bluuebunny/crossref_metadata_2025_split huggingface dataset:
A mutant wfs1 zebrafish model of Wolfram syndrome manifesting visual dysfunction and developmental delay
Authors: Cairns G. , Burté F. , Price R. , O’Connor E. , Toms M. , Mishra R. , Moosajee M. , Pyle A. , Sayer J. A. , Yu-Wai-Man P. 
Published: October 2021

AbstractWolfram syndrome (WS) is an ultra-rare progressive neurodegenerative disorder defined by early-onset diabetes mellitus and optic atrophy. The majority of patients harbour recessive mutations in the WFS1 gene, which encodes for Wolframin, a transmembrane endoplasmic reticulum protein. There is limited availability of human ocular and brain tissues, and there are few animal models for WS that replicate the neuropathology and clinical phenotype seen in this disorder. We, therefore, characterised two wfs1 zebrafish knockout models harbouring nonsense wfs1a and wfs1b mutations. Both homozygous mutant wfs1a−/− and wfs1b−/− embryos showed significant morphological abnormalities in early development. The wfs1b−/− zebrafish exhibited a more pronounced neurodegenerative phenotype with delayed neuronal development, progressive loss of retinal ganglion cells and clear evidence of visual dysfunction on functional testing. At 12 months of age, wfs1b−/− zebrafish had a significantly lower RGC density per 100 μm2 (mean ± standard deviation; 19 ± 1.7) compared with wild-type (WT) zebrafish (25 ± 2.3, p < 0.001). The optokinetic response for wfs1b−/− zebrafish was significantly reduced at 8 and 16 rpm testing speeds at both 4 and 12 months of age compared with WT zebrafish. An upregulation of the unfolded protein response was observed in mutant zebrafish indicative of increased endoplasmic reticulum stress. Mutant wfs1b−/− zebrafish exhibit some of the key features seen in patients with WS, providing a versatile and cost-effective in vivo model that can be used to further investigate the underlying pathophysiology of WS and potential therapeutic interventions.
Impaired placental mitophagy and oxidative stress are associated with dysregulated BNIP3 in preeclampsia
Authors: Zhou Xiaobo , Zhao Xue , Zhou Wei , Qi Hongbo , Zhang Hua , Han Ting-li , Baker Philip 
Published: October 2021

AbstractPreeclampsia (PE) is a severe multisystem pregnancy complication characterized by gestational hypertension and proteinuria. Bcl-2/adenovirus E1B 19-kDa interacting protein 3 (BNIP3) is a mediator of mitophagy and has been proven to be associated with PE, but the mechanism is not well understood. This study aimed to investigate the role of BNIP3 in PE. Placentae from preeclamptic and normal pregnancies were analyzed by western-blot and transmission electron microscopy to quantify the level of BNIP3 expression and observe the organelle morphologies. Trophoblast cells with knockdown BNIP3 were analyzed by western-blot, immunofluorescence, flow cytometry, migration and invasion assays. BNIP3 expression was suppressed in PE patients. Impaired autophagy and increased mitochondrial damage were observed in PE placentae when compared with normal placentae. Suppression of BNIP3 inhibited Beclin-1 expression and reduced the transformation of LC3-I to LC3-II. In the knockdown BNIP3 group, p62 was overexpressed, ROS accumulated and the apoptotic process was elevated under oxidative stress condition. The knockdown of BNIP3 reduced the colocalization of GFP-LC3 and mitochondria. The findings of this study suggest that dysregulated BNIP3 is associated with impaired mitophagy, oxidative stress, and apoptosis in PE. The study provides new insights into the role of BNIP3 in the pathophysiology of PE.
Association between baseline LH/FSH and live-birth rate after fresh-embryo transfer in polycystic ovary syndrome women
Authors: Su Nian-jun , Huang Cui-yu , Liu Jie , Kang De-ying , Wang Song-lu , Liao Liu-jun , Yang Jin-di , Zhang Xi-qian , Liu Feng-hua 
Published: October 2021

