bluuebunny/crossref_metadata_2025_split huggingface dataset:
Material balance principle to estimate eco-efficiency of saffron-producers aiming reduction in greenhouse gas emissions in Iran
Authors: Mardani Najafabadi M. , Rastegaripour F. , Yavari F. , Ahani E. 
Published: June 2023

Introduction: During the last decades, environmental pollution has been considered one of the challenges of the agricultural sector, which has affected the relationship between the ecological and economic performance of agricultural products.Methods: In this study, the DEA-MBP approach based on the SBM model has been used to investigate the eco-efficiency of saffron farms in Iran. The main purpose of this approach is to decrease GHG emissions by mitigating the use of highly polluting production inputs.Results: The results showed that the average eco-efficiency is estimated at 74% and is 12% lower than technical efficiency without considering environmental issues. Therefore, saffron producers are 26% far from full efficiency, and they must change their consumption of inputs and production of inputs according to environmental issues in order to achieve it. Excessive use of diesel fuel and fungicides is cause of GHG emissions in these farms.Discussion: The use of sustainable and ecological cultivation methods in farms in order to reduce the consumption of chemical fertilizers and fungicides should be considered. Replacing old machinery and repairing them can also considerably reduce fuel consumption and GHG emissions.
Bismuth exposure affects morpho-physiological performances and the ionomic profile in garden cress (Lepidium sativum L.) plants
Authors: Pietrini Fabrizio , Passatore Laura , Carloni Serena , Massimi Lorenzo , Astolfi Maria Luisa , Giusto Chiara , Zacchini Massimo 
Published: June 2023

Environmental pollution caused by heavy metals has long been considered a relevant threat to ecosystem survival and human health. The use of safer substitutes for the most toxic heavy metals in many industrial applications is discussed as a potential way to face this issue. In this regard, Bi has been proposed for replacing Pb in several production processes. However, few literature records reported on the effects of Bi on living organisms, particularly on plants. In this study, garden cress (Lepidium sativum L.) plants were exposed to different concentrations of Bi nitrate added to soil in growth chambers for 21 days. Results evidenced the toxic effect of Bi on shoot growth, regardless of the Bi nitrate concentration in the soil, paralleled by a similar reduction in the chlorophyll and carotenoid content, a decrease in the nitrogen balance index values, and an impairment of the photosynthetic machinery evaluated by chlorophyll fluorescence image analysis. The presence of Bi in the soil was shown to affect element accumulation in roots and translocation to shoots, with micronutrient content particularly reduced in the leaves of Bi-treated plants. A dose-dependent plant accumulation of Bi to metal concentration in the soil was observed, even if very low metal bioconcentration ability was highlighted. The reduced Bi translocation from roots to shoots in plants exposed to increasing Bi concentrations in the soil is discussed as a possible defense mechanism likely associated with the observed increase of anthocyan and flavonol contents and the activation of photoprotection mechanisms preventing higher damages to the photosynthetic apparatus.
A novel PKHD1 splicing variant identified in a fetus with autosomal recessive polycystic kidney disease
Authors: Miao Mingzhu , Feng Liqun , Wang Jue , Xu Cheng , Su Xiaotian , Zhang Guoying , Lu Shoulian 
Published: June 2023

Objective: Variants of the polycystic kidney and hepatic disease 1 (PKHD1) gene are associated with autosomal recessive polycystic kidney disease (ARPKD). This study aimed to identify the genetic causes in a Chinese pedigree with ARPKD and design a minigene construct of the PKHD1 gene to investigate the impact of its variants on splicing.Methods: Umbilical cord samples from the proband and peripheral blood samples from his parents were collected, and genomic DNA was extracted for whole-exome sequencing (WES). Bioinformatic analysis was used to identify potential genetic causes, and Sanger sequencing confirmed the existence of variants within the pedigree. A minigene assay was performed to validate the effects of an intronic variant on mRNA splicing.Results: Two variants, c.9455del (p.N3152Tfs*10) and c.2408-13C&gt;G, were identified in the PKHD1 gene (NM_138694.4) by WES; the latter has not been previously reported. In silico analysis predicted that this intronic variant is potentially pathogenic. Bioinformatic splice prediction tools revealed that the variant is likely to strongly impact splice site function. An in vitro minigene assay revealed that c.2408-13C&gt;G can cause aberrant splicing, resulting in the retention of 12 bp of intron 23.Conclusion: A novel pathogenic variant of PKHD1, c.2408-13C&gt;G, was found in a fetus with ARPKD, which enriches the variant spectrum of the PKHD1 gene and provides a basis for genetic counseling and the diagnosis of ARPKD. Minigenes are optimal to determine whether intron variants can cause aberrant splicing.
Identification and prediction of immune checkpoint inhibitors-related pneumonitis by machine learning
Authors: Gong Li , Gong Jun , Sun Xin , Yu Lin , Liao Bin , Chen Xia , Li Yong-sheng 
Published: June 2023

