bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reversing the Immunosuppressive Microenvironment with Reduced Redox Level by Microwave-Chemo-Immunostimulant Ce-Mn MOF for Improved Immunotherapy
Authors: Zeng Zhiheng , Fu Changhui , Sun Xiaohan , Niu Meng , Ren Xiangling , Tan Longfei , Wu Qiong , Huang Zhongbing , Meng Xianwei 
Published: July 2022

Abstract
Backgrounds:
Reversing the immunosuppressive microenvironment (TME) in the tumor is widely deemed to be an effective strategy to improve immune therapy. In particular, the redox balance in TME needs to be well controlled due to its critical role in mediating the functions of various cells, including cancer cells and immune-suppressive cells. Here, we propose an efficient strategy to reshape the redox homeostasis to reverse immunosuppressive TME.
Results
Specifically, we developed a microwave-chemo-immunostimulant CMMCP to promote the generation of the tumor-infiltration T cells by simultaneously reducing the reactive oxygen species (ROS) and glutathione (GSH) and improving the oxygen levels in TME. The CMMCP was designed by loading chemotherapy drugs cisplatin into the bimetallic Ce-Mn MOF nanoparticles coated with polydopamine. The Ce-Mn MOF nanoparticles can effectively improve the catalytic decomposition of ROS into O2 under microwave irradiation, resulting in the overcome hypoxia and limited ROS generation. Besides, the activity of intracellular GSH in TME was reduced by the redox reaction with Mn2+ of Ce-Mn MOF nanoparticles. The reprogrammed TME not only boosts the immunogenic cell death (ICD) induced by cisplatin and microwave hyperthermia but also gives rise to the polarization of pro-tumor M2-type macrophages to the anti-tumor M1-type ones.
Conclusion
Our in vivo experimental results demonstrate that the microwave-chemo-immunostimulant CMMCP significantly enhances the T cells infiltration and thus improves the antitumor effect. This study presents an easy, safe, and effective strategy for a whole-body antitumor effect after local treatment.
Iterative construction of the optimal sunspot number series
Authors: Švanda Michal , Pavelková Martina , Dvořák Jiří , Solarová Božena 
Published: July 2022

Abstract
The relative number of sunspots represents the longest evidence describing the level of solar activity. As such, its use goes beyond solar physics, e.g. towards climate research. The construction of a single representative series is a delicate task which involves a combination of observation of many observers. We propose a new iterative algorithm that allows to construct a target series of relative sunspot number of a hypothetical stable observer by optimally combining series obtained by many observers. We show that our methodology provides us with results that are comparable with recent reconstructions of both sunspot number and group number. Furthermore, the methodology accounts for the possible non-solar changes of observers' time series such as gradually changing observing conditions or slow change in the observers vision. It also provides us with reconstruction uncertainties. We apply the methodology to a limited sample of observations by ČESLOPOL network and discuss its properties and limitations.
Differential diagnosis value of ultrasound and radiomics features in B-cell and T-cell lymphoma
Authors: Zhou Yasu , Yuan Ya , Deng Hongyan , Lu Wenjuan , Li Lu , Ye Xinhua 
Published: July 2022

Abstract
Objectives
One of the challenges in the diagnosis of composite lymphoma is the selection of the lymph node adequately reflect heterogeneity for biopsy. This study evaluated whether ultrasound and radiomics may help differentiating B-cell and T-cell lymphoma.
Materials and Methods
This is a retrospective study and a total of 124 patients with B-cell lymphoma(n = 97) or T-cell lymphoma(n = 27) were enrolled in. Each patient went through ultrasound examinations including two dimensional ultrasound (2DUS) and contrast-enhanced ultrasound (CEUS). Radiomic features were extracted from gray-scale ultrasound images and then selected. A radiomics score (Rad-score) was calculated via a linear combination. Performances of differential diagnosis of ultrasound, radiomics and the combination were compared with each other.
Results
Three ultrasound features (hilum, echo characteristic and PI of TIC analysis) and three radiomics features (texture features) were finally chosen as statistically significant. The AUC of ultrasound based on the three features was 0.829, with a sensitivity, specificity, and accuracy of 92.6%,63.9%, and 70.2%, respectively. The AUC of radiomics based on Rad-score was 0.666, with a sensitivity, specificity, and accuracy of 74.1%, 55.7%, and 59.7%, respectively. By comparison, ultrasound combined with radiomics showed greatest diagnostic value in distinguishing B-cell and T-cell lymphoma, with the AUC of 0.858, and a sensitivity, specificity, accuracy of 92.6%, 74.2%, 78.2%.
Conclusions
Ultrasound combined with radiomics are of great diagnostic value for differentiating B-cell and T-cell lymphoma and enables us to select a lymph node that adequately reflect heterogeneity for biopsy and avoid missed diagnosis.
Comparative Analysis of Earth Rotation Parameters Using VLBI Observations During CONT and GNSS Observations
Authors: Yu Kehao , Sun Mengqi , Li Lihua , Shi Haowei 
Published: July 2022