AbstractThis study aimed to retrospectively analyse the effect of the baseline luteinising hormone/follicle-stimulating hormone ratio (bLH/FSH) on the live-birth rate per fresh-embryo transfer cycle (LBR/ET) in infertile women with polycystic ovary syndrome (PCOS) who received a fresh-embryo transfer. A total of 424 patients with PCOS who underwent the first cycle of in vitro fertilisation (IVF)/intracytoplasmic sperm injection (ICSI) fresh-embryo transfer at our hospital was enrolled. Univariate and multivariate logistic regression analyses, along with curve fitting and a threshold effect analysis, were performed. Baseline LH/FSH levels were a significant (P < 0.05) independent risk factor affecting live birth. In the first IVF/ICSI antagonist treatment cycles, LBR/ET after fresh-embryo transfer was relatively flat, until bLH/FSH was 1.0; thereafter, it started to decrease by 17% for every 0.1-unit bLH/FSH increase. Considering the decline in LBR/ET, it is recommended that PCOS women with bLH/FSH > 1.0 carefully consider fresh-embryo transfer during their first IVF/ICSI.
Endoscopic injection sclerotherapy improves liver function compared with endoscopic variceal ligation
Authors: Hayashi Tsuguru , Watanabe Tatsuyuki , Shibata Michihiko , Kumei Shinsuke , Oe Shinji , Miyagawa Koichiro , Honma Yuichi , Harada Masaru 
Published: October 2021

AbstractLiver function is a most important prognostic factor in patients with liver cirrhosis. Also, portal hypertension is a fatal complication of liver cirrhosis and variceal treatment is indispensable. However, changes of liver functions after endoscopic variceal treatments are unknown. The aim of this study was to evaluate prognosis and liver functions after endoscopic injection sclerotherapy (EIS) and endoscopic variceal ligation (EVL). A total of liver cirrhotic 103 patients who underwent prophylactic EIS and EVL were enrolled. Overall survival rate was higher in EIS group than EVL group (p = 0.03). Multivariate analysis showed that EIS was a negative factor for death (HR: 0.46, 95% confidence interval: 0.24–0.88, p = 0.02). Liver functions were assessed by blood test taken at before and 3 months after treatment. In EIS group, albumin and prothrombin time improved (p < 0.01), leading to improvement of Child–Pugh score, ALBI score and MELD score (p < 0.05). However, these did not improve in EVL group. EIS was a significant factor related to the elevated value of albumin after treatment in linear regression analysis (estimated regression coefficient: 0.17, 95% confidence interval: 0.05–0.29, p = 0.005). These results revealed that EIS could improve liver functions and prognosis.
Human m6A-mRNA and lncRNA epitranscriptomic microarray reveal function of RNA methylation in hemoglobin H-constant spring disease
Authors: Ruan Heyun , Yang Fang , Deng Lingjie , Yang Dongmei , Zhang Xiaoli , Li Xueyu , Pang Lihong 
Published: October 2021

AbstractThe thalassemia of Hemoglobin H-Constant Spring disease (HbH-CS) is the most common type of Thalassemia in non-transfusion thalassemia. Interestingly, the clinical manifestations of the same genotype of thalassemia can be vastly different, likely due to epigenetic regulation. Here, we used microarray technology to reveal the epigenetic regulation of m6A in modifiable diseases and demonstrated a role of BCL2A1 in disease regulation. In this study, we revealed that methylating enzyme writers including METTL16, WTAP, CBLL1, RBM15B, and ZC3H13 displayed low expression and the demethylating enzyme ALKBH5, along with reader proteins including IGF2BP2 and YTHDF3 exhibited high expression. In addition, BCL2A1 was hypo-methylated and showed low expression. We also revealed that the BCL2A1 methylation level and IGF2BP2 expression were negatively correlated. Additionally, the mRNAs expression between ALKBH5 and IGF2BP2 were positively correlated. In HbH-CS, most genes were hypo-methylated. This included BCL2A1, which may play an important role in the process of red blood cell differentiation and development of HbH-CS. Moreover, the mRNA-M6A methylation status may be regulated by the demethylating enzyme ALKBH5 via IGF2BP2.
A systematic review and meta-analysis of acceptance- and mindfulness-based interventions for DSM-5 anxiety disorders
Authors: Haller Heidemarie , Breilmann Pascal , Schröter Marleen , Dobos Gustav , Cramer Holger 
Published: October 2021

