bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reducing the muscle activity of walking using a portable hip exoskeleton based on human-in-the-loop optimization
Authors: Xu Linghui , Liu Xiaoguang , Chen Yuting , Yu Linfan , Yan Zehao , Yang Canjun , Zhou Congcong , Yang Wei 
Published: May 2023

Introduction: Human-in-the-loop optimization has made great progress to improve the performance of wearable robotic devices and become an effective customized assistance strategy. However, a lengthy period (several hours) of continuous walking for iterative optimization for each individual makes it less practical, especially for disabled people, who may not endure this process. Methods: In this paper, we provide a muscle-activity-based human-in-the-loop optimization strategy that can reduce the time spent on collecting biosignals during each iteration from around 120 s to 25 s. Both Bayesian and Covariance Matrix Adaptive Evolution Strategy (CMA-ES) optimization algorithms were adopted on a portable hip exoskeleton to generate optimal assist torque patterns, optimizing rectus femoris muscle activity. Four volunteers were recruited for exoskeleton-assisted walking trials. Results and Discussion: As a result, using human-in-the-loop optimization led to muscle activity reduction of 33.56% and 41.81% at most when compared to walking without and with the hip exoskeleton, respectively. Furthermore, the results of human-in-the-loop optimization indicate that three out of four participants achieved superior outcomes compared to the predefined assistance patterns. Interestingly, during the optimization stage, the order of the two typical optimizers, i.e., Bayesian and CMA-ES, did not affect the optimization results. The results of the experiment have confirmed that the assistance pattern generated by muscle-activity-based human-in-the-loop strategy is superior to predefined assistance patterns, and this strategy can be achieved more rapidly than the one based on metabolic cost.
Genome analysis for the identification of genes involved in phenanthrene biodegradation pathway in Stenotrophomonas indicatrix CPHE1. Phenanthrene mineralization in soils assisted by integrated approaches
Authors: Lara-Moreno Alba , Merchán Francisco , Morillo Esmeralda , Zampolli Jessica , Di Gennaro Patrizia , Villaverde Jaime 
Published: May 2023

Phenanthrene (PHE) is a highly toxic compound, widely present in soils. For this reason, it is essential to remove PHE from the environment. Stenotrophomonas indicatrix CPHE1 was isolated from an industrial soil contaminated by polycyclic aromatic hydrocarbons (PAHs) and was sequenced to identify the PHE degrading genes. Dioxygenase, monooxygenase, and dehydrogenase gene products annotated in S. indicatrix CPHE1 genome were clustered into different trees with reference proteins. Moreover, S. indicatrix CPHE1 whole-genome sequences were compared to genes of PAHs-degrading bacteria retrieved from databases and literature. On these basis, reverse transcriptase-polymerase chain reaction (RT-PCR) analysis pointed out that cysteine dioxygenase (cysDO), biphenyl-2,3-diol 1,2-dioxygenase (bphC), and aldolase hydratase (phdG) were expressed only in the presence of PHE. Therefore, different techniques have been designed to improve the PHE mineralization process in five PHE artificially contaminated soils (50 mg kg−1), including biostimulation, adding a nutrient solution (NS), bioaugmentation, inoculating S. indicatrix CPHE1 which was selected for its PHE-degrading genes, and the use of 2-hydroxypropyl-β-cyclodextrin (HPBCD) as a bioavailability enhancer. High percentages of PHE mineralization were achieved for the studied soils. Depending on the soil, different treatments resulted to be successful; in the case of a clay loam soil, the best strategy was the inoculation of S. indicatrix CPHE1 and NS (59.9% mineralized after 120 days). In sandy soils (CR and R soils) the highest percentage of mineralization was achieved in presence of HPBCD and NS (87.3% and 61.3%, respectively). However, the combination of CPHE1 strain, HPBCD, and NS showed to be the most efficient strategy for sandy and sandy loam soils (LL and ALC soils showed 35% and 74.6%, respectively). The results indicated a high degree of correlation between gene expression and the rates of mineralization.
Phase-contrast imaging with synchrotron hard X-ray reveals the effect of icariin on bone tissue morphology and microstructure in rabbits with early glucocorticoid-induced osteonecrosis of the femoral head
Authors: Yang Xu , Shi Lijun , Li Aifeng , Gao Fuqiang , Sun Wei , Li Zirong 
Published: May 2023

