bluuebunny/crossref_metadata_2025 huggingface dataset:
Autoantibody Landscape Revealed by Wet Protein Array: Sum of Autoantibody Levels Reflects Disease Status
Authors: Matsuda Kazuki M. , Yoshizaki Ayumi , Yamaguchi Kei , Fukuda Eriko , Okumura Taishi , Ogawa Koji , Ono Chihiro , Norimatsu Yuta , Kotani Hirohito , Hisamoto Teruyoshi , Kawanabe Ruriko , Kuzumi Ai , Fukasawa Takemichi , Ebata Satoshi , Miyagawa Takuya , Yoshizaki-Ogawa Asako , Goshima Naoki , Sato Shinichi
Published: May 2022

Autoantibodies are found in various pathological conditions such as autoimmune diseases, infectious diseases, and malignant tumors. However their clinical implications have not yet been fully elucidated. Herein, we conducted proteome-wide autoantibody screening and quantification with wet protein arrays consisting of proteins synthesized from proteome-wide human cDNA library (HuPEX) maintaining their three-dimensional structure. A total of 565 autoantibodies were identified from the sera of three representative inflammatory disorders (systemic sclerosis, psoriasis, and cutaneous arteritis). Each autoantibody level either positively or negatively correlated with serum levels of C-reactive protein, the best-recognized indicator of inflammation. In particular, we discovered total levels of a subset of autoantibodies correlates with the severity of clinical symptoms. From the sera of malignant melanoma, 488 autoantibodies were detected. Notably, patients with metastases had increased overall autoantibody production compared to those with tumors limiting to the primary site. Collectively, proteome-wide screening of autoantibodies using the in vitro proteome can reveal the “autoantibody landscape” of human subjects and may provide novel clinical biomarkers.
Omalizumab for STAT3 Hyper-IgE Syndromes in Adulthood: A Case Report and Literature Review
Authors: Lan Jun , Zhang Yi , Song Min , Cai Shan , Luo Hong , OuYang Ruoyun , Yang Pan , Shi Xiaoliu , Long Yingjiao , Chen Yan
Published: May 2022

Background

Hyper-immunoglobulin E (IgE) syndromes (HIES) are a group of primary immune deficiencies disorders (PID) characterized by elevated serum IgE, eczema, recurrent skin, or respiratory system infections and may also be accompanied by some connective tissues and skeletal abnormalities. Currently, there is no complete cure or targeted treatment for HIES. Omalizumab is a humanized recombinant monoclonal antibody against IgE, reducing the level of free IgE, inhibiting the binding of IgE to receptors on the surface of effector cells, and reducing the activation of inflammatory cells and the release of multiple inflammatory mediators. However, the effect of omalizumab in treating HIES remains unknown. Herein, we described a case of an AD-HIES patient with chronic airway disease who benefited from omalizumab treatment.

Case Presentation

A 28-year-old Chinese woman was admitted for recurrent cough for 7 years, markedly elevated serum IgE level, and recurrent pneumonia caused by multiple pathogens, such as Pneumocystis jirovecii, Cytomegalovirus, Staphylococcus aureus, Aspergillus, and Mycobacterium tuberculosis. She had eczema-dermatitis, skin abscess, slightly traumatic fracture since childhood, and developed asthma and allergic bronchopulmonary aspergillosis (ABPA) lately. Using whole-exome sequencing, the STAT3 (c.1294G>T, p.Val432Leu) missense mutation for the autosomal dominant hyper-IgE syndrome was identified, and omalizumab was prescribed at 300 mg every 2 weeks. The patient responded well with the improvement of respiratory symptoms and lung function tests. The level of serum IgE remained stable on follow-up.

Conclusion

Omalizumab treatment proved beneficial in the case of HIES, especially with chronic airway disease, for which therapeutic options are limited. However, larger-scale prospective studies and long-term follow-up are required to establish the efficacy and safety of this therapeutic intervention.
Association of Proton Pump Inhibitor and Infection and Major Adverse Clinical Events in Patients With ST-Elevation Myocardial Infarction: A Propensity Score Matching Analysis
Authors: Liu Yuan-Hui , Cao Zhi-Yuan , Dai Yi-Ning , Zeng Li-Huan , Zhang Ye-Shen , Fan Hua-Lin , Duan Chong-Yang , Tan Ning , He Peng-Cheng
Published: May 2022

Background

Infections are not common but important in patients with acute myocardial infarction, and are associated with worse outcomes. Infection was proved to be associated with the use of proton pump inhibitor (PPI) in several cohorts. It remains unclear whether PPI usage affects infection in patients with acute myocardial infarction.

