bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estrogen Deficiency Induces Mitochondrial Damage Prior to Emergence of Cognitive Deficits in a Postmenopausal Mouse Model
Authors: Zhao Wei , Hou Yue , Song Xinxin , Wang Lei , Zhang Fangfang , Zhang Hanting , Yu Haiyang , Zhou Yanmeng 
Published: July 2021

Background: Estrogen deficiency contributes to the development of Alzheimer’s disease (AD) in menopausal women. In the current study, we examined the impact of estrogen deficiency on mitochondrial function and cognition using a postmenopausal mouse model.Methods: Bilateral ovariectomy was conducted in adult females C57BL/6J. Cognitive function was examined using the Morris water maze (MWM) test at 2 weeks, 1, 2, and 3 months after ovariectomy. Neurodegeneration was assessed using an immunofluorescence assay of microtubule-associated protein 2 (MAP2) in the hippocampus and immunoblotting against postsynaptic density-95 (PSD95). Mitochondrial function in the hippocampus was assessed using immunoblotting for NDUFB8, SDHB, UQCRC2, MTCO1, and ATP5A1. Mitochondrial biogenesis was examined using immunoblotting for PGC-1α, NRF1, and mtTFA. Mitochondrion fission was assessed with immunoblotting for Drp1, whereas mitochondrion fusion was analyzed with immunoblotting for OPA1 and Mfn2. Mitophagy was examined with immunoblotting for PINK1 and LC3B. Mice receiving sham surgery were used as controls.Results: Ovariectomy resulted in significant learning and memory deficits in the MWM test at 3 months, but not at any earlier time points. At 2 weeks after ovariectomy, levels of Drp1 phosphorylated at Ser637 decreased in the hippocampus. At 1 month after ovariectomy, hippocampal levels of NDUFB8, SDHB, PGC-1α, mtTFA, OPA1, and Mfn2 were significantly reduced. At 2 months after ovariectomy, hippocampal levels of MAP2, PSD95, MTCO1, NRF1, and Pink1 were also reduced. At 3 months, levels of LC3B-II were reduced.Conclusions: The cognitive decline associated with estrogen deficiency is preceded by mitochondrial dysfunction, abnormal mitochondrial biogenesis, irregular mitochondrial dynamics, and decreased mitophagy. Thus, mitochondrial damage may contribute to cognitive impairment associated with estrogen deficiency.
A Data-Driven Investigation on Surface Electromyography Based Clinical Assessment in Chronic Stroke
Authors: Ye Fuqiang , Yang Bibo , Nam Chingyi , Xie Yunong , Chen Fei , Hu Xiaoling 
Published: July 2021

Background:Surface electromyography (sEMG) based robot-assisted rehabilitation systems have been adopted for chronic stroke survivors to regain upper limb motor function. However, the evaluation of rehabilitation effects during robot-assisted intervention relies on traditional manual assessments. This study aimed to develop a novel sEMG data-driven model for automated assessment.Method:A data-driven model based on a three-layer backpropagation neural network (BPNN) was constructed to map sEMG data to two widely used clinical scales, i.e., the Fugl–Meyer Assessment (FMA) and the Modified Ashworth Scale (MAS). Twenty-nine stroke participants were recruited in a 20-session sEMG-driven robot-assisted upper limb rehabilitation, which consisted of hand reaching and withdrawing tasks. The sEMG signals from four muscles in the paretic upper limbs, i.e., biceps brachii (BIC), triceps brachii (TRI), flexor digitorum (FD), and extensor digitorum (ED), were recorded before and after the intervention. Meanwhile, the corresponding clinical scales of FMA and MAS were measured manually by a blinded assessor. The sEMG features including Mean Absolute Value (MAV), Zero Crossing (ZC), Slope Sign Change (SSC), Root Mean Square (RMS), and Wavelength (WL) were adopted as the inputs to the data-driven model. The mapped clinical scores from the data-driven model were compared with the manual scores by Pearson correlation.Results:The BPNN, with 15 nodes in the hidden layer and sEMG features, i.e., MAV, ZC, SSC, and RMS, as the inputs to the model, was established to achieve the best mapping performance with significant correlations (r&gt; 0.9,P&lt; 0.001), according to the FMA. Significant correlations were also obtained between the mapped and manual FMA subscores, i.e., FMA-wrist/hand and FMA-shoulder/elbow, before and after the intervention (r&gt; 0.9,P&lt; 0.001). Significant correlations (P&lt; 0.001) between the mapped and manual scores of MASs were achieved, with the correlation coefficientsr= 0.91 at the fingers, 0.88 at the wrist, and 0.91 at the elbow after the intervention.Conclusion:An sEMG data-driven BPNN model was successfully developed. It could evaluate upper limb motor functions in chronic stroke and have potential application in automated assessment in post-stroke rehabilitation, once validated with large sample sizes.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT02117089.
Factors Associated With Response to Pilot Home-Based Light Therapy for Fatigue Following Traumatic Brain Injury and Stroke
Authors: Connolly Laura J. , Rajaratnam Shantha M. W. , Spitz Gershon , Lockley Steven W. , Ponsford Jennie L. 
Published: July 2021

