bluuebunny/crossref_metadata_2025_split huggingface dataset:
Embryonic transcriptome unravels mechanisms and pathways underlying embryonic development with respect to muscle growth, egg production, and plumage formation in native and broiler chickens
Authors: Kanakachari M. , Ashwini R. , Chatterjee R. N. , Bhattacharya T. K. 
Published: October 2022

Background: Muscle development, egg production, and plumage colors are different between native and broiler chickens. The study was designed to investigate why improved Aseel (PD4) is colorful, stronger, and grew slowly compared with the control broiler (CB).Methods: A microarray was conducted using the 7th-day embryo (7EB) and 18th-day thigh muscle (18TM) of improved Aseel and broiler, respectively. Also, we have selected 24 Gallus gallus candidate reference genes from NCBI, and total RNA was isolated from the broiler, improved Aseel embryo tissues, and their expression profiles were studied by real-time quantitative PCR (qPCR). Furthermore, microarray data were validated with qPCR using improved Aseel and broiler embryo tissues.Results: In the differential transcripts screening, all the transcripts obtained by microarray of slow and fast growth groups were screened by fold change ≥ 1 and false discovery rate (FDR) ≤ 0.05. In total, 8,069 transcripts were differentially expressed between the 7EB and 18TM of PD4 compared to the CB. A further analysis showed that a high number of transcripts are differentially regulated in the 7EB of PD4 (6,896) and fewer transcripts are differentially regulated (1,173) in the 18TM of PD4 compared to the CB. On the 7th- and 18th-day PD4 embryos, 3,890, 3,006, 745, and 428 transcripts were up- and downregulated, respectively. The commonly up- and downregulated transcripts are 91 and 44 between the 7th- and 18th-day of embryos. In addition, the best housekeeping gene was identified. Furthermore, we validated the differentially expressed genes (DEGs) related to muscle growth, myostatin signaling and development, and fatty acid metabolism genes in PD4 and CB embryo tissues by qPCR, and the results correlated with microarray expression data.Conclusion: Our study identified DEGs that regulate the myostatin signaling and differentiation pathway; glycolysis and gluconeogenesis; fatty acid metabolism; Jak-STAT, mTOR, and TGF-β signaling pathways; tryptophan metabolism; and PI3K-Akt signaling pathways in PD4. The results revealed that the gene expression architecture is present in the improved Aseel exhibiting embryo growth that will help improve muscle development, differentiation, egg production, protein synthesis, and plumage formation in PD4 native chickens. Our findings may be used as a model for improving the growth in Aseel as well as optimizing the growth in the broiler.
Molecular epidemiology of tuberculosis in the Somali region, eastern Ethiopia
Authors: Worku Getnet , Gumi Balako , Mohammedbirhan Binyam , Girma Musse , Sileshi Henok , Hailu Michael , Wondimu Amanuel , Ashagre Wondimu , Tschopp Rea , Carruth Lauren , Ameni Gobena 
Published: October 2022

BackgroundTuberculosis (TB) is one of the leading causes of morbidity and mortality in low-income countries like Ethiopia. However, because of the limited laboratory infrastructure there is a shortage of comprehensive data on the genotypes of clinical isolates of Mycobacterium tuberculosis (M. tuberculosis) complex (MTBC) in peripheral regions of Ethiopia. The objective of this study was to characterize MTBC isolates in the Somali region of eastern Ethiopia.MethodsA cross-sectional study was conducted in three health institutions between October 2018 and December 2019 in the capital of Somali region. A total of 323 MTBC isolates (249 from pulmonary TB and 74 from extrapulmonary TB) were analyzed using regions of difference 9 (RD 9)-based polymerase chain reaction (PCR) and spoligotyping.ResultsOf the 323 MTBC isolates, 99.7% (95% CI: 99.1–100%) were M. tuberculosis while the remaining one isolate was M. bovis based on RD 9-based PCR. Spoligotyping identified 71 spoligotype patterns; 61 shared types and 10 orphans. A majority of the isolates were grouped in shared types while the remaining grouped in orphans. The M. tuberculosis lineages identified in this study were lineage 1, 2, 3, 4, and 7 with the percentages of 7.4, 2.2, 28.2, 60.4, and 0.6%, respectively. Most (87.9%) of the isolates were classified in clustered spoligotypes while the remaining 12.1% isolates were singletons. The predominant clustered spoligotypes identified were SIT 149, SIT 21, SIT 26, SIT 53, and SIT 52, each consisting of 17.6, 13.3, 8.4, 7.4, and 5%, respectively. Lineage 3 and lineage 4, as well as the age group (15–24), were associated significantly with clustering.ConclusionThe MTBC isolated from TB patients in Somali region were highly diverse, with considerable spoligotype clustering which suggests active TB transmission. In addition, the Beijing spoligotype was isolated in relatively higher frequency than the frequencies of its isolation from the other regions of Ethiopia warranting the attention of the TB Control Program of the Somali region.
Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line
Authors: Lackner Marcel , Neef Sylvia K. , Winter Stefan , Beer-Hammer Sandra , Nürnberg Bernd , Schwab Matthias , Hofmann Ute , Haag Mathias 
Published: October 2022