Background: Phase-contrast imaging (PCI) with synchrotron hard X-ray was used to observe the changes in bone tissue morphology and microstructure in rabbit models of early glucocorticoid-induced osteonecrosis of the femoral head (ONFH), and to evaluate the intervention effect of Icariin.Methods: Fifty mature New Zealand rabbits (weighing 2.5–3.0 kg) were randomly divided into a control group (n = 10), a glucocorticoid group (n = 20), and an Icariin group (n = 20). The glucocorticoid group and the Icariin group were sequentially injected with lipopolysaccharide (LPS) and methylprednisolone (MPS) to establish a glucocorticoid-induced ONFH animal model. The Icariin group was given Icariin solution when methylprednisolone was injected for the first time, and the control group and glucocorticoid group were given the same amount of normal saline. Animals were sacrificed after 6 weeks, and bilateral femoral head specimens were taken for research. The right femoral head was observed by PCI with synchrotron hard X-ray technology, and the left femoral head was verified by Micro-CT scanning and HE staining.Results: Forty-three animals (nine in the control group, sixteen in the glucocorticoid group, and eighteen in the Icariin group) were included in the study. PCI with synchrotron hard X-ray revealed that the trabecular bone in the glucocorticoid group was thinned, broken, and structurally damaged, whereas the trabecular bone in the Icariin group had normal volume, thickness, and a relatively intact structure. Micro-CT scan reconstruction and HE staining were used to verify the reliability of this technique in identifying osteonecrosis.Conclusion: The effects of Icariin were observed in an early glucocorticoid-induced ONFH rabbit model using PCI with synchrotron hard X-ray. Icariin weakens the destructive effect of glucocorticoids on bone tissue structure, improves bone tissue morphology, and stabilizes bone microstructure. This technique may provide a definitive, non-invasive alternative to histological examination for the diagnosis of early ONFH.
Unorthodox localization of P2X7 receptor in subcellular compartments of skeletal system cells
Authors: Penolazzi Letizia , Notarangelo Maria Pina , Lambertini Elisabetta , Vultaggio-Poma Valentina , Tarantini Mario , Di Virgilio Francesco , Piva Roberta 
Published: May 2023

Identifying the subcellular localization of a protein within a cell is often an essential step in understanding its function. The main objective of this report was to determine the presence of the P2X7 receptor (P2X7R) in healthy human cells of skeletal system, specifically osteoblasts (OBs), chondrocytes (Chs) and intervertebral disc (IVD) cells. This receptor is a member of the ATP-gated ion channel family, known to be a main sensor of extracellular ATP, the prototype of the danger signal released at sites of tissue damage, and a ubiquitous player in inflammation and cancer, including bone and cartilaginous tissues. Despite overwhelming data supporting a role in immune cell responses and tumor growth and progression, a complete picture of the pathophysiological functions of P2X7R, especially when expressed by non-immune cells, is lacking. Here we show that human wild-type P2X7R (P2X7A) was expressed in different samples of human osteoblasts, chondrocytes and intervertebral disc cells. By fluorescence microscopy (LM) and immunogold transmission electron microscopy we localized P2X7R not only in the canonical sites (plasma membrane and cytoplasm), but also in the nucleus of all the 3 cell types, especially IVD cells and OBs. P2X7R mitochondrial immunoreactivity was predominantly detected in OBs and IVD cells, but not in Chs. Evidence of subcellular localization of P2X7R may help to i. understand the participation of P2X7R in as yet unidentified signaling pathways in the joint and bone microenvironment, ii. identify pathologies associated with P2X7R mislocalization and iii. design specific targeted therapies.
A chatbot for mental health support: exploring the impact of Emohaa on reducing mental distress in China
Authors: Sabour Sahand , Zhang Wen , Xiao Xiyao , Zhang Yuwei , Zheng Yinhe , Wen Jiaxin , Zhao Jialu , Huang Minlie 
Published: May 2023

