. Our methodology involves extracting feature representations from the Swin transformer, utilizing GA to identify the optimal feature set, and employing random forest as the classification model. Additionally, data augmentation techniques are applied to augment the diversity and quantity of the SIPaKMeD1 cervical cancer image dataset. We compare the performance of the Swin-GA-RF Transformer with pre-trained CNN models using two classes and five classes of cervical cancer classification, employing both Adam and SGD optimizers. The experimental results demonstrate that Swin-GA-RF outperforms other Swin transformers and pre-trained CNN models. When utilizing the Adam optimizer, Swin-GA-RF achieves the highest performance in both binary and five-class classification tasks. Specifically, for binary classification, it achieves an accuracy, precision, recall, and F1-score of 99.012, 99.015, 99.012, and 99.011, respectively. In the five-class classification, it achieves an accuracy, precision, recall, and F1-score of 98.808, 98.812, 98.808, and 98.808, respectively. These results underscore the effectiveness of the Swin-GA-RF approach in cervical cancer classification, demonstrating its potential as a valuable tool for early diagnosis and screening programs.
Case Report: Taking action or standing by: managing a preterm neonate at the risk of neonatal varicella by metagenomic next-generation sequencing
Authors: Li Haiting , Chen Xiyang , Li Jie , Chen Linlin , Liu Xixi , Chen Caie , Xie Dengpan , Chen Yunqin , Yuan Junhui , Tao Enfu
Published: July 2024

Neonatal varicella is indeed a rare condition, and most infants born to mothers with varicella have a good prognosis. However, in exceptional cases, neonatal varicella can be life-threatening, particularly for preterm infants. Therefore, it is vital to make an early diagnosis or predict the risk of neonatal varicella to ensure prompt treatment and improve prognosis. This report made an effort to early predict neonatal vericalla by using metagenomic next-generation sequencing (mNGS) in a preterm infant who was at risk for vericalla infection. A preterm infant born from a mother with varicella with symptom onset at 8 days before delivery, putting the infant at risk for varicella infection. Importantly, the patient develop pneumonia and pneumothorax, and neonatal vericella was suspected. Fortunately, the use of mNGS for testing the varicella gene in the serum promptly ruled out varicella zoster virus (VZV) infection in the patient, as indicated by a negative mNGS result. Subsequent follow-up, which included a 14-day stay in the hospital followed by an additional 7 days at home, confirmed this finding. Throughout this period, the patient did not exhibit any rash or other symptoms associated with varicella. Therefore, the novel approach of using mNGS allows neonatologists to predict and promptly address potential neonatal infections. This early detection is crucial, as delayed diagnosis or treatment could pose life-threatening risks, as exemplified by the case of neonatal varicella. In such cases, neonatologists can take proactive measures instead of standing by for at-risk neonates. Furthermore, given the severity of neonatal varicella as a life-threatening condition, the early exclusion of subsequent varicella infection by mNGS can offer reassurance to both family members and healthcare professionals.
The effect of folic acid intake on congenital anomalies. A systematic review and meta-analysis
Authors: Moges Natnael , Sisay Chanie Ermias , Anteneh Rahel Mulatie , Zemene Melkamu Aderajew , Gebeyehu Asaye Alamneh , Belete Melaku Ashagrie , Kebede Natnael , Anley Denekew Tenaw , Dessie Anteneh Mengist , Alemayehu Ermiyas , Dagnaw Fentaw Teshome , Asmare Zufan Alamrie , Tsega Sintayehu Simie
Published: July 2024

Background

Congenital anomalies pose a significant challenge to global health and result in considerable morbidity and mortality in early childhood. With the decline of other causes of death among children under five, the burden of congenital anomalies is rising, emphasizing the need for improved prenatal care, screening, and nutrition for pregnant women. This systematic review and meta-analysis aim to estimate the pooled effect of folic acid intake on congenital anomalies.

Methods

To identify relevant research published up until December 30/2023, we conducted electronic searches of PubMed/Medline, PubMed Central, Hinary, Google, African Journals Online, Web of Science, Science Direct, and Google Scholar databases using predefined eligibility criteria. We used Excel to extract data and evaluated the studies using the JBI appraisal checklist. We computed the pooled effect size with 95% confidence intervals for maternal folic acid intake on congenital anomalies using STATA version 17 and the DerSimonian and Laird random effects meta-analysis model. We assessed statistical heterogeneity using Cochran's Q-test, I2 statistic, and visual examination of the funnel plot.