Methods

We consecutively enrolled patients with ST-elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI) from January 2010 to June 2018. All patients were divided into the PPI group and non-PPI group according to whether the PPI was used. The primary endpoint was the development of infection during hospitalization.

Results

A total of 3027 patients were finally enrolled, with a mean age of 62.2 ± 12.6 years. 310 (10.2%) patients were developed infection during hospitalization. Baseline characteristics were similar between the PPI and non-PPI groups (n = 584 for each group) after propensity score analysis. PPI usage was significantly associated with infection based on the propensity score matching analysis (adjusted OR = 1.62, 95% CI = 1.02-2.57, P = 0.041). Comparing to patients with non-PPI usage, PPI administration was positively associated with higher risk of in-hospital all-cause mortality (adjusted OR = 3.25, 95% CI = 1.06-9.97, P = 0.039) and in-hospital major adverse clinical events (adjusted OR = 3.71, 95% CI = 1.61-8.56, P = 0.002). Subgroup analysis demonstrated that the impact of PPI on infection was not significantly different among patients with or without diabetes and patients with age ≥65 years or age <65 years.

Conclusion

PPI usage was related to a higher incidence of infection during hospitalization, in-hospital all-cause mortality, and in-hospital major adverse clinical events (MACE) in STEMI patients.
Repurposing of Doxycycline to Hinder the Viral Replication of SARS-CoV-2: From in silico to in vitro Validation
Authors: Alexpandi Rajaiah , Gendrot Mathieu , Abirami Gurusamy , Delandre Océane , Fonta Isabelle , Mosnier Joel , Mariadasse Richard , Jeyakanthan Jeyaraman , Pandian Shunmugiah Karutha , Pradines Bruno , Ravi Arumugam Veera
Published: May 2022

Since the rapid spread of coronavirus disease (COVID-19) became a global pandemic, healthcare ministries around the world have recommended specific control methods such as quarantining infected peoples, identifying infections, wearing mask, and practicing hand hygiene. Since no effective treatment for COVID-19 has yet been discovered, a variety of drugs approved by Food and Drug Administration (FDA) have been suggested for repurposing strategy. In the current study, we predicted that doxycycline could interact with the nucleotide triphosphate (NTP) entry channel, and is therefore expected to hinder the viral replication of SARS-CoV-2 RNA-dependent RNA-polymerase (RdRp) through docking analysis. Further, the molecular dynamics results revealed that the RdRp-Doxycycline complex was structurally relatively stable during the dynamic period (100 ns), and its complex maintained close contact with their active catalytic domains of SARS-CoV-2 RdRp. The molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculation of binding free energy also showed that the doxycycline has worthy affinities with SARS-CoV-2 RdRp. As expected, doxycycline effectively inhibited the viral replication of IHU strains of SARS-CoV-2 (IHUMI-3 and IHUMI-6), identified from the hospitalized patients in IHU Méditerranée Infection (IHUMI), Marseille, France. Moreover, doxycycline inhibited the viral load in vitro at both on-entry and after viral entry of IHU variants of SARS-CoV-2. The results suggest that doxycycline exhibits strains-dependant antiviral activity against COVID-19. As a result, the current study concludes that doxycycline may be more effective in combination with other drugs for better COVID-19 treatment efficacy.
Insight Into Distinct Functional Roles of the Flagellar ATPase Complex for Flagellar Assembly in Salmonella
Authors: Minamino Tohru , Kinoshita Miki , Namba Keiichi
Published: May 2022

