bluuebunny/crossref_metadata_2025_split huggingface dataset:
The η-secretase-derived APP fragment ηCTF is localized in Golgi, endosomes and extracellular vesicles and contributes to Aβ production
Authors: Afram Elissa , Lauritzen Inger , Bourgeois Alexandre , Manaa Wejdane El , Duplan Eric , Chami Mounia , Valverde Audrey , Bauer Charlotte , Pardossi-Piquard Raphaëlle , Checler Frederic 
Published: November 2022

Abstract
The processing of the amyloid precursor protein (APP) is one of the key events contributing to Alzheimer’s disease (AD) etiology. Canonical cleavages by β- and γ-secretases lead to Aβ production which accumulate in amyloid plaques. Recently, the matrix metalloprotease MT5-MMP, referred to as η-secretase, has been identified as a novel APP cleaving enzyme producing a transmembrane fragment, ηCTF that undergoes subsequent cleavages by α- and β-secretases yielding the Aηα and Aηβ peptides, respectively. The functions and contributions of ηCTF and its related fragments to AD pathology are poorly understood. In this study, we designed a novel immunological probe referred to as ηCTF-NTer antibody that specifically interacts with the N-terminal part of ηCTF targeting ηCTF, Aηα, Aηβ but not C99, C83 and Aβ. We examined the fate and localization of ηCTF fragment in various cell models and in mice. We found that overexpressed ηCTF undergoes degradation in the proteasomal and autophagic pathways and accumulates mainly in the Golgi and in endosomes. Moreover, we observed the presence of ηCTF in small extracellular vesicles (sEVs) purified from neuroblastoma cells or from mouse brains expressing ηCTF. Importantly, the expression of ηCTF in fibroblasts devoid on APP leads to Aβ production demonstrating its contribution to the amyloidogenic pathway. Finally, we observed an ηCTF-like immunoreactivity around amyloid plaques and an age-dependent accumulation of ηCTF in the triple-transgenic mouse AD model. Thus, our study suggests that the ηCTF fragment likely contributes to AD pathology by its exosomal spreading and involvement in Aβ production
Automatic Detection of Circulating Tumor Cells and Cancer Associated Fibroblasts using Deep Learning
Authors: Shen Cheng , Rawal Siddarth , Brown Rebecca , Zhou Haowen , Agarwal Ashutosh , Watson Mark , Cote Richard , Yang Changhuei 
Published: November 2022

Abstract
Circulating tumor cells (CTCs) and cancer-associated fibroblasts (CAFs) from whole blood are emerging as important biomarkers that potentially aid in cancer diagnosis and prognosis. The microfilter technology provides an efficient capture platform for them but is confounded by two challenges. First, uneven microfilter surfaces makes it hard for commercial scanners to obtain images with all cells in-focus. Second, current analysis is labor-intensive with long turnaround time and user-to-user variability. Here we addressed the first challenge through developing a customized imaging system and data pre-processing algorithms. Utilizing cultured cancer and CAF cells captured by microfilters, we showed that images from our custom system are 99.3% in-focus compared to 89.9% from a top-of-the-line commercial scanner. Then we developed a deep-learning-based method to automatically identify tumor cells serving to mimic CTC (mCTC) and CAFs from the uniformly in-focus images. Our deep learning method achieved precision and recall of 94% and 96% for mCTC detection, and 90% and 83% for CAF detection, significantly better than a conventional computer vision method, whose numbers are 92% and 79% for mCTC and 57% and 54% for CAF. Our custom imaging system combined with deep learning cell identification method represents a significant advance on CTC and CAF analysis.
Modular architecture and resilience of structural covariance networks in first-episode antipsychotic-naive psychoses
Authors: Lewis Madison , Santini Tales , Theis Nicholas , Muldoon Brendan , Dash Katherine , Rubin Jonathan , Keshavan Matcheri , Prasad Konasale 
Published: November 2022

