bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fluorescence microscopy imaging of a neurotransmitter receptor and its cell membrane lipid milieu
Authors: Barrantes Francisco J. 
Published: November 2022

Hampered by the diffraction phenomenon, as expressed in 1873 by Abbe, applications of optical microscopy to image biological structures were for a long time limited to resolutions above the ∼200 nm barrier and restricted to the observation of stained specimens. The introduction of fluorescence was a game changer, and since its inception it became the gold standard technique in biological microscopy. The plasma membrane is a tenuous envelope of 4 nm–10 nm in thickness surrounding the cell. Because of its highly versatile spectroscopic properties and availability of suitable instrumentation, fluorescence techniques epitomize the current approach to study this delicate structure and its molecular constituents. The wide spectral range covered by fluorescence, intimately linked to the availability of appropriate intrinsic and extrinsic probes, provides the ability to dissect membrane constituents at the molecular scale in the spatial domain. In addition, the time resolution capabilities of fluorescence methods provide complementary high precision for studying the behavior of membrane molecules in the time domain. This review illustrates the value of various fluorescence techniques to extract information on the topography and motion of plasma membrane receptors. To this end I resort to a paradigmatic membrane-bound neurotransmitter receptor, the nicotinic acetylcholine receptor (nAChR). The structural and dynamic picture emerging from studies of this prototypic pentameric ligand-gated ion channel can be extrapolated not only to other members of this superfamily of ion channels but to other membrane-bound proteins. I also briefly discuss the various emerging techniques in the field of biomembrane labeling with new organic chemistry strategies oriented to applications in fluorescence nanoscopy, the form of fluorescence microscopy that is expanding the depth and scope of interrogation of membrane-associated phenomena.
Hepatocellular carcinoma risk-stratification based on ASGR1 in circulating epithelial cells for cancer interception
Authors: Roa-Colomo Amparo , López Garrido María Ángeles , Molina-Vallejo Pilar , Rojas Angela , Sanchez Mercedes González , Aranda-García Violeta , Salmeron Javier , Romero-Gomez Manuel , Muntane Jordi , Padillo Javier , Alamo Jose María , Lorente Jose A. , Serrano María José , Garrido-Navas M. Carmen 
Published: November 2022

Purpose: Lack of diagnostic and prognostic biomarkers in hepatocellular carcinoma impedes stratifying patients based on their risk of developing cancer. The aim of this study was to evaluate phenotypic and genetic heterogeneity of circulating epithelial cells (CECs) based on asialoglycoprotein receptor 1 (ASGR1) and miR-122-5p expression as potential diagnostic and prognostic tools in patients with hepatocellular carcinoma (HCC) and liver cirrhosis (LC).Methods: Peripheral blood samples were extracted from LC and HCC patients at different disease stages. CECs were isolated using positive immunomagnetic selection. Genetic and phenotypic characterization was validated by double immunocytochemistry for cytokeratin (CK) and ASGR1 or by in situ hybridization with miR-122-5p and CECs were visualized by confocal microscopy.Results: The presence of CECs increased HCC risk by 2.58-fold, however, this was only significant for patients with previous LC (p = 0.028) and not for those without prior LC (p = 0.23). Furthermore, the number of CECs lacking ASGR1 expression correlated significantly with HCC incidence and absence of miR-122-5p expression (p = 0.014; r = 0.23). Finally, overall survival was significantly greater for patients at earlier cancer stages (p = 0.018), but this difference was only maintained in the group with the presence of CECs (p = 0.021) whereas progression-free survival was influenced by the absence of ASGR1 expression.Conclusion: Identification and characterization of CECs by ASGR1 and/or miR-122-5p expression may be used as a risk-stratification tool in LC patients, as it was shown to be an independent prognostic and risk-stratification marker in LC and early disease stage HCC patients.
Cryo-EM structure of the diapause chaperone artemin
Authors: Parvate Amar D. , Powell Samantha M. , Brookreson Jory T. , Moser Trevor H. , Novikova Irina V. , Zhou Mowei , Evans James E. 
Published: November 2022