The combination of high-resolution LC-MS untargeted metabolomics with stable isotope-resolved tracing is a promising approach for the global exploration of metabolic pathway activities. In our established workflow we combine targeted isotopologue feature extraction with the non-targeted X13CMS routine. Metabolites, detected by X13CMS as differentially labeled between two biological conditions are subsequently integrated into the original targeted library. This strategy enables monitoring of changes in known pathways as well as the discovery of hitherto unknown metabolic alterations. Here, we demonstrate this workflow in a PTEN (phosphatase and tensin homolog) null breast cancer cell line (MDA-MB-468) exploring metabolic pathway activities in the absence and presence of the selective PI3Kβ inhibitor AZD8186. Cells were fed with [U-13C] glucose and treated for 1, 3, 6, and 24 h with 0.5 µM AZD8186 or vehicle, extracted by an optimized sample preparation protocol and analyzed by LC-QTOF-MS. Untargeted differential tracing of labels revealed 286 isotope-enriched features that were significantly altered between control and treatment conditions, of which 19 features could be attributed to known compounds from targeted pathways. Other 11 features were unambiguously identified based on data-dependent MS/MS spectra and reference substances. Notably, only a minority of the significantly altered features (11 and 16, respectively) were identified when preprocessing of the same data set (treatment vs. control in 24 h unlabeled samples) was performed with tools commonly used for label-free (i.e. w/o isotopic tracer) non-targeted metabolomics experiments (Profinder´s batch recursive feature extraction and XCMS). The structurally identified metabolites were integrated into the existing targeted isotopologue feature extraction workflow to enable natural abundance correction, evaluation of assay performance and assessment of drug-induced changes in pathway activities. Label incorporation was highly reproducible for the majority of isotopologues in technical replicates with a RSD below 10%. Furthermore, inter-day repeatability of a second label experiment showed strong correlation (Pearson R2 &gt; 0.99) between tracer incorporation on different days. Finally, we could identify prominent pathway activity alterations upon PI3Kβ inhibition. Besides pathways in central metabolism, known to be changed our workflow revealed additional pathways, like pyrimidine metabolism or hexosamine pathway. All pathways identified represent key metabolic processes associated with cancer metabolism and therapy.
Effects of short-term spinal cord stimulation on patients with prolonged disorder of consciousness: A pilot study
Authors: Zhuang Yutong , Yang Yi , Xu Long , Chen Xueling , Geng Xiaoli , Zhao Jizong , He Jianghong 
Published: October 2022