AbstractThis meta-analysis systematically reviewed the evidence on standardized acceptance-/mindfulness-based interventions in DSM-5 anxiety disorders. Randomized controlled trials examining Acceptance and Commitment Therapy (ACT), Mindfulness-Based Cognitive Therapy (MBCT), and Mindfulness-Based Stress Reduction (MBSR) were searched via PubMed, Central, PsycInfo, and Scopus until June 2021. Standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for primary outcomes (anxiety) and secondary ones (depression and quality of life). Risk of bias was assessed using the Cochrane tool. We found 23 studies, mostly of unclear risk of bias, including 1815 adults with different DSM-5 anxiety disorders. ACT, MBCT and MBSR led to short-term effects on clinician- and patient-rated anxiety in addition to treatment as usual (TAU) versus TAU alone. In comparison to Cognitive Behavioral Therapy (CBT), ACT and MBCT showed comparable effects on both anxiety outcomes, while MBSR showed significantly lower effects. Analyses up to 6 and 12 months did not reveal significant differences compared to TAU or CBT. Effects on depression and quality of life showed similar trends. Statistical heterogeneity was moderate to considerable. Adverse events were reported insufficiently. The evidence suggests short-term anxiolytic effects of acceptance- and mindfulness-based interventions. Specific treatment effects exceeding those of placebo mechanisms remain unclear. Protocol registry: Registered at Prospero on November 3rd, 2017 (CRD42017076810).
Latent negative precipitation for the delineation of a zero-precipitation area in spatial interpolations
Authors: Lee Taesam , Shin Ju-young 
Published: October 2021

AbstractThe spatial interpolation of precipitation has been employed in a number of fields, including by spatially downscaling the Global Circulation Model (GCM) to a finer scale. Most precipitation events become more sporadic when the coverage area increases (i.e., a portion of the points experience zero precipitation). However, spatial interpolations of precipitation generally ignore these dry areas, and the interpolated grids are filled with certain precipitation amounts. Subsequently, no delineation of dry and wet regions can be made. Therefore, the current study suggested a novel approach to determine dry areas in spatial interpolations of precipitation events by assigning latent negative precipitation (LNP) to points with observed precipitation values of zero. The LNP-assigned points are then employed in a spatial interpolation. After that, the dry region can be determined using the negative region (i.e., points with zero precipitation). The magnitude of LNP can be defined by multiplying the precipitation values of neighboring stations by a tuning parameter. The LNP method and the tuning parameter are tested on weather stations covering South Korea. The results indicate that the proposed LNP method can be suitable for the spatial interpolation of precipitation events by delineating dry and wet regions. Additionally, the tuning parameter plays a special role in that it increases in value with longer precipitation durations and denser networks. A value of 0.5–1.5 can be suggested for the tuning parameter as a rule of thumb when high accuracy for final products of interpolated precipitation is not critical. For future studies, the LNP model derived herein can be tested over much larger areas, such as the United States, and the model can also be easily adopted for other variables with spatially sporadic values.
Morphodynamics facilitate cancer cells to navigate 3D extracellular matrix
Authors: Eddy Christopher Z. , Raposo Helena , Manchanda Aayushi , Wong Ryan , Li Fuxin , Sun Bo 
Published: October 2021

AbstractCell shape is linked to cell function. The significance of cell morphodynamics, namely the temporal fluctuation of cell shape, is much less understood. Here we study the morphodynamics of MDA-MB-231 cells in type I collagen extracellular matrix (ECM). We systematically vary ECM physical properties by tuning collagen concentrations, alignment, and gelation temperatures. We find that morphodynamics of 3D migrating cells are externally controlled by ECM mechanics and internally modulated by Rho/ROCK-signaling. We employ machine learning to classify cell shape into four different morphological phenotypes, each corresponding to a distinct migration mode. As a result, we map cell morphodynamics at mesoscale into the temporal evolution of morphological phenotypes. We characterize the mesoscale dynamics including occurrence probability, dwell time and transition matrix at varying ECM conditions, which demonstrate the complex phenotype landscape and optimal pathways for phenotype transitions. In light of the mesoscale dynamics, we show that 3D cancer cell motility is a hidden Markov process whereby the step size distributions of cell migration are coupled with simultaneous cell morphodynamics. Morphological phenotype transitions also facilitate cancer cells to navigate non-uniform ECM such as traversing the interface between matrices of two distinct microstructures. In conclusion, we demonstrate that 3D migrating cancer cells exhibit rich morphodynamics that is controlled by ECM mechanics, Rho/ROCK-signaling, and regulate cell motility. Our results pave the way to the functional understanding and mechanical programming of cell morphodynamics as a route to predict and control 3D cell motility.
An adapted dorsal skinfold model used for 4D intravital followed by whole-mount imaging to reveal endothelial cell–pericyte association
Authors: Seynhaeve Ann L. B. , ten Hagen Timo L. M. 
Published: October 2021