The protein artemin acts as both an RNA and protein chaperone and constitutes over 10% of all protein in Artemia cysts during diapause. However, its mechanistic details remain elusive since no high-resolution structure of artemin exists. Here we report the full-length structure of artemin at 2.04 Å resolution. The cryo-EM map contains density for an intramolecular disulfide bond between Cys22-Cys61 and resolves the entire C-terminus extending into the core of the assembled protein cage but in a different configuration than previously hypothesized with molecular modeling. We also provide data supporting the role of C-terminal helix F towards stabilizing the dimer form that is believed to be important for its chaperoning activity. We were able to destabilize this effect by placing a tag at the C-terminus to fully pack the internal cavity and cause limited steric hindrance.
Epigenetic histone acetylation modulating prenatal Poly I:C induced neuroinflammation in the prefrontal cortex of rats: a study in a maternal immune activation model
Authors: Su Yueqing , Lian Jiamei , Chen Shiyan , Zhang Wenchang , Deng Chao 
Published: November 2022

Introduction: Neuroinflammation in the central nervous system, particularly the prefrontal cortex (PFC), plays a role in the pathogenesis of schizophrenia, which has been found to be associated with maternal immune activation (MIA). Recent evidence suggests that epigenetic regulation involves in the MIA-induced neurodevelopmental disturbance. However, it is not well-understood how epigenetic modulation is involved in the neuroinflammation and pathogenesis of schizophrenia.Methods: This study explored the modulation of histone acetylation in both neuroinflammation and neurotransmission using an MIA rat model induced by prenatal polyriboinosinic-polyribocytidylic acid (Poly I:C) exposure, specifically examining those genes that were previously observed to be impacted by the exposure, including a subunit of nuclear factor kappa-B (Rela), Nod-Like-Receptor family Pyrin domain containing 3 (Nlrp3), NMDA receptor subunit 2A (Grin2a), 5-HT2A (Htr2a), and GABAA subunit β3 (Gabrb3).Results: Our results revealed global changes of histone acetylation on H3 (H3ace) and H4 (H4ace) in the PFC of offspring rats with prenatal Poly I:C exposure. In addition, it revealed enhancement of both H3ace and H4ace binding on the promoter region of Rela, as well as positive correlations between Rela and genes encoding histone acetyltransferases (HATs) including CREB-binding protein (CBP) and E1A-associated protein p300 (EP300). Although there was no change in H3ace or H4ace enrichment on the promoter region of Nlrp3, a significant enhancement of histone deacetylase 6 (HDAC6) binding on the promoter region of Nlrp3 and a positive correlation between Nlrp3 and Hdac6 were also observed. However, prenatal Poly I:C treatment did not lead to any specific changes of H3ace and H4ace on the promoter region of the target genes encoding neurotransmitter receptors in this study.Discussion: These findings demonstrated that epigenetic modulation contributes to NF-κB/NLRP3 mediated neuroinflammation induced by prenatal Poly I:C exposure via enhancement of histone acetylation of H3ace and H4ace on Rela and HDAC6-mediated NLRP3 transcriptional activation. This may further lead to deficits in neurotransmissions and schizophrenia-like behaviors observed in offspring.
Constructing brain functional network by Adversarial Temporal-Spatial Aligned Transformer for early AD analysis
Authors: Zuo Qiankun , Lu Libin , Wang Lin , Zuo Jiahui , Ouyang Tao 
Published: November 2022