Abstract
Structural covariance network (SCN) studies on first-episode antipsychotic-naïve psychosis (FEAP) have examined less granular parcellations on one morphometric feature reporting lower network resilience among other findings. We examined SCNs of volumes, cortical thickness, and surface area using the Human Connectome Project atlas-based parcellation of 358 regions from 79 FEAP and 68 controls to comprehensively characterize the networks using descriptive and perturbational network neuroscience approach. Using graph theoretic methods, we examined network integration, segregation, centrality, community structure, and hub distribution across small-worldness threshold range and correlated them with psychopathology severity. We used simulated nodal “attacks” (removal of nodes and all their edges) to investigate network resilience, and calculated DeltaCon similarity scores and contrasted the removed nodes to characterize the impact of simulated attacks. Compared to controls, FEAP SCN showed higher betweenness centrality (BC) and lower degree in all three morphometric features and disintegrated with fewer attacks with no change in global efficiency. SCNs showed higher similarity score at the first point of disintegration with ≈54% top-ranked BC nodes attacked. FEAP communities consisted of fewer prefrontal, auditory and visual regions. Lower BC, and higher clustering and degree were associated with greater positive and negative symptom severity. Negative symptoms required twice the changes in these metrics. Globally sparse but locally dense network with more higher-importance nodes in FEAP could result in higher communication cost compared to controls. FEAP network disintegration with fewer attacks suggests lower resilience without altering efficiency measure. Greater network disarray underlying negative symptom severity possibly explains the therapeutic challenge.
Comparison and Multivariate Analysis of Radiofrequency and Pulsed Radiofrequency in the Treatment of Postherpetic Neuralgia
Authors: Nie Huiyong , Wang Hui , Yan Shaoyao , Bu Gang , Wang Huan 
Published: November 2022

Abstract
Background: Postherpetic neuralgia(PHN) is the most common complication following herpes zoster. It presents as a persistent or paroxysmal stabbing or burning pain, usually beginning≥3 months after complete healing of the skin lesions. Radiofrequency(RF) and pulsed radiofrequency(PRF), as two minimally invasive interventional techniques, have been clinically validated in the treatment of PHN with good results. However, a comparative effect between the two has not been reported so far. The aim of this cohort study to Compare and multivariate analysis of RF and PRF in the treatment of PHN.
Methods: A total of 164 PHN patients who received RF or PRF from January 2020 to October 2021 were retrospectively analyzed. There were 68 cases in PRF group and 96 cases in RF group. The pain (visual analogue scale, VAS), quality of life (36-Item Short Form Health Survey, SF-36), sleep quality (Athens insomnia scale, AIS) and postoperative complications were evaluated and compared before and after surgery at 1W, 1M, 3M,6M and 12M. The factors that may affect the treatment effect were also analyzed.
Result: The VAS and SF-36 after surgery at 1W, 1M, 3M, 6M and 12M in PRF group and RF group were significantly improved compared with those before operation (P<0.01). VAS decreased more in PRF group than in RF group at 6M after operation (P<0.05).The improvement of mental health SF-36 after surgery at 1W, 3M, 6M and 12M in PRF group was better than that in RF group (P<0.05). The physical functioning of SF-36 in PRF group was significantly higher than that in RF group at 1W, 1M, 3M, 6M and 12M after operation(P<0.01). Social functioning of SF-36 in PRF group increased more after surgery at 3M, 6M and 12M, which was better than that in RF group (P<0.05). In terms of sleep quality, postoperative PRF group and RF group were significantly improved compared with preoperative ones (P<0.01), but there was no significant difference between the two groups. Logistic regression analysis showed that age, gender, preoperative VAS and complications were the possible factors affecting the postoperative outcome.
Conclusion：Both RF and PRF have significant therapeutic effects on PHN. PRF has greater advantages than RF in reducing postoperative pain and improving quality of life. Age, gender, preoperative pain and complications are the possible related factors affecting the efficacy of RF and PRF therapy for PHN.
Construction and Validation of Prognostic Signature Model Based on Metastatic Features for Colorectal Cancer
Authors: Zhao Zhixun , Chen Haipeng , yang Yanwei , Guan Xu , Jiang Zheng , Yang Ming , Liu Hengchang , Chen Tianli , Lv Jingfang , Zou Shuangmei , Liu Zheng , Wang Xishan 
Published: November 2022