BackgroundSpinal cord stimulation (SCS) can improve the level of awareness of prolonged disorder of consciousness (pDOC), but its application is restricted due to damage of invasive operation. Short-term spinal cord stimulation (st-SCS) in a minimally invasive manner will better balance the benefits and risks.ObjectivesThis study focuses on the safety and efficacy of st-SCS for pDOC and reveals the modulation characteristics of different frequencies of SCS.Methods31 patients received 2-week st-SCS treatment and 3-months follow-up. All patients were divided into two types of frequency treatment groups of 5 Hz and 70 Hz according to the postoperative electroencephalography (EEG) test. The efficacy was assessed based on the revised coma recovery scale (CRS-R).ResultsThe results showed a significant increase in CRS-R scores after treatment (Z = −3.668, p &lt; 0.001) without significant adverse effects. Univariate analysis showed that the minimally conscious state minus (MCS–) benefits most from treatment. Furthermore, two frequency have a difference in the time-point of the CRS-R score increase. 5 Hz mainly showed a significant increase in CRS-R score at 2 weeks of treatment (p = 0.027), and 70 Hz additionally showed a delayed effect of a continued significant increase at 1 week after treatment (p = 0.004).Conclusionst-SCS was safe and effective in improving patients with pDOC levels of consciousness, and was most effective for MCS–. Both 5 Hz and 70 Hz st-SCS can promote consciousness recovery, with 70 Hz showing a delayed effect in particular.
Single- and dual-task gait performance and their diagnostic value in early-stage Parkinson's disease
Authors: Zhang Xiaodan , Fan Weinv , Yu Hu , Li Li , Chen Zhaoying , Guan Qiongfeng 
Published: October 2022

BackgroundGait parameters are considered potential diagnostic markers of Parkinson's disease (PD). We aimed to 1) assess the gait impairment in early-stage PD and its related factors in the single-task (ST) and dual-task (DT) walking tests and 2) evaluate and compare the diagnostic value of gait parameters for early-stage PD under ST and DT conditions.MethodsA total of 97 early-stage PD patients and 41 healthy controls (HC) were enrolled at Hwa Mei hospital. Gait parameters were gathered and compared between the two groups in the ST and DT walking test, controlling for covariates. Utilizing the receiver operating characteristic curve, diagnostic parameters were investigated.ResultsIn the ST walking test, significantly altered gait patterns could be observed in early-stage PD patients in all domains of gait, except for asymmetry (P &lt; 0.05). Compared to the ST walking test, the early-stage PD group performed poorly in the DT walking test in the pace, rhythm, variability and postural control domain (P &lt; 0.05). Older, heavier subjects, as well as those with lower height, lower level of education and lower gait velocity, were found to have a poorer gait performance (P &lt; 0.05). Stride length (AUC = 0.823, sensitivity, 68.0%; specificity, 85.4%; P &lt; 0.001) and heel strike angle (AUC = 0.796, sensitivity, 71.1%; specificity, 80.5%; P &lt; 0.001) could distinguish early-stage PD patients from HCs with moderate accuracy, independent of covariates. The diagnostic accuracy of gait parameters under ST conditions were statistically noninferior to those under DT conditions(P&gt;0.05). Combining all gait parameters with diagnostic values under ST and DT walking test, the predictive power significantly increased with an AUC of 0.924 (sensitivity, 85.4%; specificity, 92.7%; P &lt; 0.001).ConclusionGait patterns altered in patients with early-stage PD but the gait symmetry remained preserved. Stride length and heel strike angle were the two most prominent gait parameters of altered gait in early-stage of PD that could serve as diagnostic markers of early-stage PD. Our findings are helpful to understand the gait pattern of early-stage PD and its related factors and can be conducive to the development of new diagnostic tools for early-stage PD.
Diagnostic model optimization method for ADHD based on brain network analysis of resting-state fMRI images and transfer learning neural network
Authors: Meng Xiaojing , Zhuo Wenjie , Ge Peng , Zou Bin , Zhu Yao , Liu Weidong , Li Xuzhou 
Published: October 2022

