bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-wide association study identifies GhSAL1 conferring cold tolerance at the seeding stage in upland cotton (Gossypium hirsutum L.)
Authors: Shen Qian , Zhang Siping , Ge Changwei , Liu Shaodong , Chen Jing , Liu Ruihua , Ma Huijuan , Yang Guozheng , Song Meizhen , Pang Chaoyou 
Published: August 2022

Abstract
Gossypium hirsutum L. is a globally cultivated cotton species. The genetic mechanisms underlying cold resistance in cotton remain unclear. We analyzed the growth and physiological parameters in 200 unrelated accessions under constant chilling (CC) and diurnal variation of chilling (DVC) conditions at seeding stage. All accessions were clustered into four subgroups based on population structure analyses. Group IV, which contained most species from the northwest inland region (NW), had better phenotypes than the other three subgroups under the two chilling stresses. We concluded that the cold adaptability of cotton was associated with its subpopulation and geographical distribution. A total of 577 significant single nucleotide polymorphisms (SNPs) were associated and 35 quantitative trait nucleotides (QTNs) were detected across multiple environments and traits. Gh_D09G0189 (GhSAL1) was obtained in the stable 6.17–6.15 Mb regions on chromosome D09, which were involved in the photomorphogenesis of seedlings under CC stress. GhSAL1HapB was the elite haplotype, which could increase seedling emergence, dry matter weight, and total length by 19.04%, 11.26%, and 7.69%, respectively, compared to that of GhSAL1HapA. The expression abundance of GhSAL1 in cold-tolerant plants was lower. The survival rate of GhSAL1 silenced lines was significantly higher than that of the negative control by 46.33% after CC treatment. It was speculated that GhSAL1 regulated cold tolerance through the GhSAL1-IP3 signaling pathway. The elite genotypes and candidate genes identified in this study can be used to improve low-temperature resistance at the seeding stage in future cotton breeding.
Boosting Algorithm for Optimizing Morphological Dental Age Estimation Method: A Southern China Population Study
Authors: Shan Weijie , Sun Yunshu , Hu Leyan , Qiu Jie , Huo Miao , Zhang Zikang , Lei Yuting , Chen Qianling , Zhang Yan , Yue Xia 
Published: August 2022

Abstract
Age estimation based on the mineralized morphology of teeth is one of the important elements of forensic anthropology. To explore the most suitable age assessment protocol for adolescents in the South China population, 1477 panoramic radiographs images of people aged 2–18 years in the South were collected and staged by the Demirjian mineralization staging method. The dental age were estimated using the parameters of the Demirjian and Willems. Mathematical optimization and machine learning optimization were also performed in the data processing process in an attempt to obtain a more accurate model. The results show that Willems' method is more accurate in estimating the dental age of the South China population, while the model can be further optimized by re-assigning the model through a non-intercept regression method. The machine learning model presented excellent results in terms of the efficacy comparison results with the traditional mathematical model, and the machine learning model under the Boosting framework such as Gradient Boosting Decision Tree (GBDT) significantly reduced the error in dental age estimation compared to the traditional mathematical method. This machine learning processing method based on traditional assessment data can effectively reduce the error of assessment while saving arithmetic power. This study demonstrates the effectiveness of the GBDT algorithm in optimizing forensic age estimation models and provides a reference for other regions to use this scheme for age assessment model architecture, also the lightweight nature of machine learning offers the possibility of widespread forensic anthropological age estimation.
Chronic heart failure health-related quality of life questionnaire (CHFQOLQ-20): Development and psychometric properties
Authors: Khajavi Abdoljavad , Moshki Mahdi , Minaee Shima , Vakilian Farveh , Montazeri Ali , Hashemizadeh Haydeh 
Published: August 2022