Background:Fatigue and sleep disturbance are common and debilitating problems after brain injury. Light therapy shows promise as a potential treatment. We conducted a trial of in-home light therapy to alleviate fatigue and sleep disturbance. The aim of the current study was to identify factors moderating treatment response.Methods:Participants were 24 individuals with traumatic brain injury (TBI) (n= 19) or stroke (n= 5) reporting clinically significant fatigue. Outcomes included fatigue on Brief Fatigue Inventory (primary outcome), sleep disturbance on Pittsburgh Sleep Quality Index, reaction time (RT) on Psychomotor Vigilance Task and time spent in productive activity. Interactions of demographic and clinical variables with these outcomes were examined in linear mixed-model analyses.Results:Whilst there were no variables found to be significantly associated with change in our primary outcome of fatigue, some variables revealed medium or large effect sizes, including chronotype, eye color, injury severity as measured by PTA, and baseline depressive symptoms. Chronotype significantly moderated sleep quality, with evening chronotype being associated with greater improvement during treatment. Injury type significantly predicted mean RT, with stroke participants exhibiting greater post-treatment reduction than TBI. Age significantly predicted productive activity during Treatment, with younger participants showing stronger Treatment effect.Conclusion:Light therapy may have a greater impact on sleep in younger individuals and those with an evening chronotype. Older individuals may need higher treatment dose to achieve benefit.Clinical Trial Registration:www.anzctr.org.au, identifier: ACTRN12617000866303.
Computerized Dual-Task Testing of Gait Visuomotor and Cognitive Functions in Parkinson’s Disease: Test-Retest Reliability and Validity
Authors: Bhatt Mayank , Mahana Bhuvan , Ko Ji Hyun , Kolesar Tiffany A. , Kanitkar Anuprita , Szturm Tony 
Published: July 2021

BackgroundMobility and cognitive impairments in Parkinson’s disease (PD) often coexist and are prognostic of adverse health events. Consequently, assessment and training that simultaneously address both gait function and cognition are important to consider in rehabilitation and promotion of healthy aging. For this purpose, a computer game-based rehabilitation treadmill platform (GRP) was developed for dual-task (DT) assessment and training.ObjectiveThe first objective was to establish the test-retest reliability of the GRP assessment protocol for DT gait, visuomotor and executive cognitive function in PD patients. The second objective was to examine the effect of task condition [single task (ST) vs. DT] and disease severity (stage 2 vs. stage 3) on gait, visuomotor and cognitive function.MethodsThirty individuals aged 55 to 70 years, diagnosed with PD; 15 each at Hoehn and Yahr scale stage 2 (PD-2) and 3 (PD-3) performed a series of computerized visuomotor and cognitive game tasks while sitting (ST) and during treadmill walking (DT). A treadmill instrumented with a pressure mat was used to record center of foot pressure and compute the average and coefficient of variation (COV) of step time, step length, and drift during 1-min, speed-controlled intervals. Visuomotor and cognitive game performance measures were quantified using custom software. Testing was conducted on two occasions, 1 week apart.ResultsWith few exceptions, the assessment protocol showed moderate to high intraclass correlation coefficient (ICC) values under both ST and DT conditions for the spatio-temporal gait measures (average and COV), as well as the visuomotor tracking and cognitive game performance measures. A significant decline in gait, visuomotor, and cognitive game performance measures was observed during DT compared to ST conditions, and in the PD-3 compared to PD-2 groups.ConclusionThe high to moderate ICC values along with the lack of systematic errors in the measures indicate that this tool has the ability to repeatedly record reliable DT interference (DTI) effects over time. The use of interactive digital media provides a flexible method to produce and evaluate DTI for a wide range of executive cognitive activities. This also proves to be a sensitive tool for tracking disease progression.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier NCT03232996.
How to Arrange Follow-Up Time-Intervals for Longitudinal Brain MRI Studies in Neurodegenerative Diseases
Authors: Müller Hans-Peter , Behler Anna , Landwehrmeyer G. Bernhard , Huppertz Hans-Jürgen , Kassubek Jan 
Published: July 2021