BackgroundImmune checkpoint inhibitor (ICI)-related pneumonitis (IRP) is a common and potentially fatal clinical adverse event. The identification and prediction of the risk of ICI-related IRP is a major clinical issue. The objective of this study was to apply a machine learning method to explore risk factors and establish a prediction model.MethodsWe retrospectively analyzed 48 patients with IRP (IRP group) and 142 patients without IRP (control group) who were treated with ICIs. An Elastic Net model was constructed using a repeated k-fold cross-validation framework (repeat = 10; k = 3). The prediction models were validated internally and the final prediction model was built on the entire training set using hyperparameters with the best interval validation performance. The generalizability of the final prediction model was assessed by applying it to an independent test set. The overall performance, discrimination, and calibration of the prediction model were evaluated.ResultsEleven predictors were included in the final predictive model: sindillizumab, number of ≥2 underlying diseases, history of lung diseases, tirelizumab, non-small cell lung cancer (NSCLC), percentage of CD4+ lymphocytes, body temperature, KPS score ≤70, hemoglobin, cancer stage IV, and history of antitumor therapy. The external validation of the risk prediction model on an independent test set of 37 patients and showed good discrimination and acceptable calibration ability: with AUC of 0.81 (95% CI 0.58–0.90), AP of 0.76, scaled Brier score of 0.31, and Spiegelhalter-z of −0.29 (P-value:0.77). We also designed an online IRP risk calculator for use in clinical practice.ConclusionThe prediction model of ICI-related IRP provides a tool for accurately predicting the occurrence of IRP in patients with cancer who received ICIs.
Airway macrophages display decreased expression of receptors mediating and regulating scavenging in early cystic fibrosis lung disease
Authors: Slimmen Lisa J. M. , Giacalone Vincent D. , Schofield Craig , Horati Hamed , Manaï Badies H. A. N. , Estevão Silvia C. , Garratt Luke W. , Peng Limin , Tirouvanziam Rabindra , Janssens Hettie M. , Unger Wendy W. J. 
Published: June 2023

BackgroundCystic fibrosis (CF) airway disease is characterized by chronic inflammation, featuring neutrophil influx to the lumen. Airway macrophages (AMs) can promote both inflammation and resolution, and are thus critical to maintaining and restoring homeostasis. CF AM functions, specifically scavenging activity and resolution of inflammation, have been shown to be impaired, yet underlying processes remain unknown. We hypothesized that impaired CF AM function results from an altered expression of receptors that mediate or regulate scavenging, and set out to investigate changes in expression of these markers during the early stages of CF lung disease.MethodsBronchoalveolar lavage fluid (BALF) was collected from 50 children with CF aged 1, 3 or 5 years. BALF cells were analyzed using flow cytometry. Expression levels of surface markers on AMs were expressed as median fluorescence intensities (MFI) or percentage of AMs positive for these markers. The effect of age and neutrophilic inflammation, among other variables, on marker expression was assessed with a multivariate linear regression model.ResultsAM expression of scavenger receptor CD163 decreased with age (p = 0.016) and was negatively correlated with BALF %neutrophils (r = -0.34, p = 0.016). AM expression of immune checkpoint molecule SIRPα also decreased with age (p = 0.0006), but did not correlate with BALF %neutrophils. Percentage of AMs expressing lipid scavenger CD36 was low overall (mean 20.1% ± 16.5) and did not correlate with other factors. Conversely, expression of immune checkpoint PD-1 was observed on the majority of AMs (mean PD-1pos 72.9% ± 11.8), but it, too, was not affected by age or BALF %neutrophils. Compared to matched blood monocytes, AMs had a higher expression of CD16, CD91, and PD-1, and a lower expression of CD163, SIRPα and CD36.ConclusionIn BALF of preschool children with CF, higher age and/or increased neutrophilic inflammation coincided with decreased expression of scavenger receptors on AMs. Expression of scavenging receptors and regulators showed a distinctly different pattern in AMs compared to blood monocytes. These findings suggest AM capacity to counter inflammation and promote homeostasis reduces during initiation of CF airway disease and highlight new avenues of investigation into impaired CF AM function.
Missing link between tissue specific expressing pattern of ERβ and the clinical manifestations in LGBLEL
Authors: Zhang Xujuan , Zhao Pengxiang , Ma Mingshen , Wu Hao , Liu Rui , Liu Ziyi , Cai Zisong , Liu Mengyu , Xie Fei , Ma Xuemei 
Published: June 2023