Abstract
Background
Colorectal cancer (CRC) is a common malignant cancer with a poor prognosis. Liver metastasis is the dominant cause of death in CRC patients, and it often involves changes in various gene expression profiling. This study proposed to construct and validate a risk model based on differentially expressed genes between primary and liver metastatic tumors from CRC for prognostic prediction.
Methods
Transcriptomic and clinical data of CRC were downloaded from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus database (GEO). Identification and screening of candidate differentially expressed genes (DEGs) between liver metastatic tissues and corresponding primary tumors were conducted by R package “limma” and univariate Cox analysis in the GSE50760 and TCGA cohort. Last, absolute shrinkage and selection operator (LASSO) Cox regression was carried out to shrink DEGs and develop the risk model. CRC patients from the GSE161158 cohort were utilized for validation. Functional enrichment, CIBERSORT algorithm, and ESTIMATE algorithm for further analysis.
Results
An 8-gene signature risk model, including HPD, C8G, CDO1, FGL1, SLC2A2, ALDOB, SPINK4, and ITLN1, was developed and classified the CRC patients from TCGA and GEO cohorts into high and low-risk groups. The high-risk group has a worse prognosis compared with the low-risk group. The model was verified as an independent indicator for prognosis. Moreover, tumor immune infiltration analyses demonstrated that monocytes (P = 0.006), macrophage M0 (P < 0.001), and macrophage M1 (P < 0.001) were enriched in the high-risk group, while plasma cells (P = 0.010), T cells CD4 memory resting (P < 0.001) and dendritic cells activated (P = 0.006) were increased in the low-risk group.
Conclusions
We developed and validated a risk predictive model for the DEGs between liver metastases and primary tumor of CRC, which can be utilized for the clinical prognostic indicator in CRC.
Surface roughness and moistening of the finger affect friction and detection threshold for a single microdot
Authors: Deflorio Davide , Luca Massimiliano Di , Wing Alan Miles 
Published: November 2022

Abstract
With sliding contact humans are able to perceive tactile features at the micron scale, such as a single dot raised only few microns when placed on a smooth surface. Frictional effects are important in determining the tactile cues available in sliding and depend on a variety of factors. In this study, we investigated how detection sensitivity to a single micro dot is affected by surface roughness and moistening of the index finger. These manipulations were chosen to alter the skin-surface interaction and the resulting forces acting on the skin. We found that detection threshold was 6-fold higher for the rough surfaces when compared to smooth surfaces. Moistening the finger with water or water and soap reduced the friction as well as the magnitude of tangential force variations when compared to the dry finger, regardless of the surface geometry. However, detection sensitivity improved for the ‘smooth’ surfaces but worsened for the ‘rough’ ones with moistening. We suggest that this is due to the different nature of neural noise generated when making contact with smooth or rough background surfaces, and the extent to which different fluid environments modulate friction and the forces acting on the skin with consequences for the neural response.
The role of Amhara credit and saving institution in improving rural households’ livelihood
Authors: Bekele Ayisheshim , Adiss Debassu 
Published: November 2022

Abstract
In Ethiopia only 7% rural community have ever received loan from microfinance. Some researchers argue that microfinance is not a silver bullet or panacea of poverty alleviation. The main objective of this study is to investigate the role of Amhara Credit and Saving Institution in improving livelihood of rural households. Cross sectional design and mixed research approach were used. The target population of the study was rural household clients and samples were selected by systematic random sampling. Data were gathered from primary sources via structured questionnaire and by in-depth interview. Data were analyzed quantitatively and qualitatively. Percent from descriptive and related paired t-test and Pearson correlation from inferential were mainly used. Amhara Credit and Saving Institution is not effective in improving saving habit of rural clients ad their saving amount is not enough to minimize livelihood vulnerability. The institution is not effective in helping rural clients to convert their loan for livelihood asset building and creation. The improvement of rural household’s livelihood assets after they became a client is limited mainly to human, social and financial assets. There is no significant improvement in natural and physical livelihood assets. Therefore the institution must work with different offices agriculture office specially to bring improvement on natural and physical livelihood assets.
Quality Control System for Mammographic Breast Positioning Using Deep Learning
Authors: Watanabe Haruyuki , Hayashi Saeko , Kondo Yohan , Matsuyama Eri , Hayashi Norio , Ogura Toshihiro , Shimosegawa Masayuki 
Published: November 2022