Introduction: Attention deficit and hyperactivity disorder (ADHD) is a common inherited disease of the nervous system whose cause(s) and pathogenesis remain unclear. Currently, the diagnosis of ADHD is mainly based on clinical experience and guidelines that have laid out some diagnostic standards. Our study aimed to apply a learning-based classification method to assist the ADHD diagnosis based on high-dimensional resting-state fMRI.Methods: Our study selected the ADHD-200 Peking dataset of resting-state fMRI, which has an ADHD patient (n = 142) group and a typically developing control (TDC) healthy control (n = 102) group. We first used Pearson and partial correlation coefficients to perform functional connectivity (FC) analysis between ROIs. Then, the Pearson and partial correlation coefficient matrices were concatenated into a dual-channel feature to build a dual data channel as input to the transfer learning neural network (TLNN) architecture. Finally, we transferred the pretrained model from the auxiliary domain to our target domain and fine-tuned it.Results: Based on the Pearson correlation coefficient, FC between ROIs was detected in 22 brain regions, including the fusiform gyrus, superior frontal gyrus, posterior superior temporal sulcus, inferior parietal lobule, anterior cingulate cortex, and parahippocampal gyrus. Based on the partial correlation coefficient, we found FC in the salient network, default network, sensory-motor network, dorsal attention network, and cerebellum network. With the TLNN architecture, we solved the problem of insufficient training data and improved the sensitivity of the classification method. When the VGG model (fine-tuned transfer strategy, 1,024 fully connected layers) was applied, the accuracy of TLNN classification ultimately reached 82%.Conclusion: Our study suggests that completing the training of the target domain by transferring the prior knowledge of the auxiliary domain is effective in solving the classification problem of small sample datasets. Based on prior knowledge of FC analysis, TLNN classification may assist ADHD diagnosis in a new way.
Performance effects of internal pre- and per-cooling across different exercise and environmental conditions: A systematic review
Authors: Roriz Maria , Brito Pedro , Teixeira Filipe J. , Brito João , Teixeira Vitor Hugo 
Published: October 2022

Exercise in a hot and humid environment may endanger athlete’s health and affect physical performance. This systematic review aimed to examine whether internal administration of ice, cold beverages or menthol solutions may be beneficial for physical performance when exercising in different environmental conditions and sports backgrounds. A systematic search was performed in PubMed, Web of Science, Scopus and SPORTDiscus databases, from inception to April 2022, to identify studies meeting the following inclusion criteria: healthy male and female physically active individuals or athletes (aged ≥18 years); an intervention consisting in the internal administration (i.e., ingestion or mouth rinse) of ice slush, ice slurry or crushed ice and/or cold beverages and/or menthol solutions before and/or during exercise; a randomized crossover design with a control or placebo condition; the report of at least one physical performance outcome; and to be written in English. Our search retrieved 2,714 articles in total; after selection, 43 studies were considered, including 472 participants, 408 men and 64 women, aged 18-42 years, with a VO2max ranging from 46.2 to 67.2 mL⋅kg–1⋅min–1. Average ambient temperature and relative humidity during the exercise tasks were 32.4 ± 3.5°C (ranging from 22°C to 38°C) and 50.8 ± 13.4% (varying from 20.0% to 80.0%), respectively. Across the 43 studies, 7 exclusively included a menthol solution mouth rinse, 30 exclusively involved ice slurry/ice slush/crushed ice/cold beverages intake, and 6 examined both the effect of thermal and non-thermal internal techniques in the same protocol. Rinsing a menthol solution (0.01%) improved physical performance during continuous endurance exercise in the heat. Conversely, the ingestion of ice or cold beverages did not seem to consistently increase performance, being more likely to improve performance in continuous endurance trials, especially when consumed during exercises. Co-administration of menthol with or within ice beverages seems to exert a synergistic effect by improving physical performance. Even in environmental conditions that are not extreme, internal cooling strategies may have an ergogenic effect. Further studies exploring both intermittent and outdoor exercise protocols, involving elite male and female athletes and performed under not extreme environmental conditions are warranted.Systematic review registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021268197], identifier [CRD42021268197].
Two-step artificial intelligence system for endoscopic gastric biopsy improves the diagnostic accuracy of pathologists
Authors: Zhu Yan , Yuan Wei , Xie Chun-Mei , Xu Wei , Wang Jia-Ping , Feng Li , Wu Hui-Li , Lu Pin-Xiang , Geng Zi-Han , Lv Chuan-Feng , Li Quan-Lin , Hou Ying-Yong , Chen Wei-Feng , Zhou Ping-Hong 
Published: October 2022