PurposeLacrimal gland benign lymphoepithelial lesion (LGBLEL) is an IgG4-related disease of unknown etiology with a risk for malignant transformation. Estrogen is considered to be related to LGBLEL onset.MethodsSeventy-eight LGBLEL and 13 control clinical samples were collected and studied to determine the relationship between estrogen and its receptors and LGBLEL development.ResultsThe serological analysis revealed no significant differences in the levels of three estrogens be-tween the LGBLEL and control groups. However, immunohistochemical analyses indicated that the expression levels of ERβ and its downstream receptor RERG were relatively lower in LGBLEL samples than in control samples, with higher expression in the lacrimal gland and lower expression in the lymphocyte infiltration region. However, low expression of ERα was detected. The transcriptome sequence analysis revealed upregulated genes associated with LGBLEL enriched in lymphocyte proliferation and activation function; downregulated genes were enriched in epithelial and vascular proliferation functions. The key genes and gene networks were further analyzed. Interactions between B cells and epithelial cells were analyzed due to the identified involvement of leukocyte subsets and epithelial cells. B cell proliferation was found to potentially contribute to lacrimal gland apoptosis.ConclusionTherefore, the tissue-heterogeneous expression pattern of ERβ is potentially related to the clinical manifestations and progression of LGBLEL, although further investigations are required to confirm this finding.
BALF metagenomic next-generation sequencing analysis in hematological malignancy patients with suspected pulmonary infection: clinical significance of negative results
Authors: Deng Zuqun , Tang Yishu , Tu Yixuan , Liu Mei , Cheng Qian , Zhang Jian , Liu Feiyang , Li Xin 
Published: June 2023

PurposeMetagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) is gradually being used in hematological malignancy (HM) patients with suspected pulmonary infections. However, negative results are common and the clinical value and interpretation of such results in this patient population require further analysis.MethodsRetrospective analysis of 112 HM patients with suspected pulmonary infection who underwent BALF mNGS and conventional microbiological tests. The final diagnosis, imaging findings, laboratory results and treatment regimen of 29 mNGS-negative patients were mainly analyzed.ResultsA total of 83 mNGS positive and 29 negative patients (15 true-negatives and 14 false-negatives) were included in the study. Compared to false-negative patients, true-negative patients showed more thickening of interlobular septa on imaging (p &lt; 0.05); fewer true-negative patients had acute respiratory symptoms such as coughing or sputum production (p &lt; 0.05) clinically; On the aspect of etiology, drug-related interstitial pneumonia (6/15, 40%) was the most common type of lung lesion in true-negative patients; on the aspect of pathogenesis, false-negative patients mainly missed atypical pathogens such as fungi and tuberculosis (8/14, 57.1%). Regarding treatment, delayed anti-infection treatment occurred after pathogen missing in mNGS false-negative patients, with the longest median time delay observed for anti-tuberculosis therapy (13 days), followed by antifungal therapy (7 days), and antibacterial therapy (1.5 days); the delay in anti-tuberculosis therapy was significantly longer than that in antibacterial therapy (p &lt; 0.05).ConclusionFor HMs patients with imaging showing thickening of interlobular septa and no obvious acute respiratory symptoms, lung lesions are more likely caused by drug treatment or the underlying disease, so caution should be exercised when performing BALF mNGS. If BALF mNGS is negative but infection is still suspected, atypical pathogenic infections should be considered.
Genomic insights into Aspergillus sydowii 29R-4-F02: unraveling adaptive mechanisms in subseafloor coal-bearing sediment environments
Authors: Jiang Jun-Peng , Liu Xuan , Liao Yi-Fan , Shan Jun , Zhu Yu-Ping , Liu Chang-Hong 
Published: June 2023