Most motile bacteria utilize the flagellar type III secretion system (fT3SS) to construct the flagellum, which is a supramolecular motility machine consisting of basal body rings and an axial structure. Each axial protein is translocated via the fT3SS across the cytoplasmic membrane, diffuses down the central channel of the growing flagellar structure and assembles at the distal end. The fT3SS consists of a transmembrane export complex and a cytoplasmic ATPase ring complex with a stoichiometry of 12 FliH, 6 FliI and 1 FliJ. This complex is structurally similar to the cytoplasmic part of the FOF1 ATP synthase. The export complex requires the FliH12-FliI6-FliJ1 ring complex to serve as an active protein transporter. The FliI6 ring has six catalytic sites and hydrolyzes ATP at an interface between FliI subunits. FliJ binds to the center of the FliI6 ring and acts as the central stalk to activate the export complex. The FliH dimer binds to the N-terminal domain of each of the six FliI subunits and anchors the FliI6-FliJ1 ring to the base of the flagellum. In addition, FliI exists as a hetero-trimer with the FliH dimer in the cytoplasm. The rapid association-dissociation cycle of this hetero-trimer with the docking platform of the export complex promotes sequential transfer of export substrates from the cytoplasm to the export gate for high-speed protein transport. In this article, we review our current understanding of multiple roles played by the flagellar cytoplasmic ATPase complex during efficient flagellar assembly.
A Fluorescent Reporter-Based Evaluation Assay for Antibacterial Components Against Xanthomonas citri subsp. citri
Authors: Long Yunfei , Luo Ruifang , Xu Zhou , Cheng Shuyuan , Li Ling , Ma Haijie , Bao Minli , Li Min , Ouyang Zhigang , Wang Nian , Duan Shuo
Published: May 2022

Xanthomonas citri subsp. citri (Xcc) is the agent of citrus bacterial canker (CBC) disease, which has significantly reduced citrus quantity and quality in many producing areas worldwide. Copper-based bactericides are the primary products for CBC control and management, but the problems derived from copper-resistant and environmental contamination have become issues of anxiety. Thus, there is a need to find alternative antibacterial products instead of relying on a single type of agent. This study developed a method to evaluate the inhibition of antibacterial agents using the fluorescence-labeled recombinant Xcc strain (Xcc-eYFP). The optimization of timelines and parameters for the evaluation of antibacterial agents involved the use of a Spark™ multimode microplate reader. This evaluation and screening method can be applied to bactericides, cocktail-mixture formulations, antagonistic bacteria, and derived metabolites. The results showed that the minimum inhibitory concentration (MIC) of commercial bactericides determined by fluorescence agrees with the MIC values determined by the conventional method. A screened cocktail-mixture bactericide presents more activity than the individual agents during the protective effects. Notably, this method has been further developed in the screening of Xcc-antagonistic bacterial strains. In summary, we provide a validated strategy for screening and evaluation of different antibacterial components for inhibition against Xcc for CBC control and management.
Predicting the Stone-Free Status of Percutaneous Nephrolithotomy With the Machine Learning System: Comparative Analysis With Guy’s Stone Score and the S.T.O.N.E Score System
Authors: Zhao Hong , Li Wanling , Li Junsheng , Li Li , Wang Hang , Guo Jianming
Published: May 2022

Purpose: The aim of the study was to use machine learning methods (MLMs) to predict the stone-free status after percutaneous nephrolithotomy (PCNL). We compared the performance of this system with Guy’s stone score and the S.T.O.N.E score system.

Materials and Methods: Data from 222 patients (90 females, 41%) who underwent PCNL at our center were used. Twenty-six parameters, including individual variables, renal and stone factors, and surgical factors were used as input data for MLMs. We evaluated the efficacy of four different techniques: Lasso-logistic (LL), random forest (RF), support vector machine (SVM), and Naive Bayes. The model performance was evaluated using the area under the curve (AUC) and compared with that of Guy’s stone score and the S.T.O.N.E score system.

Results: The overall stone-free rate was 50% (111/222). To predict the stone-free status, all receiver operating characteristic curves of the four MLMs were above the curve for Guy’s stone score. The AUCs of LL, RF, SVM, and Naive Bayes were 0.879, 0.803, 0.818, and 0.803, respectively. These values were higher than the AUC of Guy’s score system, 0.800. The accuracies of the MLMs (0.803% to 0.818%) were also superior to the S.T.O.N.E score system (0.788%). Among the MLMs, Lasso-logistic showed the most favorable AUC.