IntroductionThe brain functional network can describe the spontaneous activity of nerve cells and reveal the subtle abnormal changes associated with brain disease. It has been widely used for analyzing early Alzheimer's disease (AD) and exploring pathological mechanisms. However, the current methods of constructing functional connectivity networks from functional magnetic resonance imaging (fMRI) heavily depend on the software toolboxes, which may lead to errors in connection strength estimation and bad performance in disease analysis because of many subjective settings.MethodsTo solve this problem, in this paper, a novel Adversarial Temporal-Spatial Aligned Transformer (ATAT) model is proposed to automatically map 4D fMRI into functional connectivity network for early AD analysis. By incorporating the volume and location of anatomical brain regions, the region-guided feature learning network can roughly focus on local features for each brain region. Also, the spatial-temporal aligned transformer network is developed to adaptively adjust boundary features of adjacent regions and capture global functional connectivity patterns of distant regions. Furthermore, a multi-channel temporal discriminator is devised to distinguish the joint distributions of the multi-region time series from the generator and the real sample.ResultsExperimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) proved the effectiveness and superior performance of the proposed model in early AD prediction and progression analysis.DiscussionTo verify the reliability of the proposed model, the detected important ROIs are compared with clinical studies and show partial consistency. Furthermore, the most significant altered connectivity reflects the main characteristics associated with AD.ConclusionGenerally, the proposed ATAT provides a new perspective in constructing functional connectivity networks and is able to evaluate the disease-related changing characteristics at different stages for neuroscience exploration and clinical disease analysis.
Propensity score matching comparing short-term nerve electrical stimulation to pulsed radiofrequency for herpes zoster-associated pain: A retrospective study
Authors: Liu Liu , Zhang Wen-jing , Xu Shu-xiang , Guo Wen-shuai , Yan Ran-ran , Jiang Xiao-han , Li Shi-yao , Sun Tao 
Published: November 2022

BackgroundZoster-associated pain (ZAP) is notoriously difficult to treat. Pulsed radiofrequency (PRF) and short-term nerve electrical stimulation (st-NES) have been proven effective treatments for ZAP. However, it is still unclear which technique provides improved analgesia in ZAP. This study is based on a large-scale, long-term follow-up to evaluate the efficacy and safety between st-NES and PRF.Materials and methodsAll eligible ZAP patients treated with st-NES or PRF in our department were enrolled. Cohorts were divided into the st-NES group and the PRF group. A 1:1 ratio propensity score matching (PSM) was used to balance the baseline characteristics. The PS-matched cohort was adopted to investigate the efficacy and safety of the two treatments. The ordinal regression analysis was performed to determine the variables affecting the treatment effect of ZAP.ResultsA total of 226 patients were included after PSM. The numerical rating scale (NRS) scores in st-NES and PRF groups considerably reduced compared to baseline levels after treatment. The NRS scores in the st-NES group were obviously lower than those in the PRF group at discharge, 1, 3, 6, 12, and 24 months. During the follow-up period, the NRS reduction rate remained higher in the st-NES group than in the PRF group (P &lt; 0.01). The dosage of medication, Pittsburgh Sleep Quality Index (PSQI) score, and the number of patients with aggravated pain after discharge in the st-NES group were significantly less than in the PRF group after treatment.ConclusionShort-term nerve electrical stimulation has been shown to be more advantageous than PRF for pain relief and quality of life improvement for ZAP patients.
Diagnostic performance of radiomics in predicting axillary lymph node metastasis in breast cancer: A systematic review and meta-analysis
Authors: Gong Xiuru , Guo Yaxin , Zhu Tingting , Peng Xiaolin , Xing Dongwei , Zhang Minguang 
Published: November 2022