Abstract
The Earth rotation parameters mainly include the displacement and rate of the Earth's poles, length of day, which can be estimated based on VLBI and GNSS. In order to obtain the ERP results with higher accuracy, two VLBI data processing schemes were compared. VLBI observations during 2008, 2011, 2014, and 2017 are processed with VieVS. In addition, the experiments to estimate ERP using CONT08, CONT11, CONT14, and CONT17 campaigns were also designed. The results showed that the higher accuracy of ERP were calculated using CONT campaigns. At the same time, ERP estimations using the 86 globally distributed GNSS observatories data during the same period were processed by GAMIT. The ERP results from the CONT campaigns and GNSS observations estimated were then combined in a weighted manner, based on the Helmert variance component estimation and the IERS14 C04 sequences, respectively. The weighted results showed that the Root Mean Square Error (RMSE) of polar motion was about between 0.05 and 0.10 mas, and the RMSE in UT1-UTC ranged from 0.005 and 0.02 ms.
Gene content and coding diversity of growth hormone loci of apes
Authors: González-Álvarez Rafael , Rodríguez-Sánchez Irám Pablo , Barrera-Saldaña Hugo Alberto 
Published: July 2022

Abstract
Growth hormone (GH) locus experienced dramatic evolution in primates, becoming multigenic and diverse in anthropoids. Despite sequence information from vast number of primate species, it has remained unclear how the multigene family was favored feature. We sought to compare the structure and composition of the apes’ GH loci as a prerequisite to understanding their origin and possible evolutionary role. GH loci of chimpanzee, gorilla, and orangutan were sequenced from bacterial artificial chromosomes, while those of modern man, neanderthal, gibbon, and wild boar were retrieved from GenBank. Coding regions, regulatory elements, and repetitive sequences were identified and compared among species. GH loci of all analyzed species are flanked by the genes CD79B (5´) and ICAM-1(3´). In man, neanderthal, and chimpanzee the loci are integrated by five genes almost indistinguishable, however while in the former two they render three different hormones, in the latter one four different proteins are derived. Gorilla exhibits six genes, gibbon seven, and orangutan four. The sequences of proximal promoters, enhancers, P-elements, and a locus control region (LCR) are highly conserved. The locus evolution might have implicated duplications of the ancestral pituitary GH-N gene and subsequent diversification of the copies, to lead to the placental single GH-V gene and to the multiple also placental CSH genes.
Metabolic engineering for Escherichia coli BW25113 for the production of 5-Aminolevulinic Acid based on CRISPR/Cas9 mediated gene knockout and metabolic pathway modification
Authors: Ye Changchuan , Yang Yuting , Chen Xi , Yang Lijie , Hua Xia , Yang Mengjie , Zeng Xiangfang , Qiao Shiyan 
Published: July 2022