IntroductionAspergillussydowii is an important filamentous fungus that inhabits diverse environments. However, investigations on the biology and genetics of A. sydowii in subseafloor sediments remain limited.MethodsHere, we performed de novo sequencing and assembly of the A. sydowii 29R-4-F02 genome, an isolate obtained from approximately 2.4 km deep, 20-million-year-old coal-bearing sediments beneath the seafloor by employing the Nanopore sequencing platform.Results and DiscussionThe generated genome was 37.19 Mb with GC content of 50.05%. The final assembly consisted of 11 contigs with N50 of 4.6 Mb, encoding 12,488 putative genes. Notably, the subseafloor strain 29R-4-F02 showed a higher number of carbohydrate-active enzymes (CAZymes) and distinct genes related to vesicular fusion and autophagy compared to the terrestrial strain CBS593.65. Furthermore, 257 positively selected genes, including those involved in DNA repair and CAZymes were identified in subseafloor strain 29R-4-F02. These findings suggest that A. sydowii possesses a unique genetic repertoire enabling its survival in the extreme subseafloor environments over tens of millions of years.
A novel framework of MOPSO-GDM in recognition of Alzheimer's EEG-based functional network
Authors: Wang Ruofan , Wang Haodong , Shi Lianshuan , Han Chunxiao , He Qiguang , Che Yanqiu , Luo Li 
Published: June 2023

BackgroundMost patients with Alzheimer's disease (AD) have an insidious onset and frequently atypical clinical symptoms, which are considered a normal consequence of aging, making it difficult to diagnose AD medically. But then again, accurate diagnosis is critical to prevent degeneration and provide early treatment for AD patients.ObjectiveThis study aims to establish a novel EEG-based classification framework with deep learning methods for AD recognition.MethodsFirst, considering the network interactions in different frequency bands (δ, θ, α, β, and γ), multiplex networks are reconstructed by the phase synchronization index (PSI) method, and fourteen topology features are extracted subsequently, forming a high-dimensional feature vector. However, in feature combination, not all features can provide effective information for recognition. Moreover, combining features by manual selection is time-consuming and laborious. Thus, a feature selection optimization algorithm called MOPSO-GDM was proposed by combining multi-objective particle swarm optimization (MOPSO) algorithm with Gaussian differential mutation (GDM) algorithm. In addition to considering the classification error rates of support vector machine, naive bayes, and discriminant analysis classifiers, our algorithm also considers distance measure as an optimization objective.ResultsFinally, this method proposed achieves an excellent classification error rate of 0.0531 (5.31%) with the feature vector size of 8, by a ten-fold cross-validation strategy.ConclusionThese findings show that our framework can adaptively combine the best brain network features to explore network synchronization, functional interactions, and characterize brain functional abnormalities, which can improve the recognition efficiency of diseases. While improving the classification accuracy of application algorithms, we aim to expand our understanding of the brain function of patients with neurological disorders through the analysis of brain networks.
Regional contributions of D-serine to Alzheimer’s disease pathology in male AppNL–G–F/NL–G–F mice
Authors: Ni Xiance , Inoue Ran , Wu Yi , Yoshida Tomoyuki , Yaku Keisuke , Nakagawa Takashi , Saito Takashi , Saido Takaomi C. , Takao Keizo , Mori Hisashi 
Published: June 2023

BackgroundNeurodegenerative processes in Alzheimer’s disease (AD) are associated with excitotoxicity mediated by the N-methyl-D-aspartate receptor (NMDAR). D-Serine is an endogenous co-agonist necessary for NMDAR-mediated excitotoxicity. In the mammalian brain, it is produced by serine racemase (SRR) from L-serine, suggesting that dysregulation of L-serine, D-serine, or SRR may contribute to AD pathogenesis.Objective and methodsWe examined the contributions of D-serine to AD pathology in the AppNL–G–F/NL–G–F gene knock-in (APPKI) mouse model of AD. We first examined brain SRR expression levels and neuropathology in APPKI mice and then assessed the effects of long-term D-serine supplementation in drinking water on neurodegeneration. To further confirm the involvement of endogenous D-serine in AD progression, we generated Srr gene-deleted APPKI (APPKI-SRRKO) mice. Finally, to examine the levels of brain amino acids, we conducted liquid chromatography–tandem mass spectrometry.ResultsExpression of SRR was markedly reduced in the retrosplenial cortex (RSC) of APPKI mice at 12 months of age compared with age-matched wild-type mice. Neuronal density was decreased in the hippocampal CA1 region but not altered significantly in the RSC. D-Serine supplementation exacerbated neuronal loss in the hippocampal CA1 of APPKI mice, while APPKI-SRRKO mice exhibited attenuated astrogliosis and reduced neuronal death in the hippocampal CA1 compared with APPKI mice. Furthermore, APPKI mice demonstrated marked abnormalities in the cortical amino acid levels that were partially reversed in APPKI-SRRKO mice.ConclusionThese findings suggest that D-serine participates in the regional neurodegenerative process in the hippocampal CA1 during the amyloid pathology of AD and that reducing brain D-serine can partially attenuate neuronal loss and reactive astrogliosis. Therefore, regulating SRR could be an effective strategy to mitigate NMDAR-dependent neurodegeneration during AD progression.
Altered brain functional connectivity in vegetative state and minimally conscious state
Authors: Yang Yi , Dai Yangyang , He Qiheng , Wang Shan , Chen Xueling , Geng Xiaoli , He Jianghong , Duan Feng 
Published: June 2023