Results

The review included 16 case-control, cohort, and cross-sectional studies. According to the results of this systematic review and meta-analysis, maternal folic acid intake significantly lowers the incidence of congenital anomalies (odds ratio (OR), 0.23; confidence interval (CI), 0.16, 0.32). Among the included studies, both the Cochrane Q-test statistic (χ2 = 118.82, p < 0.001) and I2 test statistic (I2 = 87.38%, p < 0.001) revealed statistically significant heterogeneity. Egger's weighted regression (p < 0.001) and funnel plot show evidence of publication bias in this meta-analysis.

Conclusion

The results of the recent meta-analysis and systematic review have demonstrated a significant association between maternal folic acid intake and the risk of congenital anomalies. Specifically, children whose mothers received periconceptional folic acid supplementation had a 77% reduced risk of congenital anomalies. To further investigate the correlation between maternal folic acid supplementation and the occurrence of various congenital anomalies, particularly in developing countries, it is recommended that a comprehensive prospective study be conducted.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, PROSPERO (CRD42024511508).
Sequential model for predicting patient adherence in subcutaneous immunotherapy for allergic rhinitis
Authors: Li Yin , Xiong Yu , Fan Wenxin , Wang Kai , Yu Qingqing , Si Liping , van der Smagt Patrick , Tang Jun , Chen Nutan
Published: July 2024

Objective

Subcutaneous Immunotherapy (SCIT) is the long-lasting causal treatment of allergic rhinitis (AR). How to enhance the adherence of patients to maximize the benefit of allergen immunotherapy (AIT) plays a crucial role in the management of AIT. This study aims to leverage novel machine learning models to precisely predict the risk of non-adherence of AR patients and related local symptom scores in 3 years SCIT.

Methods

The research develops and analyzes two models, sequential latent-variable model (SLVM) of Stochastic Latent Actor-Critic (SLAC) and Long Short-Term Memory (LSTM). SLVM is a probabilistic model that captures the dynamics of patient adherence, while LSTM is a type of recurrent neural network designed to handle time-series data by maintaining long-term dependencies. These models were evaluated based on scoring and adherence prediction capabilities.

Results

Excluding the biased samples at the first time step, the predictive adherence accuracy of the SLAC models is from 60% to 72%, and for LSTM models, it is 66%–84%, varying according to the time steps. The range of Root Mean Square Error (RMSE) for SLAC models is between 0.93 and 2.22, while for LSTM models it is between 1.09 and 1.77. Notably, these RMSEs are significantly lower than the random prediction error of 4.55.

Conclusion

We creatively apply sequential models in the long-term management of SCIT with promising accuracy in the prediction of SCIT nonadherence in AR patients. While LSTM outperforms SLAC in adherence prediction, SLAC excels in score prediction for patients undergoing SCIT for AR. The state-action-based SLAC adds flexibility, presenting a novel and effective approach for managing long-term AIT.
Monoterpene antifungal activities: evaluating geraniol, citronellal, and linalool on Candida biofilm, host inflammatory responses, and structure–activity relationships
Authors: Vasconcelos Priscilla Guimarães Silva , Lee Kyu Min , Abuna Gabriel Flores , Costa Edja Maria Melo Brito , Murata Ramiro Mendonça
Published: July 2024

Introduction: Despite the rising concern with fungal resistance, a myriad of molecules has yet to be explored. Geraniol, linalool, and citronellal are monoterpenes with the same molecular formula (C10H18O), however, neither the effect of these compounds on inflammatory axis induced by Candida spp. nor the antibiofilm Structure-Activity Relationship (SAR) have been well-investigated. Herein we analyzed geraniol, linalool and citronellal antifungal activity, cytotoxicity, and distinctive antibiofilm SAR, also the influence of geraniol on Candida spp induced dysregulated inflammatory axis, and in vivo toxicity.