BackgroundEndoscopic biopsy is the pivotal procedure for the diagnosis of gastric cancer. In this study, we applied whole-slide images (WSIs) of endoscopic gastric biopsy specimens to develop an endoscopic gastric biopsy assistant system (EGBAS).MethodsThe EGBAS was trained using 2373 WSIs expertly annotated and internally validated on 245 WSIs. A large-scale, multicenter test dataset of 2003 WSIs was used to externally evaluate EGBAS. Eight pathologists were compared with the EGBAS using a man-machine comparison test dataset. The fully manual performance of the pathologists was also compared with semi-manual performance using EGBAS assistance.ResultsThe average area under the curve of the EGBAS was 0·979 (0·958-0·990). For the diagnosis of all four categories, the overall accuracy of EGBAS was 86·95%, which was significantly higher than pathologists (P&lt; 0·05). The EGBAS achieved a higher κ score (0·880, very good κ) than junior and senior pathologists (0·641 ± 0·088 and 0·729 ± 0·056). With EGBAS assistance, the overall accuracy (four-tier classification) of the pathologists increased from 66·49 ± 7·73% to 73·83 ± 5·73% (P&lt; 0·05). The length of time for pathologists to manually complete the dataset was 461·44 ± 117·96 minutes; this time was reduced to 305·71 ± 82·43 minutes with EGBAS assistance (P = 0·00).ConclusionsThe EGBAS is a promising system for improving the diagnosis ability and reducing the workload of pathologists.
A novel amino acid metabolism-related gene risk signature for predicting prognosis in clear cell renal cell carcinoma
Authors: Su Jiaqi , Tian Xi , Zhang Zihao , Xu Wenhao , Anwaier Aihetaimujiang , Ye Shiqi , Zhu Shuxuan , Wang Yue , Shi Guohai , Qu Yuanyuan , Zhang Hailiang , Ye Dingwei 
Published: October 2022

BackgroundRenal cancer is one of the most lethal cancers because of its atypical symptoms and metastatic potential. The metabolism of amino acids and their derivatives is essential for cancer cell survival and proliferation. Thus, the construction of the amino acid metabolism-related risk signature might enhance the accuracy of the prognostic model and shed light on the treatments of renal cancers.MethodsRNA expression and clinical data were downloaded from Santa Cruz (UCSC) Xena, GEO, and ArrayExpress databases. The “DESeq2” package identified the differentially expressed genes. Univariate COX analysis selected prognostic genes related to the metabolism of amino acids. Patients were divided into two clusters using the “ConsensusClusterPlus” package, and the CIBERSORT, ESTIMATE methods were explored to assess the immune infiltrations. The LASSO regression analysis constructed a risk model which was evaluated the prediction accuracy in two independent cohorts. The genomic alterations and drug sensitivity of 18-LASSO-genes were assessed. The differentially expressed genes between two clusters were used to perform functional enrichment analysis and weighted gene co-expression network analysis (WGCNA). Furthermore, external validation of TMEM72 expression was conducted in the FUSCC cohort containing 33 ccRCC patients.ResultsThe amino acid metabolism-related genes had significant correlations with prognosis. The patients in Cluster A demonstrated better survival, lower Treg cell proportion, higher ESTIMATE scores, and higher cuproptosis-related gene expressions. Amino acid metabolism-related genes with prognostic values were used to construct a risk model and patients in the low risk group were associated with improved outcomes. The Area Under Curve of the risk model was 0.801, 0.777, and 0.767 at the first, second, and third year respectively. The external validation cohort confirmed the stable prognostic value of the risk model. WGCNA identified four gene modules correlated with immune cell infiltrations and cuproptosis. We found that TMEM72 was downregulated in tumors by using TCGA, GEO datasets (p&lt;0.001) and the FUSCC cohort (p=0.002).ConclusionOur study firstly constructed an 18 amino acid metabolism related signature to predict the prognosis in clear cell renal cell carcinoma. We also identified four potential gene modules potentially correlated with cuproptosis and identified TMEM72 downregulation in ccRCC which deserved further studies.