BackgroundLongitudinal brain MRI monitoring in neurodegeneration potentially provides substantial insights into the temporal dynamics of the underlying biological process, but is time- and cost-intensive and may be a burden to patients with disabling neurological diseases. Thus, the conceptualization of follow-up time-intervals in longitudinal MRI studies is an essential challenge and substantial for the results. The objective of this work is to discuss the association of time-intervals and the results of longitudinal trends in the frequently used design of one baseline and two follow-up scans.MethodsDifferent analytical approaches for calculating the linear trend of longitudinal parameters were studied in simulations including their performance of dealing with outliers; these simulations were based on the longitudinal striatum atrophy in MRI data of Huntington’s disease patients, detected by atlas-based volumetry (ABV).ResultsFor the design of one baseline and two follow-up visits, the simulations with outliers revealed optimum results for identical time-intervals between baseline and follow-up scans. However, identical time-intervals between the three acquisitions lead to the paradox that, depending on the fit method, the first follow-up scan results do not influence the final results of a linear trend analysis.ConclusionsThis theoretical study analyses how the design of longitudinal imaging studies with one baseline and two follow-up visits influences the results. Suggestions for the analysis of longitudinal trends are provided.
Progesterone Receptor Expression in Meningiomas: Pathological and Prognostic Implications
Authors: Maiuri Francesco , Mariniello Giuseppe , de Divitiis Oreste , Esposito Felice , Guadagno Elia , Teodonno Giuseppe , Barbato Marcello , Del Basso De Caro Marialaura 
Published: July 2021

BackgroundThe progesterone receptor (PR) is variably expressed in most meningiomas and was found to have prognostic significance. However, the correlation with patient age, tumor location, time to recurrence, and pattern of regrowth has scarcely been discussed.MethodsA surgical series of 300 patients with meningiomas is reviewed. The PR expression was classified as: 0. absent; 1. low (&lt;15%); 2. moderately low (16–50%); 3. moderately high (51–79%); 4. high (≥80%). The PR values were correlated with the patient age and sex, meningioma location, WHO grade, Ki-67 MIB1, recurrence rate, pattern of recurrence (local-peripheral versus multicentric diffuse), and time to recurrence.ResultsThe PR expression has shown lower rate of high expression in the elderly group (p = 0.032) and no sex difference (including premenopausal versus postmenopausal women), higher expression in medial skull base and spinal versus other locations (p = 0.0036), inverse correlation with WHO grade and Ki67-MIB1 (p &lt; 0.0001). Meningiomas which recurred showed at initial surgery higher rates of low or moderately low PR expression than the non-recurrent ones (p = 0.0004), whereas the pattern of regrowth was not significant. Higher rates of PR values ≥80% were found in cases with time to recurrence &gt;5 years (p = 0.036).ConclusionThe higher PR expression in medial skull base meningiomas, the significant correlation with the time to recurrence, the lack of difference of PR expression between premenopausal and postmenopausal women and between local-peripheral versus multicentric-diffuse recurrences are the most relevant unreported findings of this study. The rate of PR expression must be included in the routine pathological diagnosis of meningiomas because of its prognostic significance.
Support Vector Machine Model Predicts Dose for Organs at Risk in High-Dose Rate Brachytherapy of Cervical Cancer
Authors: Zhou Ping , Li Xiaojie , Zhou Hao , Fu Xiao , Liu Bo , Zhang Yu , Lin Sheng , Pang Haowen 
Published: July 2021