BackgroundThis study aimed to perform a meta‐analysis to evaluate the diagnostic performance of radiomics in predicting axillary lymph node metastasis (ALNM) and sentinel lymph node metastasis (SLNM) in breast cancer.Materials and methodsMultiple electronic databases were systematically searched to identify relevant studies published before April 29, 2022: PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data. The quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The overall diagnostic odds ratio (DOR), sensitivity, specificity, and area under the curve (AUC) were calculated to evaluate the diagnostic performance of radiomic features for lymph node metastasis (LNM) in patients with breast cancer. Spearman’s correlation coefficient was determined to assess the threshold effect, and meta-regression and subgroup analyses were performed to explore the possible causes of heterogeneity.ResultsA total of 30 studies with 5611 patients were included in the meta-analysis. Pooled estimates suggesting overall diagnostic accuracy of radiomics in detecting LNM were determined: DOR, 23 (95% CI, 16-33); sensitivity, 0.86 (95% CI, 0.82-0.88); specificity, 0.79 (95% CI, 0.73-0.84); and AUC, 0.90 (95% CI, 0.87-0.92). The meta-analysis showed significant heterogeneity between sensitivity and specificity across the included studies, with no evidence for a threshold effect. Meta-regression and subgroup analyses showed that combined clinical factors, modeling method, region, and imaging modality (magnetic resonance imaging [MRI], ultrasound, computed tomography [CT], and X-ray mammography [MMG]) contributed to the heterogeneity in the sensitivity analysis (P &lt; 0.05). Furthermore, modeling methods, MRI, and MMG contributed to the heterogeneity in the specificity analysis (P &lt; 0.05).ConclusionOur results show that radiomics has good diagnostic performance in predicting ALNM and SLNM in breast cancer. Thus, we propose this approach as a clinical method for the preoperative identification of LNM.
Proton therapy for isolated local regional recurrence of breast cancer after mastectomy alone
Authors: Laughlin Brady S. , Bhangoo Ronik S. , Niska Joshua R. , Thorpe Cameron S. , Girardo Marlene E. , Anderson Justin D. , Kosiorek Heidi E. , McGee Lisa A. , Hartsell William F. , Chang John H. , Rossi Carl J. , Tsai Henry K. , Choi Isabelle J. , Vargas Carlos E. 
Published: November 2022

Purpose/ObjectivesTo assess adverse events (AEs) and disease-specific outcomes after proton therapy for isolated local-regional recurrence (LRR) of breast cancer after mastectomy without prior radiotherapy (RT).Materials/MethodsPatients were identified from a multi-institutional prospective registry and included if diagnosed with invasive breast cancer, initially underwent mastectomy without adjuvant RT, experienced an LRR, and subsequently underwent salvage treatment, including proton therapy. Follow-up and cancer outcomes were measured from the date of RT completion.ResultsNineteen patients were included. Seventeen patients were treated with proton therapy to the chest wall and comprehensive regional lymphatics (17/19, 90%). Maximum grade AE was grade 2 in 13 (69%) patients and grade 3 in 4 (21%) patients. All patients with grade 3 AE received &gt; 60 GyE (p=0.04, Spearman correlation coefficient=0.5). At the last follow-up, 90% of patients were alive with no LRR or distant recurrence.ConclusionsFor breast cancer patients with isolated LRR after initial mastectomy without adjuvant RT, proton therapy is well-tolerated in the salvage setting with excellent loco-regional control. All grade 3 AEs occurred in patients receiving &gt; 60 GyE.
Visualizing knowledge evolution trends and research hotspots of artificial intelligence in colorectal cancer: A bibliometric analysis
Authors: Liu Guangwei , Zhao Jun , Tian Guangye , Li Shuai , Lu Yun 
Published: November 2022

BackgroundIn recent years, the rapid development of artificial intelligence (AI) technology has created a new diagnostic and therapeutic opportunity for colorectal cancer (CRC). Numerous academic and clinical studies have demonstrated that high-level auxiliary diagnosis and treatment systems based on AI technology can significantly improve the readability of medical data, objectively provide a reliable and comprehensive reference for physicians, reduce the experience gap between physicians, and aid physicians in making more accurate diagnosis decisions. In this study, we used bibliometric techniques to visually analyze the literature about AI in the CRC field and summarize the current situation and research hotspots in this field.MethodsThe relevant literature on AI in the field of CRC research was obtained from the Web of Science Core Collection (WoSCC) database. The software CiteSpace was utilized to analyze the number of papers, countries, institutions, authors, journals, cited literature, and keywords of the included literature and generate a visual knowledge map. The present study aims to evaluate the origin, current hotspots, and research trends of AI in CRC using bibliometric analysis.ResultsAs of March 2022, 64 nations/regions, 230 institutions, 245 journals, and 300 authors had published 562 AI-related articles in the field of CRC. Since 2016, each year has seen an exponential increase. China and the United States were the largest contributors, with the largest number of beneficial research institutions and the closest collaboration relationship. The World Journal of Gastroenterology is this field’s most widely published journal. Diagnosis and treatment research, gene and immunology research, intestinal polyp research, tumor grading research, gastrointestinal endoscopy research, and prognosis research comprised the six topics derived from high-frequency keyword cluster analysis.ConclusionIn recent years, field research has been a popular topic of discussion. The results of our bibliometric analysis allow us to comprehend better the current situation and trend of this research field, and the quantitative data indicators can serve as a guide for the research and application of global scholars.
Development and validation of an ultrasound-based radiomics nomogram for predicting the luminal from non-luminal type in patients with breast carcinoma
Authors: Wu Jiangfeng , Ge Lifang , Jin Yun , Wang Yunlai , Hu Liyan , Xu Dong , Wang Zhengping 
Published: November 2022