IntroductionThe growing demand for mental health support has highlighted the importance of conversational agents as human supporters worldwide and in China. These agents could increase availability and reduce the relative costs of mental health support. The provided support can be divided into two main types: cognitive and emotional. Existing work on this topic mainly focuses on constructing agents that adopt Cognitive Behavioral Therapy (CBT) principles. Such agents operate based on pre-defined templates and exercises to provide cognitive support. However, research on emotional support using such agents is limited. In addition, most of the constructed agents operate in English, highlighting the importance of conducting such studies in China. To this end, we introduce Emohaa, a conversational agent that provides cognitive support through CBT-Bot exercises and guided conversations. It also emotionally supports users through ES-Bot, enabling them to vent their emotional problems. In this study, we analyze the effectiveness of Emohaa in reducing symptoms of mental distress.Methods and ResultsFollowing the RCT design, the current study randomly assigned participants into three groups: Emohaa (CBT-Bot), Emohaa (Full), and control. With both Intention-To-Treat (N=247) and PerProtocol (N=134) analyses, the results demonstrated that compared to the control group, participants who used two types of Emohaa experienced considerably more significant improvements in symptoms of mental distress, including depression (F[2,244]=6.26, p=0.002), negative affect (F[2,244]=6.09, p=0.003), and insomnia (F[2,244]=3.69, p=0.026).DiscussionBased on the obtained results and participants’ satisfaction with the platform, we concluded that Emohaa is a practical and effective tool for reducing mental distress.
Predicting 18F-FDG SUVs of metastatic pulmonary nodes from CT images in patients with differentiated thyroid cancer by using a convolutional neural network
Authors: Ju Nianting , Nie Liangbing , Wang Yang , Hou Liying , Li Chengfan , Ding Xuehai , Luo Quanyong , Shen Chentian 
Published: May 2023

PurposeThe aim of this study was to predict standard uptake values (SUVs) from computed tomography (CT) images of patients with lung metastases from differentiated thyroid cancer (DTC-LM).MethodsWe proposed a novel SUVs prediction model using 18-layer Residual Network for generating SUVmax, SUVmean, SUVmin of metastatic pulmonary nodes from CT images of patients with DTC-LM. Nuclear medicine specialists outlined the metastatic pulmonary as primary set. The best model parameters were obtained after five-fold cross-validation on the training and validation set, further evaluated in independent test set. Mean absolute error (MAE), mean squared error (MSE), and mean relative error (MRE) were used to assess the performance of regression task. Specificity, sensitivity, F1 score, positive predictive value, negative predictive value and accuracy were used for classification task. The correlation between predicted and actual SUVs was analyzed.ResultsA total of 3407 nodes from 74 patients with DTC-LM were collected in this study. On the independent test set, the average MAE, MSE and MRE was 0.3843, 1.0133, 0.3491 respectively, and the accuracy was 88.26%. Our proposed model achieved high metric scores (MAE=0.3843, MSE=1.0113, MRE=34.91%) compared with other backbones. The predicted SUVmax (R2 = 0.8987), SUVmean (R2 = 0.8346), SUVmin (R2 = 0.7373) were all significantly correlated with actual SUVs.ConclusionThe novel approach proposed in this study provides new ideas for the application of predicting SUVs for metastatic pulmonary nodes in DTC patients.
Diabetes as a risk factor of death in hospitalized COVID-19 patients – an analysis of a National Hospitalization Database from Poland, 2020
Authors: Kania Michal , Koń Beata , Kamiński Konrad , Hohendorff Jerzy , Witek Przemysław , Klupa Tomasz , Malecki Maciej T. 
Published: May 2023