IntroductionThis study aimed to establish a support vector machine (SVM) model to predict the dose for organs at risk (OARs) in intracavitary brachytherapy planning for cervical cancer with tandem and ovoid treatments.MethodsFifty patients with loco-regionally advanced cervical cancer treated with 200 CT-based tandem and ovoid brachytherapy plans were included. The brachytherapy plans were randomly divided into the training (N = 160) and verification groups (N = 40). The bladder, rectum, sigmoid colon, and small intestine were divided into sub-OARs. The SVM model was established using MATLAB software based on the sub-OAR volume to predict the bladder, rectum, sigmoid colon, and small intestine D2cm3. Model performance was quantified by mean squared error (MSE) and δ (δ=|D2cm3/Dprescription(actual)−D2cm3/Dprescription(predicted)|). The goodness of fit of the model was quantified by the coefficient of determination (R2). The accuracy and validity of the SVM model were verified using the validation group.ResultsThe D2cm3 value of the bladder, rectum, sigmoid colon, and small intestine correlated with the volume of the corresponding sub-OARs in the training group. The mean squared error (MSE) in the SVM model training group was &lt;0.05; the R2 of each OAR was &gt;0.9. There was no significant difference between the D2cm3 -predicted and actual values in the validation group (all P &gt; 0.05): bladder δ = 0.024 ± 0.022, rectum δ = 0.026 ± 0.014, sigmoid colon δ = 0.035 ± 0.023, and small intestine δ = 0.032 ± 0.025.ConclusionThe SVM model established in this study can effectively predict the D2cm3 for the bladder, rectum, sigmoid colon, and small intestine in cervical cancer brachytherapy.
Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT
Authors: He Kan , Liu Xiaoming , Shahzad Rahil , Reimer Robert , Thiele Frank , Niehoff Julius , Wybranski Christian , Bunck Alexander C. , Zhang Huimao , Perkuhn Michael 
Published: July 2021

ObjectiveLiver cancer is one of the most commonly diagnosed cancer, and energy-based tumor ablation is a widely accepted treatment. Automatic and robust segmentation of liver tumors and ablation zones would facilitate the evaluation of treatment success. The purpose of this study was to develop and evaluate an automatic deep learning based method for (1) segmentation of liver and liver tumors in both arterial and portal venous phase for pre-treatment CT, and (2) segmentation of liver and ablation zones in both arterial and portal venous phase for after ablation treatment.Materials and Methods252 CT images from 63 patients undergoing liver tumor ablation at a large University Hospital were retrospectively included; each patient had pre-treatment and post-treatment multi-phase CT images. 3D voxel-wise manual segmentation of the liver, tumors and ablation region by the radiologist provided reference standard. Deep learning models for liver and lesion segmentation were initially trained on the public Liver Tumor Segmentation Challenge (LiTS) dataset to obtain base models. Then, transfer learning was applied to adapt the base models on the clinical training-set, to obtain tumor and ablation segmentation models both for arterial and portal venous phase images. For modeling, 2D residual-attention Unet (RA-Unet) was employed for liver segmentation and a multi-scale patch-based 3D RA-Unet for tumor and ablation segmentation.ResultsOn the independent test-set, the proposed method achieved a dice similarity coefficient (DSC) of 0.96 and 0.95 for liver segmentation on arterial and portal venous phase, respectively. For liver tumors, the model on arterial phase achieved detection sensitivity of 71%, DSC of 0.64, and on portal venous phase sensitivity of 82%, DSC of 0.73. For liver tumors &gt;0.5cm3 performance improved to sensitivity 79%, DSC 0.65 on arterial phase and, sensitivity 86%, DSC 0.72 on portal venous phase. For ablation zone, the model on arterial phase achieved detection sensitivity of 90%, DSC of 0.83, and on portal venous phase sensitivity of 90%, DSC of 0.89.ConclusionThe proposed deep learning approach can provide automated segmentation of liver tumors and ablation zones on multi-phase (arterial and portal venous) and multi-time-point (before and after treatment) CT enabling quantitative evaluation of treatment success.
Reversing Epigenetic Gene Silencing to Overcome Immune Evasion in CNS Malignancies
Authors: Ratnam Nivedita M. , Sonnemann Heather M. , Frederico Stephen C. , Chen Huanwen , Hutchinson Marsha-Kay N. D. , Dowdy Tyrone , Reid Caitlin M. , Jung Jinkyu , Zhang Wei , Song Hua , Zhang Meili , Davis Dionne , Larion Mioara , Giles Amber J. , Gilbert Mark R. 
Published: July 2021