Abstract
5-Aminolevulinic acid (ALA) recently received much attention due to its potential application in many fields. In this study, an ALA production strain of Escherichia coli was constructed by rational metabolic engineering and stepwise improvement based on known regulatory and metabolic information and CRISPR/Cas9 mediated gene knockout. A metabolic strategy to produce ALA directly from glucose in this recombinant E. coli via the C5 pathway was applied herein. The rational metabolic engineering by gene knockouts significantly improved ALA production from 662.3 to 1601.7 mg/L. In addition, we tried to synergistically produce ALA via the C4 pathway in recombinant strain. The expression of a modified hemA gene, encoding an ALA synthase from Rhodobacter sphaeroides, improved ALA production from 1601.7 to 2099.7 mg/L. After 24 h cultivation, a yield of 0.210 g ALA per g glucose was achieved by constructed E. coli D5:FYABD. These results suggest that an industrially competitive strain can be efficiently developed by metabolic engineering based on combined rational modification and optimization of gene expression.
Comparison of ocular biometry obtained with Tomey OA-2000 and IOLMaster 700 in silicone oil-filled eyes
Authors: Xiong Yongqun , Lin Yongdong , Zhao Zifeng , Wang Hongxi , Zhang Guihua 
Published: July 2022

Abstract
Purpose
To evaluate a new non-contact instrument (OA-2000) measuring the ocular biometry parameters of silicone oil (SO)-filled aphakia eyes, as compared with IOLMaster 700.
Methods
Forty SO-filled aphakia eyes of 40 patients were enrolled in this cross-sectional clinical trial. The axial length (AL), central corneal thickness (CCT), keratometry (Kf [flattest keratometry] and Ks [steep keratometry, 90° apart from Kf]), and axis of the Kf (Ax1) measured with OA-2000 were compared with those measured with IOLMaster 700. The agreements of the results between the two devices were evaluated by Bland-Altman analysis. The differences of measurement results were evaluated by paired t test, and the correlation was evaluated by the Pearson coefficient.
Results
The mean AL obtained with the OA-2000 was 23.57 ± 0.93mm (range: 21.50 to 25.68mm), and that obtained with the IOLMaster 700 was 23.69 ± 0.94mm (range: 21.85 to 25.86mm), resulting in a mean offset of 0.124 ± 0.125mm (p < 0.001). The AL obtained with the two devices showed a strong linear correlation (r = 0.991). It was also found that the Kf, Ks and Ax1had excellent correlation (Kf, r = 0.980; Ks, r = 0.987; and Ax1, r = 0.966). There was no statistical significance in the pair t test of the Kf, Ks and Ax1. The CCT obtained with the OA-2000 was 530.7 ± 30.9µm (range: 470 to 578µm), and that obtained with the IOLMaster 700 was 545.3 ± 33.9µm (range: 479 to 600µm). The average offset was 14.6 ± 7.5µm, p < 0.001. The coefficient of variations of the biometric parameters obtained with the two devices were lower than 1% except for the Ax1.
Conclusion
In SO-filled aphakia eyes, the ocular biometry obtained with the OA-2000 and IOLMaster 700 has good correlation and consistency. OA-2000 is an accurate instrument that can provide fundus surgeons with the interesting information on ocular biological parameters of SO-filled aphakia eyes.
Does the feedback of blood results in observational studies influence response and consent? A randomised study of the Understanding Society Innovation Panel
Authors: Benzeval Michaela , Andrayas Alexandria , Mazza Jan , Baghal Tarek Al , Burton Jonathon , Crossley Thomas F , Kumari Meena 
Published: July 2022

Abstract
Background: While medical studies generally provide health feedback to participants, in observational studies this is not always the case due to logistical and financial difficulties, or concerns about changing observed behaviours. However, evidence suggests that lack of feedback may deter participants from providing biological samples. This paper investigates the effect of offering feedback of blood results on participation in biomeasure sample collection.Methods: Participants aged 16 and over from a longitudinal study – the Understanding Society Innovation Panel - were randomised to three arms – nurse interviewer, interviewer, web survey – and invited to participate in biomeasures data collection. Within each arm they were randomised to receive feedback of their blood results or not. For those interviewed by a nurse both venous and dried blood samples (DBS) were taken in the interview. For the other two arms, they were asked if they would be willing to take a sample, and if they agreed a DBS kit was left or sent to them so the participant could take their own sample and return it. Blood samples were analysed and, if in the feedback arms, participants were sent their total cholesterol and HbA1c results.Response rates for feedback and non-feedback groups were compared: overall; in each arm of the study; by socio-demographic and health characteristics; and by previous study participation. Logistic regression models of providing a blood sample by feedback group and data collection approach controlling for confounders were calculated.Results: Overall 2162 (80.3% of individuals in responding households) took part in the survey; of those 1053 (48.7%) consented to provide a blood sample. Being offered feedback had little effect on overall participation but did increase consent to provide a blood sample (unadjusted OR 1.38; CI: 1.16–1.64). Controlling for participant characteristics, the effect of feedback was highest among web participants (1.55; 1.11–2.17), followed by interview participants (1.35; 0.99 –1.84) and then nurse interview participants (1.30; 0.89–1.92).Conclusions: Offering feedback of blood results increased willingness to give samples, especially for those taking part in a web survey.
Proteomic analyses related to inflammation and pain in children with juvenile idiopathic arthritis
Authors: Elfving Andreas , Harila-Saari Arja , Nilsson Ludwig , Berntson Lillemor 
Published: July 2022