Abstract
This study proposes a deep convolutional neural network (DCNN) classification for the quality control and validation of breast positioning criteria in mammography. A total of 1631 mediolateral oblique mammographic views were collected from an open database. We designed two main steps for mammographic verification: automated detection of the positioning part and classification of three scales that determine the positioning quality using DCNNs. After acquiring labeled mammograms with three scales visually evaluated based on guidelines, the first step was automatically detecting the region of interest of the subject part by image processing. The next step was classifying mammographic positioning accuracy into three scales using four representative DCNNs. The experimental results showed that the DCNN model achieved the best positioning classification accuracy of 0.7597 using VGG16 in the inframammary fold and a classification accuracy of 0.6996 using Inception-v3 in the nipple profile. Furthermore, using the softmax function, the breast positioning criteria could be evaluated quantitatively by presenting the predicted value, which is the probability of determining positioning accuracy. The proposed method can be quantitatively evaluated without the need for an individual qualitative evaluation and has the potential to improve the quality control and validation of breast positioning criteria in mammography.
A novel biplanar positioning technique to guide iliosacral screw insertion: a retrospective study
Authors: Zhao Yangyang , Cui Pengju , Xiong Zhenggang , Zheng Jiachun , Xing Deguo 
Published: November 2022

Abstract
Purpose
To evaluate the safety and benefits of the biplanar position technique on operative time, radiation exposure, and screw placement accuracy.
Methods
In this study, we retrospectively evaluated the records of 64 patients with pelvic fractures (Tile B and C) between October 2020 and September 2021. According to the surgical methods selected by the patients, the patients were divided into a biplanar positioning technique group (biplanar group), a Ti-robot navigation group (Ti-robot group), and a traditional fluoroscopy-guided technique group (traditional group). Length of operation, blood loss, intra-operative radiation exposure fracture reduction, and the quality of screw positioning were compared among the three groups.
Results
103 screws were implanted in 64 patients (biplanar group 22, Ti-robot group 21, traditional group 21). The average operation time was significantly less in the biplanar group (26.32 ± 6.32 min) than in the traditional group (79.24 ± 11.31 min), but significantly more than in the Ti-robot group (15.81 ± 3.9 min). The radiation exposure was similar in the biplanar group (740.53 ± 185.91 cGy/cm2) and Ti-robot group (678.44 ± 127.16 cGy/cm2), both of which were significantly more than in the traditional group (2034.58 ± 494.54 cGy/cm2). The intra-operative blooding loss was similar in the biplanar group (12.76 ± 3.77 mL) and the Ti-robot group (11.92 ± 4.67 mL), both of which were significantly less than in the traditional group (29.7 ± 8.01 mL). The Screw perforation was slightly lower in the biplanar group (94.1%) than in the Ti-robot group (97.2%) but was significantly higher than in the traditional group (75.7%).
Conclusions
The biplanar positioning technique is as accurate and safe as computer-navigated systems for percutaneous iliosacral screw insertion, associated with shorter surgical time, lower intra-operative radiation exposure, and more accuracy compared to traditional fluoroscopy.
Targeting UBR5 inhibits postsurgical breast cancer lung metastases by inducing apoptosis mediated by CDC73 and p53
Authors: Yu Ziqi , Xue Dong , Song Mei , Xu Aizhang , He Qing , Li Huilin , Ouyang Wen , Chouchane Lotfi , Ma Xiaojing 
Published: November 2022

Abstract
Background: UBR5 is a HECT domain E3 ubiquitin ligase that is frequently amplified in breast, ovarian, and prostate cancers. Heightened UBR5 plays a profound role in promoting tumor growth through immune-dependent mechanisms. However, its mode of action in driving tumor metastasis has not been definitively delineated.
Methods: In this study, we used a tetracycline (Tet)-inducible RNAi-mediated expression silencing cell system to investigate how UBR5 enables postsurgical mammary tumor metastatic growth in the lungs of mice without the impact of the primary lesion. The effects of such manipulations on tumor metastasis were measured by wound healing, transwell, and clonogenicity assays in vitro, and by genetic deletion and complementation in vivo in syngeneic and xenograft mouse models. The system-wide impact was examined by RNA-seq analyses.
Results: In vitro, Ubr5 knockdown induced morphological and molecular changes characteristic of epithelial-mesenchymal transition(EMT). In vivo, UBR5 promoted lung metastasis in an E3 ubiquitin ligase-dependent manner. Moreover, doxycycline-induced knockdown of UBR5 expression in metastatic cells in the lung resulted in increased apoptosis, decreased proliferation, and prolonged survival, whereas silencing the expression of cell division cycle 73 (CDC73), a tumor suppressor and an E3 ligase substrate of UBR5, reversed these effects. Transcriptome analyses revealed a prominent role for the p53 pathway in dovitinib-induced apoptosis of tumor cells differentially regulated by UBR5 and CDC73. In human triple-negative breast cancer (TNBC) patient specimens, a strong inverse correlation was observed between UBR5 and CDC73 protein levels and reduced CDC73 expression at metastatic sites compared to primary lesions. Furthermore, a xenograft model of human TNBC recapitulated the metastatic properties and characteristics of the unique UBR5-CDC73 functional antagonism.
Conclusions: This study unveils the novel and critical roles and relationships of UBR5, CDC73 and p53 in postsurgical breast cancer metastasis and implicates the potential of targeting this pathway in cancer therapy.
Developing high-resolution metastasis signatures for improved cancer prognosis using single-cell RNA sequencing data：A case study in lung adenocarcinoma
Authors: Zhou Yeman , Li Hanlin , Zhang Cheng , Yu De’en , Yang Heng , Wang Chunping , Zhang Youhua , Deng Wensheng , Li Bo , Zhang Shihua 
Published: November 2022