ObjectivesThe pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there is a high rate of misdiagnosis for subtypes of DoC. We aimed to explore whether topological characterization may explain the pathological mechanisms of DoC and be effective in diagnosing the subtypes of DoC.MethodsUsing resting-state functional magnetic resonance imaging data, the weighted brain functional networks for normal control subjects and patients with vegetative state (VS) and minimally conscious state (MCS) were constructed. Global and local network characteristics of each group were analyzed. A support vector machine was employed to identify MCS and VS patients.ResultsThe average connection strength was reduced in DoC patients and roughly equivalent in MCS and VS groups. Global efficiency, local efficiency, and clustering coefficients were reduced, and characteristic path length was increased in DoC patients (p &lt; 0.05). For patients of both groups, global network measures were not significantly different (p &gt; 0.05). Nodal efficiency, nodal local efficiency, and nodal clustering coefficient were reduced in frontoparietal brain areas, limbic structures, and occipital and temporal brain areas (p &lt; 0.05). The comparison of nodal centrality suggested that DoC causes reorganization of the network structure on a large scale, especially the thalamus. Lobal network measures emphasized that the differences between the two groups of patients mainly involved frontoparietal brain areas. The accuracy, sensitivity, and specificity of the classifier for identifying MCS and VS patients were 89.83, 78.95, and 95%, respectively.ConclusionThere is an association between altered network structures and clinical symptoms of DoC. With the help of network metrics, it is feasible to differentiate MCS and VS patients.
Association between intraoperative steroid and postoperative mortality in patients undergoing craniotomy for brain tumor
Authors: He Jialing , He Shuanghong , Zhang Yu , Tian Yixin , Hao Pengfei , Li Tiangui , Xiao Yangchun , Peng Liyuan , Feng Yuning , Cheng Xin , Deng Haidong , Wang Peng , Chong Weelic , Hai Yang , Chen Lvlin , You Chao , Jia Lu , Chen Dengkui , Fang Fang 
Published: June 2023

BackgroundDespite the widespread use of intraoperative steroids in various neurological surgeries to reduce cerebral edema and other adverse symptoms, there is sparse evidence in the literature for the optimal and safe usage of intraoperative steroid administration in patients undergoing craniotomy for brain tumors. We aimed to investigate the effects of intraoperative steroid administration on postoperative 30-day mortality in patients undergoing craniotomy for brain tumors.MethodsAdult patients who underwent craniotomy for brain tumors between January 2011 to January 2020 were included at West China Hospital, Sichuan University in this retrospective cohort study. Stratified analysis based on the type of brain tumor was conducted to explore the potential interaction.ResultsThis study included 8,663 patients undergoing craniotomy for brain tumors. In patients with benign brain tumors, intraoperative administration of steroids was associated with a higher risk of postoperative 30-day mortality (adjusted OR 1.98, 95% CI 1.09–3.57). However, in patients with malignant brain tumors, no significant association was found between intraoperative steroid administration and postoperative 30-day mortality (adjusted OR 0.86, 95% CI 0.55–1.35). Additionally, administration of intraoperative steroids was not associated with acute kidney injury (adjusted OR 1.11, 95% CI 0.71–1.73), pneumonia (adjusted OR 0.89, 95% CI 0.74–1.07), surgical site infection (adjusted OR 0.78, 95% CI 0.50–1.22) within 30 days, and stress hyperglycemia (adjusted OR 1.05, 95% CI 0.81–1.38) within 24 h after craniotomy for brain tumor.ConclusionIn patients undergoing craniotomy for benign brain tumors, intraoperative steroids were associated with 30-day mortality, but this association was not significant in patients with malignant brain tumors.