Conclusion: Machine learning methods can predict the stone-free rate with AUCs not inferior to those of Guy’s stone score and the S.T.O.N.E score system.
Ontological Approach to Support the Horizontal and Vertical Information Integration in Smart Manufacturing Systems: An Experimental Case in a Long-Life Packaging Factory
Authors: Pereira Ramon Martinez , Szejka Anderson Luis , Canciglieri Jr. Osiris
Published: May 2022

Digital manufacturing has been challenged by the manufacturing industry to rationalize different ways to connect and exchange information and knowledge across different phases of manufacturing systems. One of the Industry 4.0 pillars is the horizontal and vertical integration with intelligent and self-adaptive systems. For this to be possible, the manufacturing industry applies an extensive range of software tools, such as GRAI, CIMOSA, MO2GO, ARIS, SCADA, MES, ERP, CAD, and CAM. Individually, each one performs its function to support the manufacturing process. However, when these multiple tools operate together using technical standards, some misinterpretation and mistake gaps are identified due to a lack of machine-to-machine (M2M) communication and users’ interpretation. This is recognized as a semantic interoperability problem. Semantic technologies, such as ontologies, have been proven to be a promising way to overcome semantic interoperability obstacles. Based on this context, this study is proposing a conceptual framework based on semantic technologies to create a solution to the horizontal and vertical integration and semantic interoperability obstacle. MANUMATE is the framework proposed, and it consists of three artifacts, 1) reference ontologies, 2) requirements, and 3) application ontology, and two processes, 1) ontology specialization and 2) information application. The MANUMATE framework is applied to two experimental case studies to validate the conceptual solution in two different applications, in the context of a long-life package for the beverages industry. These case studies help elucidate how the application of the framework could improve the information and knowledge exchange by providing a standard way to represent information among different stakeholders in the productive process. A discussion about the results is presented, revealing the benefits and limitations of the solution.
Endoplasmic Reticulum Stress and the Unfolded Protein Response in Cerebral Ischemia/Reperfusion Injury
Authors: Wang Lei , Liu Yan , Zhang Xu , Ye Yingze , Xiong Xiaoxing , Zhang Shudi , Gu Lijuan , Jian Zhihong , Wang Hongfa
Published: May 2022

Ischemic stroke is an acute cerebrovascular disease characterized by sudden interruption of blood flow in a certain part of the brain, leading to serious disability and death. At present, treatment methods for ischemic stroke are limited to thrombolysis or thrombus removal, but the treatment window is very narrow. However, recovery of cerebral blood circulation further causes cerebral ischemia/reperfusion injury (CIRI). The endoplasmic reticulum (ER) plays an important role in protein secretion, membrane protein folding, transportation, and maintenance of intracellular calcium homeostasis. Endoplasmic reticulum stress (ERS) plays a crucial role in cerebral ischemia pathophysiology. Mild ERS helps improve cell tolerance and restore cell homeostasis; however, excessive or long-term ERS causes apoptotic pathway activation. Specifically, the protein kinase R-like endoplasmic reticulum kinase (PERK), activating transcription factor 6 (ATF6), and inositol-requiring enzyme 1 (IRE1) pathways are significantly activated following initiation of the unfolded protein response (UPR). CIRI-induced apoptosis leads to nerve cell death, which ultimately aggravates neurological deficits in patients. Therefore, it is necessary and important to comprehensively explore the mechanism of ERS in CIRI to identify methods for preserving brain cells and neuronal function after ischemia.
Neurodegeneration Within the Amygdala Is Differentially Induced by Opioid and HIV-1 Tat Exposure
Authors: Nass Sara R. , Ohene-Nyako Michael , Hahn Yun K. , Knapp Pamela E. , Hauser Kurt F.
Published: May 2022