IntroductionThe molecular subtype plays a significant role in breast carcinoma (BC), which is the main indicator to guide treatment and is closely associated with prognosis. The aim of this study was to investigate the feasibility and efficacy of an ultrasound-based radiomics nomogram in preoperatively discriminating the luminal from non-luminal type in patients with BC.MethodsA total of 264 BC patients who underwent routine ultrasound examination were enrolled in this study, of which 184 patients belonged to the training set and 80 patients to the test set. Breast tumors were delineated manually on the ultrasound images and then radiomics features were extracted. In the training set, the T test and least absolute shrinkage and selection operator (LASSO) were used for selecting features, and the radiomics score (Rad-score) for each patient was calculated. Based on the clinical risk features, Rad-score, and combined clinical risk features and Rad-score, three models were established, respectively. The performances of the models were validated with receiver operator characteristic (ROC) curve and decision curve analysis.ResultsIn all, 788 radiomics features per case were obtained from the ultrasound images. Through radiomics feature selection, 11 features were selected to constitute the Rad-score. The area under the ROC curve (AUC) of the Rad-score for predicting the luminal type was 0.828 in the training set and 0.786 in the test set. The nomogram comprising the Rad-score and US-reported tumor size showed AUCs of the training and test sets were 0.832 and 0.767, respectively, which were significantly higher than the AUCs of the clinical model in the training and test sets (0.691 and 0.526, respectively). However, there was no significant difference in predictive performance between the Rad-score and nomogram.ConclusionBoth the Rad-score and nomogram can be applied as useful, noninvasive tools for preoperatively discriminating the luminal from non-luminal type in patients with BC. Furthermore, this study might provide a novel technique to evaluate molecular subtypes of BC.
Pharmacokinetics of fluorobenzyl polyethylene glycol conjugated tetraiodothyroacetic acid (NP751), a novel anticancer thyrointegrin αvβ3 antagonist
Authors: Fujioka Kazutoshi , Hay Bruce A. , Godugu Kavitha , Mousa Shaker A. 
Published: November 2022

We have recently reported on the development of fb-PMT (NP751), a conjugate of the thyroid hormone metabolite tetraiodothyroacetic acid (tetrac) and monodisperse polyethylene glycol 36. It exhibited high affinity for thyrointegrin αvβ3 receptor and potent anti-angiogenic and anticancer activity in vivo. The objective of the current study is to determine the pharmacokinetics (PK) of fb-PMT in experimental animals, such as mice, rats, and monkeys. NP751 was quantified using a propylene diamine-modified tetraiodothyroacetic acid (DAT) as an internal standard. The limit of quantification (LOQ) for fb-PMT was 1.5 ng/μL and the recovery efficiency was 93.9% with the developed method. The peak plasma concentration (Cmax) and the area under the curve (AUC) results at different doses in mice, rats and monkeys suggest that pharmacokinetics of NP751 is dose-dependent within the dose ranges administered. Results indicate that NP751 has comparable PK parameters that provides enough exposure as a molecularly tumor targeted molecule in multiple species and is a promising anticancer therapeutic.