Abstract
Background
Health-related quality of life (HRQoL) is an important outcome indicator for chronic diseases. This study aimed to develop a new instrument for assessment of HRQoL in chronic heart failure (CHF) and evaluate its psychometric properties.
Methods
This study included two steps of conceptualization and item generation, and assessment of the psychometric properties of an instrument for measuring HRQoL in patients with CHF. Content validity, exploratory and confirmatory factor analyses, concurrent validity, convergent validity, known groups comparison were performed to assess construct validity. Internal consistency, and stability were estimated by the Cronbach’s alpha and intraclass correlation coefficients.
Results
The content validity of the developed chronic heart failure quality of life questionnaire (CHFQOLQ-20) was assessed by 10 experts. The exploratory and confirmatory factor analyses yielded and confirmed four factors with 20 items. The concurrent and convergent validity of the CHFQOLQ-20 were established using the Short Form Health Survey (SF-36), and the MacNew Heart Disease Quality of Life Questionnaire, respectively. The known-groups validity as assessed by using the New York Heart Association (NYHA) functional classification., showed that the questionnaire discriminated well between patients who differed in functional classification. The internal consistency and test-retest reliability of the CHFQOLQ-20 were satisfactory, with a Cronbach’s alpha and intraclass correlation coefficient (ICC) values of 0.93 and 0.84, respectively.
Conclusion
The results confirmed that CHFQOLQ-20 is a valid and reliable measure of quality of life (QoL) in patients with CHF. It is a short and easy-to-use instrument that is also capable of assessing the cognitive function, which has been overlooked in previous questionnaires.
NLRP3 deficiency decreases alcohol intake controlling anxiety-like behavior via modification of glutamatergic transmission in mPFC-striatal circuits
Authors: Li Ziyi , Vidjro Olivia Ewi , Guo Gengni , Du Yanfeng , Zhou Yao , Xie Qian , Li Jiaxin , Gao Keqiang , Zhou Li , Ma Tengfei 
Published: August 2022

Abstract
Background
Repeated binge alcohol drinking and chronic alcohol consumption with negative effects such as anxiety on cessation induces alcohol use disorders. This process is associated with activation of NLRP3 inflammasome-mediated responses. However, whether and how inhibition of NLRP3 inflammasome alters alcohol intake and anxiety behavior remains unclear.
Methods
A combination of drinking-in-the dark and Gavage model were established in NLRP3-knockout and their control mice. Behaviors were assessed by open-field and elevated plus maze tests. Binge alcohol drinking at 2h and 4h were measured and 24 voluntary drinking was determined by a two-bottle choice paradigm. Western blot and ELISA were applied to examine the levels of NLRP3 inflammasome and inflammatory factors such as IL-1β and TNF-α. Nissl’s staining was measured the neuronal injury. Electrophysiological method was determined the glutamatergic transmission in mPFC to striatum circuits. In vivo opotogenetic LTP and LTD were applied to control the function of mPFC-striatal circuits on behavior of mice. MCC950 was used to antagonize NLRP3 inflammasome.
Results
The binge alcohol intake was decreased in NLRP3 KO mice compared to their control drinking mice. During alcohol withdrawal, NLRP3 deficiency attenuated anxiety-like behaviors and neuronal injury in mPFC and striatum. Moreover, we discovered that the glutamatergic transmission from cortex to striatum was reduced in NLRP3 KO mice. Importantly, in vivo optogenetic induction of long-term potentiation (LTP) of mPFC-striatal circuits reversed the effects of NLRP3 deficiency on glutamatergic transmission and anxiety behaviors. We also demonstrated that optogenetic induction of LTD decreased anxiety-like behaviors with a reduction of glutamatergic transmission. Interestingly, NLRP3 deficiency or inhibition (MCC950 injection)-mediated the attenuation of anxiety behavior reduced binge alcohol intake, but did not decrease 24h-voluntary alcohol consumption and alcohol preference.
Conclusion
Our results demonstrate that NLRP3 deficiency decreases binge alcohol intake and anxiety-like behaviors through downregulation of glutamatergic transmission in mPFC-striatal circuits, which may provide an anti-inflammatory target to treat alcohol use disorders.
Effects of miR-629-5p on odontoblast differentiation and target gene TEAD4 expression of dental pulp stem cells
Authors: Han Jianpeng , Zhao Xin , Jiang Rongrong , Jiang Chengfeng , li lei , xu zhiliang , song yihua , feng xingmei 
Published: August 2022

Abstract
TEAD4 is a member of the TEA domain (TEAD) family of transcription factors. It plays a key regulatory role in embryonic development, tissue homeostasis and cancer progression. Its expression is related to the regulation of a variety of inflammations. MicroRNA can regulate the expression of target genes and play an important role in various physiological and pathological processes. In view of the important role of TEAD4 and microRNA-629-5p (miR-629-5p) in inflammation, and based on the findings of bioinformatics research, we selected miR-629-5p as the focus of our study. In inflammatory dental pulp, we found that the expression of miR-629-5p was increased, while the expression of TEAD4 was decreased. We used Porphyromonas gingivalis lipopolysaccharide (LPS) as a stimulator of dental pulp stem cells (DPSCs) to simulate the inflammatory environment of dental pulp. The mineralization ability of LPS-stimulated DPSCs was significantly inhibited, while the level of miR-629-5p increased and the level of TEAD4 decreased. Inhibition of miR-629-5p can reverse the odontogenic defects of DPSCs treated with LPS. In addition, the expression of miR-629-5p in DPSCs was negatively correlated with the expression of TEAD4. In conclusion, miR-629-5p can inhibit the odontogenic differentiation of human dental pulp stem cells and the mechanism may be related to its role in downregulation of TEAD4 expression.
Incremental Prognostic Value of Triglyceride Glucose Index Additional to Coronary Artery Calcium Score in Asymptomatic Low-Risk Population
Authors: Song Shinjeong , Choi Su‑Yeon , Park Hyo Eun , Han Hae‑Won , Park Sung Hak , Sung Jidong , Jung Hae Ok , Sung Ji Min , Chang Hyuk‑Jae 
Published: August 2022