AbstractEndothelial cells and pericytes are highly dynamic vascular cells and several subtypes, based on their spatiotemporal dynamics or molecular expression, are believed to exist. The interaction between endothelial cells and pericytes is of importance in many aspects ranging from basic development to diseases like cancer. Identification of spatiotemporal dynamics is particularly interesting and methods to studies these are in demand. Here we describe the technical details of a method combining the benefits of high resolution intravital imaging and whole-mount histology. With intravital imaging using an adapted light weight dorsal skinfold chamber we identified blood flow patterns and spatiotemporal subtypes of endothelial cells and pericytes in a 4D (XYZ, spatial+T, time dimension) manner as representative examples for this model. Thereafter the tissue was extracted and stained as a whole-mount, by which the position and volumetric space of endothelial cells as well as pericytes were maintained, to identify molecular subtypes. Integration of the two imaging methods enabled 4D dissection of endothelial cell–pericyte association at the molecular level.
A deep learning model for gastric diffuse-type adenocarcinoma classification in whole slide images
Authors: Kanavati Fahdi , Tsuneki Masayuki 
Published: October 2021

AbstractGastric diffuse-type adenocarcinoma represents a disproportionately high percentage of cases of gastric cancers occurring in the young, and its relative incidence seems to be on the rise. Usually it affects the body of the stomach, and it presents shorter duration and worse prognosis compared with the differentiated (intestinal) type adenocarcinoma. The main difficulty encountered in the differential diagnosis of gastric adenocarcinomas occurs with the diffuse-type. As the cancer cells of diffuse-type adenocarcinoma are often single and inconspicuous in a background desmoplaia and inflammation, it can often be mistaken for a wide variety of non-neoplastic lesions including gastritis or reactive endothelial cells seen in granulation tissue. In this study we trained deep learning models to classify gastric diffuse-type adenocarcinoma from WSIs. We evaluated the models on five test sets obtained from distinct sources, achieving receiver operator curve (ROC) area under the curves (AUCs) in the range of 0.95–0.99. The highly promising results demonstrate the potential of AI-based computational pathology for aiding pathologists in their diagnostic workflow system.
Cross-cultural asymmetries in oculomotor interference elicited by gaze distractors belonging to Asian and White faces
Authors: Zhang Xinyuan , Dalmaso Mario , Castelli Luigi , Fu Shimin , Galfano Giovanni 
Published: October 2021

AbstractThe averted gaze of others triggers reflexive attentional orienting in the corresponding direction. This phenomenon can be modulated by many social factors. Here, we used an eye-tracking technique to investigate the role of ethnic membership in a cross-cultural oculomotor interference study. Chinese and Italian participants were required to perform a saccade whose direction might be either congruent or incongruent with the averted-gaze of task-irrelevant faces belonging to Asian and White individuals. The results showed that, for Chinese participants, White faces elicited a larger oculomotor interference than Asian faces. By contrast, Italian participants exhibited a similar oculomotor interference effect for both Asian and White faces. Hence, Chinese participants found it more difficult to suppress eye-gaze processing of White rather than Asian faces. The findings provide converging evidence that social attention can be modulated by social factors characterizing both the face stimulus and the participants. The data are discussed with reference to possible cross-cultural differences in perceived social status.
Convolutional neural network for classification of eight types of arrhythmia using 2D time–frequency feature map from standard 12-lead electrocardiogram
Authors: Jeong Da Un , Lim Ki Moo 
Published: October 2021