Glioblastoma (GBM) is an aggressive brain malignancy with a dismal prognosis. With emerging evidence to disprove brain-immune privilege, there has been much interest in examining immunotherapy strategies to treat central nervous system (CNS) cancers. Unfortunately, the limited success of clinical studies investigating immunotherapy regimens, has led to questions about the suitability of immunotherapy for these cancers. Inadequate inherent populations of tumor infiltrating lymphocytes (TILs) and limited trafficking of systemic, circulating T cells into the CNS likely contribute to the poor response to immunotherapy. This paucity of TILs is in concert with the finding of epigenetic silencing of genes that promote immune cell movement (chemotaxis) to the tumor. In this study we evaluated the ability of GSK126, a blood-brain barrier (BBB) permeable small molecule inhibitor of EZH2, to reverse GBM immune evasion by epigenetic suppression of T cell chemotaxis. We also evaluated the in vivo efficacy of this drug in combination with anti-PD-1 treatment on tumor growth, survival and T cell infiltration in syngeneic mouse models. GSK126 reversed H3K27me3 in murine and human GBM cell lines. When combined with anti-PD-1 treatment, a significant increase in activated T cell infiltration into the tumor was observed. This resulted in decreased tumor growth and enhanced survival both in sub-cutaneous and intracranial tumors of immunocompetent, syngeneic murine models of GBM. Additionally, a significant increase in CXCR3+ T cells was also seen in the draining lymph nodes, suggesting their readiness to migrate to the tumor. Closer examination of the mechanism of action of GSK126 revealed its ability to promote the expression of IFN-γ driven chemokines CXCL9 and CXCL10 from the tumor cells, that work to traffic T cells without directly affecting T maturation and/or proliferation. The loss of survival benefit either with single agent or combination in immunocompromised SCID mice, suggest that the therapeutic efficacy of GSK126 in GBM is primarily driven by lymphocytes. Taken together, our data suggests that in glioblastoma, epigenetic modulation using GSK126 could improve current immunotherapy strategies by reversing the epigenetic changes that enable immune cell evasion leading to enhanced immune cell trafficking to the tumor.
Total Flavones of Abelmoschus manihot Ameliorates Podocyte Pyroptosis and Injury in High Glucose Conditions by Targeting METTL3-Dependent m6A Modification-Mediated NLRP3-Inflammasome Activation and PTEN/PI3K/Akt Signaling
Authors: Liu Bu-Hui , Tu Yue , Ni Guang-Xia , Yan Jin , Yue Liang , Li Zi-Lin , Wu Jing-Jing , Cao Yu-Ting , Wan Zi-Yue , Sun Wei , Wan Yi-Gang 
Published: July 2021

Background: The total flavones of Abelmoschus manihot (TFA), a compound that is extracted from Abelmoschus manihot, has been widely used in China to reduce podocyte injury in diabetic kidney disease (DKD). However, the mechanisms underlying the therapeutic action of this compound have yet to be elucidated. Podocyte pyroptosis is characterized by activation of the NLRP3 inflammasome and plays an important role in inflammation-mediated diabetic kidneys. Regulation of the PTEN/PI3K/Akt pathway is an effective strategy for improving podocyte damage in DKD. Previous research has also shown that N6-methyladenosine (m6A) modification is involved in DKD and that m6A-modified PTEN regulates the PI3K/Akt pathway. In this study, we investigated whether TFA alleviates podocyte pyroptosis and injury by targeting m6A modification-mediated NLRP3-inflammasome activation and PTEN/PI3K/Akt signaling.Methods: We used MPC-5 cells under high glucose (HG) conditions to investigate the key molecules that are involved in podocyte pyroptosis and injury, including activation of the NLRP3 inflammasome and the PTEN/PI3K/Akt pathway. We detected alterations in the levels of three methyltransferases that are involved in m6A modification. We also investigated changes in the levels of these key molecules in podocytes with the overexpression or knockdown of methyltransferase-like (METTL)3.Results: Analysis showed that TFA and MCC950 protected podocytes against HG-induced pyroptosis and injury by reducing the protein expression levels of gasdermin D, interleukin-1β, and interleukin-18, and by increasing the protein expression levels of nephrin, ZO-1, WT1 and podocalyxin. TFA and 740Y-P inhibited activation of the NLRP3 inflammasome via the PI3K/Akt pathway by inhibiting the protein levels of NIMA-related kinase7, NLRP3, ASC, and caspase-1, and by increasing the protein expression levels of p-PI3K and p-Akt. TFA improved pyroptosis and injury in HG-stimulated podocytes by regulating METTL3-dependent m6A modification.Conclusion: Collectively, our data indicated that TFA could ameliorate pyroptosis and injury in podocytes under HG conditions by adjusting METTL3-dependent m6A modification and regulating NLRP3-inflammasome activation and PTEN/PI3K/Akt signaling. This study provides a better understanding of how TFA can protect podocytes in DKD.