Abstract
Background
Metastasis remains the reason for high cancer mortality and it is a valuable predictive factor in cancer prognosis. Single-cell RNA sequencing (scRNA-seq) can reveal cellular heterogeneity in metastasis microenvironment and capture high-resolution signatures for improved cancer prediction.
Methods
An integrated analysis framework was designed for metastatic lung adenocarcinoma (LUAD) scRNA-seq profiles and we identified 9 key prognostic genes (KPGs) that were trained and validated in 407 internal and external patient cohorts using Lasso-Cox method and Receiver Operating Characteristic (ROC) curves. To ensure the predictive stability of the KPGs signatures, 10 random samples of data from the TCGA cohort were taken. Correlation analysis revealed the strong association between KPGs signatures and several clinical characteristics such as gender, T-stage, and N-stage. We incorporated these risk clinical variables into a KPGs nomogram model.
Results
The results based on ROC curves and calibration curves show that the KPGs nomogram model with superior accuracy for overall survival (OS) prediction. We also found that high risk group with high nomogram scores had poorer prognosis accompanied by a higher tumor mutation burden (TMB) and it was associated with the upregulation of cell cycle, DNA replication, ECM receptor interaction, P53 signaling pathway, spliceosome and proteasome pathway.
Conclusions
Mining single-cell resolution metastatic features from scRNA-seq data to improve cancer prognosis is a viable strategy that would be a useful tool in risk gene discovery and targeted therapy in metastatic cancers.
Therapeutic potential of oxymatrine in impeding the cardiomyopathy in the STZ- nicotinamide induced diabetes through SIRT1/Nrf2 signaling activation
Authors: Seksaria Sanket , Mehan Sidharth , Dutta Bhaskar Jyoti , Gupta Ghanshyam Das , Singh Amrita 
Published: November 2022

Abstract
Aims

Diabetes mellitus increases the risk of heart failure independently of underlying hypertention and ischemic heart disease, leads to the cardiomyopathy. Molecular mechanism underlying these pathological changes in the diabetic cardiomyopathy (DCM) are most likely to multifactorial, but clearer pathogenesis is partially understood. Literature showed that insulin resistance was associated with the dysfunction of SIRT1, TGF-β1 protein expression and pro-apoptotic pathways. In the current research, we aimed to investigate the ameliorative effect of oxymatrine (OMT) against streptozotocin-nicotinamide (STZ-NA) induced DCM in the experimental animals.

Method

Male wistar rats (120–150 g) were pre-treated with the NA (110 mg/kg, i.p) followed by administration of STZ (60 mg/kg, i.p) after 15 min. After observed the onset of cardiomyopathy evaluated by increased diastolic dysfunction followed by systolic, two weeks later of STZ-NA administration, animals were divided in to various treatment groups. Diabetic animals were treated with pioglitazone (10mg/kg, p.o) and OMT(25, 100, 150 mg/kg, i.p) for 3 weeks. Various biochemical parameters were checked after completion of the experimental protocol.

Key findings

Diabetic animals showed hyperglycemia, impaired glucose tolerance and lipid profile. In addition, increased blood pressure, serum LDH, CK-MB levels, and abnormal hemodynamic. Apart from this, pro-inflammatory cytokines, apoptotic markers, TGF-β1 activity were increased and SIRT1 activity was decreased in thediabetic animals.While, treatment with the OMT,restored all these abnormalities. Additionally, OMT treatment dose dependently restored the anti-oxidants, pro-inflammatory, and apoptotic marker. On the basis of these observations, we concluded that OMT can protect diabetic rats from insulin resistance through the regulation of SIRT1/Nrf2, TGF-β1 and pro-apoptotic pathways.