Abstract
Background
To explore levels of inflammatory proteins (including cytokines) in plasma samples from children with juvenile idiopathic arthritis (JIA) and their relation to the degree of inflammation and pain.
Methods
A total of 69 plasma samples were collected from 51 children with JIA (51 at diagnosis in a higher disease activity state, 18 at follow-up in a lower disease activity state) and 18 healthy controls. Relative levels of 92 proteins related to a wide range of biological processes in inflammation were obtained using a proximity extension assay panel. Comparisons between children with and without JIA, in different JIA disease states, by juvenile disease activity score (JADAS 27), and by degree of pain on visual analogue scale (VAS), were performed using parametric and non-parametric statistical methods.
Results
Nineteen proteins involved in arthritic inflammation, such as interleukin 6 (IL-6) and S100 protein A12 (S100A12), were higher in patients with JIA than controls, seven decreased significantly during treatment, and 18 correlated significantly with JADAS27 score. Three proteins correlated with pain VAS scores in unadjusted analyses: the glial cell line-derived neurotrophic factor (GDNF), transforming growth factor beta (TGFβ), and IL-18R1. Levels of GDNF correlated significantly with pain VAS scores but not with JADAS 27.
Conclusions
Plasma levels of 18 of 92 tested proteins correlated with degree of disease activity. Levels of GDNF originating from neural cells correlated with pain without correlating to inflammatory degree, suggesting that it may play a role in pain in JIA. Further studies in larger cohorts are warranted.
Fatigue like behavior in different tumor-bearing mice metastasis model for the study of colorectal cancer
Authors: guo wei , liu shan , Yang Huifei , Wang Shujing , Zheng Xinting , Yang Hongxing , Xiao Zhiwei , Xiao Xi , Yang Caizhi , Sun Lingling , Chen Hanrui , Lin Lizhu 
Published: July 2022

Abstract
Background: Fatigue is a usual occurrence in tumor patients during illness and treatment, patients with cancer related fatigue (CRF) showed signs of fatigue after tumor development, and not only in patients with advanced process, and still a evidently subjective fatigue even after effective symptomatic treatment. Methods: In this study, two metastasis models of BALB/c mice were established by subcutaneous and intraperitoneal inoculation of tumor cells, and a series of quantitative description and qualitative prediction techniques were adopted to investigate the effects of subcutaneous and intraperitoneal tumorigenesis on the life of mice, After 21 days periods, all mice were tested for several aspects of CRF: (1) size of tumor volume; (2) behavioral detection of fatigue; (3) liver, kidney function and lipid levels; (4) organ indices; (5) pathological and electron microscopic observation of gastrocnemius and quadriceps muscles; and (6) determination of oxidative stress indices in gastrocnemius.Results: Compared with normal mice, the fatigue level significantly increased in both models mice, and tumor growth was accompanied by significant fatigue in the organism and might be related to decrease of skeletal muscle mass, destruction of muscle structure, and disorders of skeletal muscle metabolism. Different analyses were performed on the two models, and it was found that the fatigue level was more severe in the abdominal transfer model compared with the subcutaneous transplantation tumor model. HGB and HCT decreased significantly, liver and kidney function were more severely impaired, gastrocnemius muscle area was more reduced, and oxidative damage of gastrocnemius muscle was higher. Conclusion: This study provides a comprehensive description of the main processes that cause fatigue due to tumor itself and provides a standard and reliable animal model for further pharmacological or pharmacodynamic studies.
Construction of XGBoost Model for Early Lung Cancer Prediction Based on Metabolic Indexes
Authors: Guan Xiuliang , Ma Rufei , Teng Nan , Du Yue , Ou Shu , Li Xiaofeng 
Published: July 2022