IntroductionDiabetes is one of the comorbidities associated with poor prognosis in hospitalized COVID-19 patients. In this nationwide retrospective study, we evaluated the risk of in-hospital death attributed to diabetes.MethodsWe analyzed data from discharge reports of patients hospitalized with COVID-19 in 2020 as submitted to the Polish National Health Fund. Several multivariate logistic regression models were used. In each model, in-hospital death was estimated with explanatory variables. Models were built either on the whole cohorts or cohorts matched with propensity score matching (PSM). The models examined either the main effects of diabetes itself or the interaction of diabetes with other variables.ResultsWe included 174,621 patients with COVID-19 who were hospitalized in the year 2020. Among them, there were 40,168 diabetic patients (DPs), and the proportion of DPs in this group was higher than in the general population (23.0% vs. 9.5%, p&lt;0.001). In this group of COVID-19 hospitalizations, 17,438 in-hospital deaths were recorded, and the mortality was higher among DPs than non-diabetics (16.3% vs. 8.1%, p&lt;0.001). Multivariate logistic regressions showed that diabetes was a risk factor of death, regardless of sex and age. In the main effect analysis, odds of in-hospital death were higher by 28.3% for DPs than for non-diabetic patients. Similarly, PSM analysis including 101,578 patients, of whom 19,050 had diabetes, showed that the risk of death was higher in DPs regardless of sex with odds higher by 34.9%. The impact of diabetes differed among age groups and was the highest for patients aged 60-69.ConclusionsThis nationwide study confirmed that diabetes was an independent risk factor of in-hospital death in the course of COVID-19 infection. However, the relative risk differed across the age groups.
Cost-effectiveness analysis of serplulimab plus chemotherapy in the first-line treatment for PD-L1-positive esophageal squamous cell carcinoma in China
Authors: Liu Shixian , Jiang Nana , Dou Lei , Li Shunping 
Published: May 2023

ObjectiveThe ASTRUM-007 trial (NCT03958890) demonstrated that serplulimab plus chemotherapy administered every 2-week significantly improved progression-free and overall survival in patients with previously untreated, programmed death-ligand 1 (PD-L1) positive advanced esophageal squamous-cell carcinoma (ESCC). This study was aimed to investigate the cost-effectiveness of serplulimab plus chemotherapy in the first-line treatment of PD-L1-positive advanced ESCC.MethodsA partitioned survival model with a 2-week cycle and a 10-year time horizon was constructed from the Chinese healthcare system perspective. The survival data, direct medical costs and utilities were derived from the ASTRUM-007 trial, YAOZHI database and published sources. Total costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated. Scenario, one-way and probabilistic sensitivity analyses were performed to assess the uncertainty around model parameters.ResultsCompared with chemotherapy, serplulimab plus chemotherapy provided additional 0.27 QALYs with an incremental cost of $33,460.86, which had an ICER of $124,483.07 per QALY. The subgroup analyses revealed that the ICERs of serplulimab plus chemotherapy were $134,637.42 and $105,589.71 in advanced ESCC patients with 1 ≤ CPS &lt; 10 and CPS ≥ 10, respectively. The price of serplulimab, patient weight, utility values and discount rate were the most influential parameters on base-case results. At a willingness-to-pay threshold of three times per capita GDP ($40,587.59) in 2022, the probability of serplulimab plus chemotherapy being cost-effective was 0% compared with chemotherapy. When the price of serplulimab decreased by 70%, the probabilities of serplulimab plus chemotherapy being cost-effective were 81.42%, 67.74% and 96.75% in advanced ESCC patients with PD-L1-positive, PD-L1 1≤CPS&lt;10 and CPS≥10, respectively.ConclusionSerplulimab plus chemotherapy in the first-line treatment for PD-L1-positive advanced ESCC might not be cost-effective in China.
Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics
Authors: Liu Jianmo , Wu Yifan , Jia Weijie , Han Mengqi , Chen Yongsen , Li Jingyi , Wu Bin , Yin Shujuan , Zhang Xiaolin , Chen Jibiao , Yu Pengfei , Luo Haowen , Tu Jianglong , Zhou Fan , Cheng Xuexin , Yi Yingping 
Published: May 2023