Abstract
Background
The triglyceride glucose (TyG) index has been suggested as a reliable surrogate marker of insulin resistance which is a substantial risk factor for atherosclerotic cardiovascular disease (ASCVD). Several recent studies have shown the relationship between the TyG index and cardiovascular disease; however, the role of the TyG index in coronary artery calcification (CAC) progression has not been extensively assessed especially in low-risk population.
Methods
We enrolled 5,775 Korean adults who had at least two CAC evaluations. We determined the TyG index using ln (fasting triglycerides [mg/dL] x fasting glucose [mg/dL]/2). The CAC progression was defined as either incident CAC in a CAC-free population at baseline or an increase of ≥ 2.5 units between the square roots of the baseline and follow-up coronary artery calcium scores (CACSs) of subjects with detectable CAC at baseline.
Results
CAC progression was seen in 1,382 subjects (23.9%) during mean 3.5 years follow-up. Based on the TyG index, subjects were stratified into four groups. Follow-up CACS and incidence of CAC progression were markedly elevated with rising TyG index quartiles. (group I [lowest]:17.6% vs. group II:22.2% vs. group III:24.6% vs. group IV [highest]: 31.3%, p < 0.001). In multivariate logistic regression analysis, the TyG index was independent predictor of CAC progression (odds ratio: 1.57; 95% confidence interval: 1.33 to 1.81; p < 0.001) especially in baseline CACS ≤ 100 group.
Conclusions
The TyG index is an independent predictor of CAC progression in low-risk population. It adds incremental risk stratification over established factors including baseline CACS.
Comprehensive characterization of genetic influences on plasma metabolome in a pediatric cohort
Authors: Lee In-Hee , Smith Matthew Ryan , Yazdani Azam , Walker Douglas I. , Mandl Kenneth D. , Jones Dean P. , Kong Sek Won 
Published: August 2022

Abstract
BackgroundThe human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-phenotype associations. However, these associations have not been characterized in children. Results We conducted the largest genome by metabolome-wide association study to date of children (N=441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (>0.8) for 15.9% of features and low h2 (<0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait loci (mQTL) analysis was performed to identify genetic variants associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5x10-12 (= 5 x 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found novel associations including CSMD1 and a monostearyl alcohol triglyceride; CALN1 and a triglyceride; RBFOX1 and dimethylarginine. A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for ADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. Conclusion Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.
18F-fluorocholine PET/CT semi-quantitative analysis in patients affected by primary hyperparathyroidism: a comparison between laboratory and functional data.
Authors: Rizzo Alessio , Racca Manuela , Cauda Simona , Balma Michele , dall'Armellina Sara , Dionisi Beatrice , Mossetti Claudio , Bruna Maria Cristina , Freddi Milena , Palestini Nicola 
Published: August 2022

Abstract
Introduction: this retrospective study aims to establish 18F-fluorocholine (FCH) positron emission tomography / computed tomography (PET/CT) performance in finding hyperfunctioning parathyroid glands, analyse a potential role for semi-quantitative PET parameters and assess factors that may influence PET/CT outcome.Methods: forty patients with suspect primary hyperparathyroidism (pHPT) and negative/equivocal conventional imaging underwent FCH-PET/CT in our Institution.For every lesion, visual and semi-quantitative analyses were performed on PET/CT images. In qualitative analysis, a lesion was considered positive if a clear focus of uptake, significantly higher than normal thyroid tissue, was identifiable. Ectopic focal uptake was also regarded as positive PET result. Lesion SUVMax was measured by assigning a spheric VOI to the suspect area of uptake. Thyroid SUVMean was assessed by placing a spheric VOI inside the contralateral thyroid lobe, and SUVratio was calculated using this background region.All patients were subsequently submitted to surgery and histopathologic workup.Sensitivity, positive predictive value (PPV) and accuracy were calculated based on histopathologic reports for every lesion.Pearson’s test was used to assess a correlation between laboratory and histopathologic features with SUVr.Results: four out of the 40 patients who underwent surgery for pHPT had more than one histologic proven unhealthy parathyroid and three had papillary thyroid cancer (PTC). A total of 48 lesions were analysed.We found 42/48 lesions (87.5%) to have true-positive uptake, whereas three lesions (6.7%) had false-positive uptake (PTC). Three histologic proven parathyroid adenomas showed no uptake (6.7%); the sensitivity/PPV were 93.3% and accuracy was 87,8%.Pearson’s test showed a significant correlation between PTH values and parathyroid size with SUVr values (r=0.56 and 0.55 respectively, p<0.01 for both features).Discussion: as stated in recent literature, we observed excellent diagnostic sensitivity of FCH-PET/CT in patients with pHPT, providing surgeons a fine tool to optimize treatment.More studies are needed to improve the evaluability of semi-quantitative parameters towards a further improvement of diagnostic accuracy.
A Neuromechanical Control Model For Rhythmic and Discrete Movements Based on Central Pattern Generator (CPG)
Authors: Nia Nafiseh Ghaffar , Bahrami Fariba , Kaplanoglu Erkan , Nasab Ahad 
Published: August 2022