Abstract
Background
In order to test the predictive effect of the XGBoost model in the machine learning algorithm for early lung cancer diagnosis and the importance of amino acid and carnitine indicators in affecting the occurrence of lung cancer, this study used data from 848 patients with lung cancer and benign lung nodules.
Results
The study selected 49 serum amino acid and carnitine indexes, as well as age and gender demographic indexes of subjects from a hospital in Dalian City, Liaoning Province. After screening with stepwise regression algorithm, 16 indicators were included.Draw the ROC curve of 5 models, comparing the accuracy, precision, recall, and F1 score of the lung cancer prediction model with the nomogram and the machine learning algorithm, the optimal model (XGBoost) was obtained, and the feature importance ranking was obtained using the XGBoost model.In the method of screening indicators, the index modeling accuracy after screening using the stepwise regression algorithm was the highest, which was 75.29%, and the AUC value was 0.81. In the model performance comparison, the accuracy of the nomogram is 68.24%, and the AUC value is 0.74. Among the machine learning models, the XGBoost algorithm has the best performance, with an accuracy rate of 75.29% and an ROC value of 0.81. In the model feature importance score results, the top three important features were ornithine, valine and palmitoylcarnitine.
Conclusions
The combined use of nomogram and machine learning model(XGBoost) not only improves the accuracy of the lung cancer prediction model, but also makes the understanding of the results more intuitive and convenient for doctors and patients.
Wnt4 and ephrinB2 instruct apical constriction via Dishevelled and non-canonical signaling
Authors: Yoon Jaeho , Sun Jian , Lee Moonsup , Hwang Yoo-Seok , Daar Ira 
Published: July 2022

Abstract
Apical constriction is a cell shape change critical to vertebrate neural tube closure, and the contractile force required for this process is generated by actin-myosin networks. The signaling cue that instructs this process has remained elusive. Here, we identify Wnt4 and the transmembrane ephrinB2 protein as playing an instructive role in neural tube closure as members of a signaling complex we termed WERDS (Wnt4, EphrinB2, Ror2, Dishevelled (Dsh2), and Shroom3). Disruption of function or interaction among members of the WERDS complex results in defects of apical constriction and neural tube closure. The mechanism of action involves Wnt4 binding the non-canonical Wnt receptor, Ror2, and enhancing an interaction with ephrinB2, through the main Wnt scaffold protein, Dsh2. This complex in turn recruits the adaptor protein Shroom3, which activates Rho-associated kinase (Rock) to induce apical constriction. Remarkably, we also discovered that a key part of this mechanism is that ephrinB2 antagonizes Wnt/β-catenin signaling through the interaction with Dsh2, which switches Dsh2 function from canonical to non-canonical Wnt signaling that is required for proper neural tube closure.
scDREAMER: atlas-level integration of single-cell datasets using deep generative model paired with adversarial classifier
Authors: Shree Ajita , Pavan Musale Krushna , Zafar Hamim 
Published: July 2022

Abstract
Integration of heterogeneous single-cell sequencing datasets generated across multiple tissue locations, time and conditions is essential for a comprehensive understanding of the cellular states and expression programs underlying complex biological systems. Here, we present scDREAMER (https://github.com/Zafar-Lab/scDREAMER), a novel data integration framework that employs a novel adversarial variational autoencoder for learning lower-dimensional cellular embeddings and a batch classifier neural network for the removal of batch effects. Using five real benchmarking datasets, we demonstrated that scDREAMER can overcome critical challenges including the presence of skewed cell types among batches, nested batch effects, large number of batches and conservation of development trajectory across different batches. Moreover, our benchmarking demonstrated that scDREAMER outperformed state-of-the-art methods in batch-correction and conservation of biological variation. Using a 1 million cells dataset, we further showed that scDREAMER is scalable and can perform atlas-level integration across species (e.g., human and mouse) while being faster than other deep-learning-based methods.