Opioid use disorder (OUD) is a critical problem that contributes to the spread of HIV and may intrinsically worsen neuroHIV. Despite the advent of combined antiretroviral therapies (cART), about half of persons infected with HIV (PWH) experience cognitive and emotional deficits that can be exacerbated by opioid abuse. HIV-1 Tat is expressed in the central nervous system (CNS) of PWH on cART and is thought to contribute to neuroHIV. The amygdala regulates emotion and memories associated with fear and stress and is important in addiction behavior. Notwithstanding its importance in emotional saliency, the effects of HIV and opioids in the amygdala are underexplored. To assess Tat- and morphine-induced neuropathology within the amygdala, male Tat transgenic mice were exposed to Tat for 8 weeks and administered saline and/or escalating doses of morphine twice daily (s.c.) during the last 2 weeks of Tat exposure. Eight weeks of Tat exposure decreased the acoustic startle response and the dendritic spine density in the basolateral amygdala, but not the central nucleus of the amygdala. In contrast, repeated exposure to morphine alone, but not Tat, increased the acoustic startle response and whole amygdalar levels of amyloid-β (Aβ) monomers and oligomers and tau phosphorylation at Ser396, but not neurofilament light chain levels. Co-exposure to Tat and morphine decreased habituation and prepulse inhibition to the acoustic startle response and potentiated the morphine-induced increase in Aβ monomers. Together, our findings indicate that sustained Tat and morphine exposure differentially promote synaptodendritic degeneration within the amygdala and alter sensorimotor processing.
Multi-Model Adaptation Learning With Possibilistic Clustering Assumption for EEG-Based Emotion Recognition
Authors: Dan Yufang , Tao Jianwen , Zhou Di
Published: May 2022

In machine learning community, graph-based semi-supervised learning (GSSL) approaches have attracted more extensive research due to their elegant mathematical formulation and good performance. However, one of the reasons affecting the performance of the GSSL method is that the training data and test data need to be independently identically distributed (IID); any individual user may show a completely different encephalogram (EEG) data in the same situation. The EEG data may be non-IID. In addition, noise/outlier sensitiveness still exist in GSSL approaches. To these ends, we propose in this paper a novel clustering method based on structure risk minimization model, called multi-model adaptation learning with possibilistic clustering assumption for EEG-based emotion recognition (MA-PCA). It can effectively minimize the influence from the noise/outlier samples based on different EEG-based data distribution in some reproduced kernel Hilbert space. Our main ideas are as follows: (1) reducing the negative impact of noise/outlier patterns through fuzzy entropy regularization, (2) considering the training data and test data are IID and non-IID to obtain a better performance by multi-model adaptation learning, and (3) the algorithm implementation and convergence theorem are also given. A large number of experiments and deep analysis on real DEAP datasets and SEED datasets was carried out. The results show that the MA-PCA method has superior or comparable robustness and generalization performance to EEG-based emotion recognition.
Novel Machine-Learning Based Framework Using Electroretinography Data for the Detection of Early-Stage Glaucoma
Authors: Gajendran Mohan Kumar , Rohowetz Landon J. , Koulen Peter , Mehdizadeh Amirfarhang
Published: May 2022

Purpose

Early-stage glaucoma diagnosis has been a challenging problem in ophthalmology. The current state-of-the-art glaucoma diagnosis techniques do not completely leverage the functional measures' such as electroretinogram's immense potential; instead, focus is on structural measures like optical coherence tomography. The current study aims to take a foundational step toward the development of a novel and reliable predictive framework for early detection of glaucoma using machine-learning-based algorithm capable of leveraging medically relevant information that ERG signals contain.

Methods

ERG signals from 60 eyes of DBA/2 mice were grouped for binary classification based on age. The signals were also grouped based on intraocular pressure (IOP) for multiclass classification. Statistical and wavelet-based features were engineered and extracted. Important predictors (ERG tests and features) were determined, and the performance of five machine learning-based methods were evaluated.

Results

Random forest (bagged trees) ensemble classifier provided the best performance in both binary and multiclass classification of ERG signals. An accuracy of 91.7 and 80% was achieved for binary and multiclass classification, respectively, suggesting that machine-learning-based models can detect subtle changes in ERG signals if trained using advanced features such as those based on wavelet analyses.