AbstractElectrocardiograms (ECGs) are widely used for diagnosing cardiac arrhythmia based on the deformation of signal shapes due to changes in various heart diseases. However, these abnormal signs may not be observed in some 12 ECG channels, depending on the location, the heart shape, and the type of cardiac arrhythmia. Therefore, it is necessary to closely and comprehensively observe ECG records acquired from 12 channel electrodes to diagnose cardiac arrhythmias accurately. In this study, we proposed a clustering algorithm that can classify persistent cardiac arrhythmia as well as episodic cardiac arrhythmias using the standard 12-lead ECG records and the 2D CNN model using the time–frequency feature maps to classify the eight types of arrhythmias and normal sinus rhythm. The standard 12-lead ECG records were provided by China Physiological Signal Challenge 2018 and consisted of 6877 patients. The proposed algorithm showed high performance in classifying persistent cardiac arrhythmias; however, its accuracy was somewhat low in classifying episodic arrhythmias. If our proposed model is trained and verified using more clinical data, we believe it can be used as an auxiliary device for diagnosing cardiac arrhythmias.
A study of preparing silver iodide nanocolloid by electrical spark discharge method and its properties
Authors: Tseng Kuo-Hsiung , Yeh Chu-Ti , Chung Meng-Yun , Lin Yur-Shan , Qui Ning 
Published: October 2021

AbstractThis study employed an electric discharge machine (EDM) and the Electrical Spark Discharge Method (ESDM) to prepare silver iodide nanocolloid (AgINC). Povidone–iodine (PVP-I) was dissolved in deionized water to create a dielectric fluid. Silver material was melted using the high temperature generated by an electric arc, and the peeled-off material was reacted with PVP-I to form AgI nanoparticles (AgINPs). Six discharge pulse wave parameter combinations (Ton–Toff) were employed, and the resultant particle size and suspension of the prepared samples were examined. The results revealed that AgINPs were successfully created using the ESDM. When Ton–Toff was set at 90–90 μs, the zeta potential of the AgINC was − 50.3 mV, indicating excellent suspension stability. The AgINC particle size was 16 nm, verifying that the parameters yielded AgINPs with the smallest particle size distribution and highest zeta potential. Ultraviolet–visible spectrum analyser was performed to analyse the samples, and the spectra indicated that the characteristic wavelength was 420 nm regardless of the Ton–Toff values. X-ray diffraction analysis determined that the AgINPs exhibited two crystal structures, namely β-AgI and Ag. Transmission electron microscopy was performed and revealed that the particles were irregularly shaped and that some of the larger particles had aggregated. The crystal structure was determined to be a mixture of Ag and β-AgI, with a lattice spacing of 0.235 nm and 0.229 nm, respectively. The lattice spacing of the Ag was 0.235 nm. X-ray diffraction analysis indicated that the prepared AgINC were composed of only Ag and I; no additional chemical elements were detected.
Estimation of current and post-treatment retinal function in chronic central serous chorioretinopathy using artificial intelligence
Authors: Pfau Maximilian , van Dijk Elon H. C. , van Rijssen Thomas J. , Schmitz-Valckenberg Steffen , Holz Frank G. , Fleckenstein Monika , Boon Camiel J. F. 
Published: October 2021

AbstractRefined understanding of the association of retinal microstructure with current and future (post-treatment) function in chronic central serous chorioretinopathy (cCSC) may help to identify patients that would benefit most from treatment. In this post-hoc analysis of data from the prospective, randomized PLACE trial (NCT01797861), we aimed to determine the accuracy of AI-based inference of retinal function from retinal morphology in cCSC. Longitudinal spectral-domain optical coherence tomography (SD-OCT) data from 57 eyes of 57 patients from baseline, week 6–8 and month 7–8 post-treatment were segmented using deep-learning software. Fundus-controlled perimetry data were aligned to the SD-OCT data to extract layer thickness and reflectivity values for each test point. Point-wise retinal sensitivity could be inferred with a (leave-one-out) cross-validated mean absolute error (MAE) [95% CI] of 2.93 dB [2.40–3.46] (scenario 1) using random forest regression. With addition of patient-specific baseline data (scenario 2), retinal sensitivity at remaining follow-up visits was estimated even more accurately with a MAE of 1.07 dB [1.06–1.08]. In scenario 3, month 7–8 post-treatment retinal sensitivity was predicted from baseline SD-OCT data with a MAE of 3.38 dB [2.82–3.94]. Our study shows that localized retinal sensitivity can be inferred from retinal structure in cCSC using machine-learning. Especially, prediction of month 7–8 post-treatment sensitivity with consideration of the treatment as explanatory variable constitutes an important step toward personalized treatment decisions in cCSC.