PurposeThis study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS).MethodsThe MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge. Randomized splitting was used to divide the data into training and validation sets using a ratio of 7:3. Two radiologists used the 3D-slicer software to label the lesions on brain diffusion-weighted (DWI) MRI sequences. Radiomics features were extracted from the annotated images using the pyradiomics software package, and the features were filtered using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Four machine learning algorithms, logistic regression (LR), Support Vector Classification (SVC), LightGBM, and Random forest (RF), were used to construct a recurrence prediction model. For each algorithm, three models were constructed based on the MRI radiomics features, clinical features, and combined MRI radiomics and clinical features. The sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to compare the predictive efficacy of the models.ResultsTwenty features were selected from 1,037 radiomics features extracted from DWI images. The LightGBM model based on data with three different features achieved the best prediction accuracy from all 4 models in the validation set. The LightGBM model based solely on radiomics features achieved a sensitivity, specificity, and AUC of 0.65, 0.671, and 0.647, respectively, and the model based on clinical data achieved a sensitivity, specificity, and AUC of 0.7, 0.799, 0.735, respectively. The sensitivity, specificity, and AUC of the LightGBM model base on both radiomics and clinical features achieved the best performance with a sensitivity, specificity, and AUC of 0.85, 0.805, 0.789, respectively.ConclusionThe ischemic stroke recurrence prediction model based on LightGBM achieved the best prediction of recurrence within 1 year following an AIS. The combination of MRI radiomics features and clinical data improved the prediction performance of the model.
Levetiracetam attenuates diabetes-associated cognitive impairment and microglia polarization by suppressing neuroinflammation
Authors: Zhang Yun-yun , Wang Lu , Guo Hua , Han Ting-ting , Chang Yan-hua , Cui Xiao-chuan 
Published: May 2023

Introduction: Cognitive impairment is a common complication and comorbidity of diabetes. However, the underlying mechanisms of diabetes-associated cognitive dysfunction are currently unclear. M1 microglia secretes pro-inflammatory factors and can be marked by CD16, iNOS, Iba1 and TNF-ɑ. The decline of M2 microglia in the diabetic rats indicates that high glucose promotes the differentiation of microglia into the M1 type to trigger neuroinflammatory responses. Moreover, there is a lack of strong evidence for treatments of diabetes-associated cognitive impairment in addition to controlling blood glucose.Methods: Diabetic rats were established by intraperitoneal injection of one dose of streptozotocin (60 mg/kg). Polarization transitions of microglia were induced by high glucose treatment in BV2 cells. Levetiracetam was orally administered to rats 72 h after streptozotocin injection for 12 weeks.Results: In STZ-induced diabetic rats, the results demonstrated that levetiracetam improved rat cognitive function (Morris water maze test) and hippocampus morphology (Hematoxylin-eosin staining), and the effect was more evident in the high-dose levetiracetam group. Microglia activation in the hippocampus was inhibited by levetiracetam treatment for 12 weeks. Serum levels of TNF-α, IL-1β, and IL-6 were reduced in the LEV-L and LEV-H groups, and IL-1β level was obviously reduced in the LEV-H group. In vitro, we found that levetiracetam 50 µM attenuated high-glucose induced microglial polarization by increasing IL-10 level and decreasing IL-1β and TNF-α levels. Moreover, levetiracetam 50 µM increased and decreased the proportion of CD206+/Iba1+ and iNOS+/Iba1+cells, respectively. Western blot analysis illustrated that LEV 50 µM downregulated the expression of MyD88 and TRAF6, and phosphorylation of TAK1, JNK, p38, and NF-κB p65. The effect of levetiracetam on the anti-polarization and expression of p-JNK and p-NF-κB p65 were partly reversed by anisomycin (p38 and JNK activators).Discussion: Together, our data suggest that levetiracetam attenuates streptozotocin-induced cognitive impairment by suppressing microglia activation. The in vitro findings also indicate that the levetiracetam inhibited the polarization of microglia via the JNK/MAPK/NF-κB signaling pathway.