Methods: Minimal inhibitory (MIC) and fungicidal (MFC) concentrations against Candida spp were defined, followed by antibiofilm activity (CFU–colony forming unit/mL/g of dry weight). Cytotoxic activity was assessed using human monocytes (THP-1) and oral squamous cell (TR146). Geraniol was selected for further analysis based on antifungal, antibiofilm and cytotoxic results. Geraniol was tested using a dual-chamber co-culture model with TR146 cells infected with C. albicans, and THP-1 cells, used to mimic oral epithelium upon fungal infection. Expression of Candida enzymes (phospholipase–PLB and aspartyl proteases–SAP) and host inflammatory cytokines (interleukins: IL-1β, IL-6, IL-17, IL-18, IL-10, and Tumor necrosis factor–TNF) were analyzed. Lastly, geraniol in vivo toxicity was assessed using Galleria mellonella.

Results: MIC values obtained were 1.25–5 mM/mL for geraniol, 25-100 mM/mL for linalool, and 100–200 mM/mL for citronellal. Geraniol 5 and 50 mM/mL reduced yeast viability during biofilm analysis, only 500 mM/mL of linalool was effective against a 72 h biofilm and no biofilm activity was seen for citronellal. LD50 for TR146 and THP-1 were, respectively: geraniol 5.883 and 8.027 mM/mL; linalool 1.432 and 1.709 mM/mL; and citronellal 0.3006 and 0.1825 mM/mL. Geraniol was able to downregulate expression of fungal enzymes and host pro-inflammatory cytokines IL-1β, IL-6, and IL-18. Finally, safety in vivo parameters were observed up to 20 mM/Kg.

Discussion: Despite chemical similarities, geraniol presented better antifungal, antibiofilm activity, and lower cytotoxicity when compared to the other monoterpenes. It also showed low in vivo toxicity and capacity to downregulate the expression of fungal enzymes and host pro-inflammatory cytokines. Thus, it can be highlighted as a viable option for oral candidiasis treatment.
Z-ACA allotrope: a topological carbon material with obstructed Wannier charge center, real topology, and hinge states
Authors: Wu Lunsheng , Li Yang
Published: July 2024

As the most prevalent element on our planet, carbon manifests a wide variety of allotropic phases, significantly contributing to its complex physical properties. Recently, several carbon allotropes have been reported to possess abundant topological phases in theory and experiment. This work focuses on a sp3 carbon allotrope, Z-ACA allotrope, which consists of 5-6-7-type Z-ACA carbon rings. This allotrope has been reported previously as a superhard material comparable to diamond. In this study, we report that it is a candidate for both an obstructed atomic insulator and a real Chern insulator. It is worth mentioning that Z-ACA exhibits an unconventional bulk-boundary correspondence due to its hinge boundary state manifestation. Our current research indicates that Z-ACA is a suitable carbon phase platform for studying the real topology and second-order bulk-boundary correspondence.
Adherence to ACSM exercise guidelines and its influence on Fibromyalgia treatment outcomes: a meta-analysis of randomized controlled trials
Authors: Han Tianran , Xi Rui , Wang Jialin , Yan Huiqian , Li Linhua
Published: July 2024

Background

The Fibromyalgia Syndrome (FMS) is a multifaceted chronic pain disorder that exerts a substantial impact on the overall state of health and quality of life of patients.

Purpose

Investigate the effects of exercise therapy and adherence to the American College of Sports Medicine (ACSM) guidelines on treatment outcomes in FMS patients.

Methods

The literature search, which concluded in October 2023, encompassed studies investigating the impact of exercise interventions on patients diagnosed with FMS and providing adequate data for calculating standardized mean difference (SMD). The primary outcome measures encompassed the Fibromyalgia Impact Questionnaire (FIQ) and Health Assessment Questionnaire (HAQ), while secondary outcome measures comprised pain levels, sleep quality, fatigue, and mental health.

Results

Among 4,008 records, 19 studies (patients = 857) were eligible for qualitative synthesis. The meta-analysis revealed that the SMD for overall state of health impact was −0.94 (95%CI −1.26, −0.63), and the pooled SMD for the subgroup with high adherence to ACSM guidelines was −1.17 (95%CI −1.65, −0.69). The SMD for the subgroup with low or uncertain adherence was −0.73 (95%CI −1.12, −0.34). The overall effects included a −1.21 (95%CI −1.62, −0.79) SMD for pain relief, with high adherence achieving a −1.32 (95%CI −2.00, −0.64) SMD and low adherence a −1.06 (95%CI −1.55, −0.57) SMD. Mental health improvements showed a −0.95 (95%CI −1.32, −0.57) overall SMD, with high and low adherence subgroups at −0.96 (95%CI −1.62, −0.30) and −0.94 (95%CI −1.29, −0.60), respectively. Sleep quality impact was −1.59 (95%CI −2.31, −0.87) overall, with high adherence at −1.71 (95%CI −2.58, −0.83) and low adherence at −1.11 (95%CI −1.88, −0.33). Fatigue impact had a −1.55 (95%CI −2.26, −0.85) overall SMD, with −1.77 (95%CI −3.18, −0.36) for high adherence and −1.35 (95%CI −2.03, −0.66) for low adherence.