Abstract

Undoubtedly, movement is one of the essential characteristics of living beings. Despite the diversity of animal species and the apparent differences, standard features exist between their movement systems that follow a particular pattern. The movements are mainly divided into rhythmic and discrete categories controlled by the central nervous system. Scientists usually consider these two types of motion separately in the control system and use different methods and resources to produce and model them. Proposing a unified and comprehensive model for generating and controlling rhythmic and discrete movement with the same techniques is more valuable albeit challenging. The present study provides a single neuromechanical control model for producing and managing both rhythmic and discrete movements. This model consists of a neural oscillator, the central pattern generator (CPG), coupled with inhibitory and excitatory paths to drive the flexor and extensor muscles. The computational model of this study follows the Hodgkin-Huxley (HH) equations. In the nervous system, the effects of basal ganglia and cerebellum, having a critical role in motion, were also applied in this model. The structure of the model, the factors involved in creating the motion, and the oscillation were analyzed in great detail. It was found that supraspinal input and motor neuron feedback, as the motor control parameters, play an essential role in the activity and directly impact the production and control of rhythmic and discrete movements. According to these parameters, a neuromechanical model that can create both rhythmic and discrete movement is presented. The model also addresses the switching mechanism between rhythmic and discrete states.
Visualized radio-clinical biomarker for predicting neoadjuvant chemotherapy response and prognosis from pretreatment oversampled CT images of LAGC patients: A multicenter study
Authors: Xu Zhiyuan , Chen Wujie , Li Feng , Zhang Yanqiang , Yu Pengfei , Yang Litao , Huang Ling , Sun Jiancheng , Chen Shangqi , Shi Chengwei , Sun Yuanshui , Ye Zaisheng , Yuan Li , Chen Jiahui , Wei Qin , Xu Jingli , Xu Handong , Tong Yahan , Bao Zhehan , Huang Chencui , Li Yiming , Du Yian , Hu Can , Cheng Xiangdong 
Published: August 2022

Abstract
Background: The early noninvasive screening of patients suitable for neoadjuvant chemotherapy (NCT) is essential for personalized treatment in locally advanced gastric cancer (LAGC). The aim of this study was to develop and visualized a radio-clinical biomarker from pretreatment oversampled CT images to predict the response and prognosis to NCT in LAGC patients.Methods: 1060 LAGC patients were retrospectively recruited from six hospitals from January 2008 to December 2021. The training (TC) and internal validation cohort (IVC) were randomly selected from center I. The external validation cohort (EVC) comprised 265 patients from 5 other centers. An SE-ResNet50-based chemotherapy response predicting system (DL signature) was developed from pretreatment CT images preprocessed with imaging oversampling method (i.e. DeepSMOTE). Then, DL signature and clinic-based features were fed into the deep learning radio-clinical signature (DLCS). The predictive performance was evaluated according to discrimination, calibration and clinical usefulness. Model for OS prediction were built to further explore the survival benefit of the proposed DL signatures and clinicopathological characteristic. Result: DLCS showed perfect performance in predicting the response to NCT in the IVC (AUC, 0.86) and EVC (AUC, 0.82), with good calibration in all cohorts (p > 0.05). In addition, the performance of DLCS was better than that of the clinical model (p＜0.05). Finally, we found that the DL signature could also serve as an independent factor for prognosis (HR, 0.828, p = 0.004). The C-index, iAUC, IBS for the OS model were 0.64, 1.24 and 0.71 in the test set.Conclusion: We proposed the DLCS that links the imaging features to clinical risk factors to generate high accuracy classification of tumor response and risk identification of OS in LAGC patients prior to NCT that then can be used for guiding personalized treatment plans with the help of the visualization of computerized tumor-level characterization.