Conclusion

Exercise therapy can improve the overall state of health, pain, sleep, and fatigue of FMS patients, particularly when adhering to ACSM guidelines. However, adherence levels do not affect mental health gains, indicating a need for future research on psychological impact.

Systematic Review Registration:

https://inplasy.com/inplasy-2024-3-0106/, identifier INPLASY202430106.
Plastid phylogenomics reveals evolutionary relationships in the mycoheterotrophic orchid genus Dipodium and provides insights into plastid gene degeneration
Authors: Goedderz Stephanie , Clements Mark A. , Bent Stephen J. , Nicholls James A. , Patel Vidushi S. , Crayn Darren M. , Schlüter Philipp M. , Nargar Katharina
Published: July 2024

The orchid genus Dipodium R.Br. (Epidendroideae) comprises leafy autotrophic and leafless mycoheterotrophic species, with the latter confined to sect. Dipodium. This study examined plastome degeneration in Dipodium in a phylogenomic and temporal context. Whole plastomes were reconstructed and annotated for 24 Dipodium samples representing 14 species and two putatively new species, encompassing over 80% of species diversity in sect. Dipodium. Phylogenomic analysis based on 68 plastid loci including a broad outgroup sampling across Orchidaceae found that sect. Leopardanthus is the sister lineage to sect. Dipodium. Dipodium ensifolium, the only leafy autotrophic species in sect. Dipodium, was found to be a sister to all leafless, mycoheterotrophic species, supporting a single evolutionary origin of mycoheterotrophy in the genus. Divergence-time estimations found that Dipodium arose ca. 33.3 Ma near the lower boundary of the Oligocene and that crown diversification commenced in the late Miocene, ca. 11.3 Ma. Mycoheterotrophy in the genus was estimated to have evolved in the late Miocene, ca. 7.3 Ma, in sect. Dipodium. The comparative assessment of plastome structure and gene degradation in Dipodium revealed that plastid ndh genes were pseudogenised or physically lost in all Dipodium species, including in leafy autotrophic species of both Dipodium sections. Levels of plastid ndh gene degradation were found to vary among species as well as within species, providing evidence of relaxed selection for retention of the NADH dehydrogenase complex within the genus. Dipodium exhibits an early stage of plastid genome degradation, as all species were found to have retained a full set of functional photosynthesis-related genes and housekeeping genes. This study provides important insights into plastid genome degradation along the transition from autotrophy to mycoheterotrophy in a phylogenomic and temporal context.
Transcription factors involved in plant responses to cadmium-induced oxidative stress
Authors: Zhang Hewan , Lu Lingli
Published: July 2024

Cadmium (Cd) is a heavy metal highly toxic to living organisms. Cd pollution of soils has become a serious problem worldwide, posing a severe threat to crop production and human health. When plants are poisoned by Cd, their growth and development are inhibited, chloroplasts are severely damaged, and respiration and photosynthesis are negatively affected. Therefore, elucidating the molecular mechanisms that underlie Cd tolerance in plants is important. Transcription factors can bind to specific plant cis-acting genes. Transcription factors are frequently reported to be involved in various signaling pathways involved in plant growth and development. Their role in the resistance to environmental stress factors, particularly Cd, should not be underestimated. The roles of several transcription factor families in the regulation of plant resistance to Cd stress have been widely demonstrated. In this review, we summarize the mechanisms of five major transcription factor families–WRKY, ERF, MYB, bHLH, and bZIP–in plant resistance to Cd stress to provide useful information for using molecular techniques to solve Cd pollution problems in the future.
Growth, yield and oil quality of adult pedestrian olive orchards grown at four different planting systems
Authors: Massenti Roberto , Ioppolo Antonino , Carella Alessandro , Imperiale Valeria , Lo Bianco Riccardo , Servili Maurizio , Selvaggini Roberto , Caruso Tiziano
Published: July 2024

This study evaluated growth, yield and olive oil quality of mature pedestrian olive orchards. Trees of three Sicilian cultivars Calatina, Nocellara del Belice and Abunara were planted at four combinations of planting densities and training forms. Trees at 2 × 5 m were trained to central leader (CLx2), those at 3 × 5 m to free palmette (FPx3), those at 4 x 5 to globe vase (GVx4), and those at 5 x 5 to poly-conic vase (PVx5). ‘Calatina’ had the smallest trees in terms of trunk size in all growing systems, while canopy size of trees at higher densities was similar for all three cultivars. ‘Calatina’ was also the most growth efficient (m3 of canopy per cm2 of TCSA) and produced the least amount of pruning wood in the hedgerow systems (CLx2 and FPx3). Fruit yield per tree tended to be higher in more vigorous cultivars (Abunara and Nocellara) grown to 3D systems (GVx4 and PVx5), while ‘Calatina’ was the most yield efficient (kg of fruit per cm2 of TCSA) especially in the hedgerow growing systems. Fruit and oil yield per ha and average production value tended to be highest in CLx2 trees and lowest in GVx4 trees, with ‘Calatina’ showing the sharpest changes and ‘Nocellara’ the smallest changes among growing systems. According to the Jaen index, CLx2 tended to induce earlier fruit maturation, followed by PVx5, GVx4, and FPx3. The growing system did not affect oil fatty acid composition, while ‘Calatina’ had the highest amount of mono-unsaturated fatty acids and the lowest amount of saturated fatty acids. ‘Abunara’ oils exhibited the highest amount of total phenols in CLx2, while ‘Calatina’ and ‘Nocellara’ oils exhibited the highest amount in FPx3 and PVx5. Both, trans-2-hexenal (“cut grass” sensory note) and hexenyl acetate (“floral” sensory note) tended to be lowest in oils from trees grown at CLx2 and highest in those from trees grown at GVx4, showing a somewhat inverse relationship with fruit ripening degree. The outcome of the present study on mature pedestrian orchards shows that proper combinations of cultivars, planting densities, and training forms (canopy shape) may result in efficient intensive systems for growing olive in areas where super-high density systems cannot be profitable due to agronomic and environmental limitations (water shortage, steep sloping sites, small farm size, etc.). Pedestrian growing systems can also be used to exploit olive biodiversity by allowing the use of available local genotypes. For this reason, they may represent an effective and sustainable solution against unexpected climate changes and associated emerging diseases.
Proteomic and metabolomic revealed the effect of shading treatment on cigar tobacco
Authors: Yan Tongjing , Cai Bin , Li Fangyou , Guo Dong , Xia Changjian , Lv Hongkun , Lin Beisen , Gao Huajun , Geng Zhaoliang
Published: July 2024

Shading or low light conditions are essential cultivation techniques for cigar wrapper tobacco leaves production, yet their impact on protein and metabolic regulatory networks is not well understood. In this study, we integrated proteomic and metabolomic analyses to uncover the potential molecular mechanisms affecting cigar tobacco leaves under shading treatment. Our findings include: (1) Identification of 780 significantly differentially expressed proteins (DEPs) in the cigar wrapper tobacco leaves, comprising 560 up-regulated and 220 down-regulated proteins, predominantly located in the chloroplast, cytoplasm, and nucleus, collectively accounting for 50.01%. (2) Discovery of 254 significantly differentially expressed metabolites (DEMs), including 148 up-regulated and 106 down-regulated metabolites. (3) KEGG pathway enrichment analysis revealed that the mevalonate (MVA) pathway within ‘Terpenoid backbone biosynthesis’ was inhibited, leading to a down-regulation of ‘Sesquiterpenoid and triterpenoid biosynthesis’. Conversely, the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway was enhanced, resulting in an up-regulation of ‘Monoterpenoid biosynthesis’, ‘Diterpenoid biosynthesis’, and ‘Carotenoid biosynthesis’, thereby promoting the synthesis of terpenoids such as carotenoids and chlorophylls. Simultaneously, the Calvin cycle in ‘Carbon fixation in photosynthetic organisms’ was amplified, increasing photosynthetic efficiency. These results suggest that under low light conditions, cigar tobacco optimizes photosynthetic efficiency by reconfiguring its energy metabolism and terpenoid biosynthesis. This study contributes valuable insights into protein and metabolic analyses, paving the way for future functional studies on plant responses to low light.