Conclusions

The present study describes a novel, machine-learning-based method to analyze ERG signals providing additional information that may be used to detect early-stage glaucoma. Based on promising performance metrics obtained using the proposed machine-learning-based framework leveraging an established ERG data set, we conclude that the novel framework allows for detection of functional deficits of early/various stages of glaucoma in mice.
From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila
Authors: Ryu Leesun , Kim Sung Yong , Kim Anmo J.
Published: May 2022

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.
Dietary Supplementation With Branched Chain Amino Acids to Improve Sleep in Veterans With Traumatic Brain Injury: A Randomized Double-Blind Placebo-Controlled Pilot and Feasibility Trial
Authors: Elliott Jonathan E. , Keil Allison T. , Mithani Sara , Gill Jessica M. , O’Neil Maya E. , Cohen Akiva S. , Lim Miranda M.
Published: May 2022

Study Objectives

Traumatic brain injury (TBI) is associated with chronic sleep disturbances and cognitive impairment. Our prior preclinical work demonstrated dietary supplementation with branched chain amino acids (BCAA: leucine, isoleucine, and valine), precursors to de novo glutamate production, restored impairments in glutamate, orexin/hypocretin neurons, sleep, and memory in rodent models of TBI. This pilot study assessed the feasibility and preliminary efficacy of dietary supplementation with BCAA on sleep and cognition in Veterans with TBI.

Methods

Thirty-two Veterans with TBI were prospectively enrolled in a randomized, double-blinded, placebo-controlled trial comparing BCAA (30 g, b.i.d. for 21-days) with one of two placebo arms (microcrystalline cellulose or rice protein, both 30 g, b.i.d. for 21-days). Pre- and post-intervention outcomes included sleep measures (questionnaires, daily sleep/study diaries, and wrist actigraphy), neuropsychological testing, and blood-based biomarkers related to BCAA consumption.

Results

Six subjects withdrew from the study (2/group), leaving 26 remaining subjects who were highly adherent to the protocol (BCAA, 93%; rice protein, 96%; microcrystalline, 95%; actigraphy 87%). BCAA were well-tolerated with few side effects and no adverse events. BCAA significantly improved subjective insomnia symptoms and objective sleep latency and wake after sleep onset on actigraphy.

Conclusion

Dietary supplementation with BCAA is a mechanism-based, promising intervention that shows feasibility, acceptability, and preliminary efficacy to treat insomnia and objective sleep disruption in Veterans with TBI. A larger scale randomized clinical trial is warranted to further evaluate the efficacy, dosing, and duration of BCAA effects on sleep and other related outcome measures in individuals with TBI.

Clinical Trial Registration

[http://clinicaltrials.gov/], identifier [NCT03990909].
The Nature and Persistence of Posthypnotic Suggestions' Effects on Food Preferences: An Online Study
Authors: Zahedi Anoushiravan , Öznur Akalin Renin , Lawrence Johanna E. , Baumann Annika , Sommer Werner
Published: May 2022

Food preferences are crucial for diet-related decisions, which substantially impact individual health and global climate. However, the persistence of unfavorable food preferences is a significant obstacle to changing eating behavior. Here we explored the effects of posthypnotic suggestions (PHS) on food-related decisions by measuring food choices, subjective ratings, and indifference points. In Session 1, demographic data and hypnotic susceptibility of participants were assessed. In Session 2, following hypnosis induction, PHS aiming to increase the desirability of healthy food was delivered. Afterward, a task set was administrated twice, once when PHS was activated and once deactivated. The order of PHS activation was counterbalanced across participants. The task set included a liking-rating task for 170 pictures of different food items, followed by an online supermarket where participants were instructed to select enough food for a fictitious week of quarantining from the same item pool. After 1 week, Session 3 repeated Session 2 without hypnosis induction in order to assess the persistence of PHS. The crucial dependent measures were food choices, subjective ratings, and the indifference points as a function of time and PHS condition.
Precision Oncology: Artificial Intelligence and DNA Methylation Analysis of Circulating Cell-Free DNA for Lung Cancer Detection
Authors: Bahado-Singh Ray , Vlachos Kyriacos T. , Aydas Buket , Gordevicius Juozas , Radhakrishna Uppala , Vishweswaraiah Sangeetha
Published: May 2022

Background

Lung cancer (LC) is a leading cause of cancer-deaths globally. Its lethality is due in large part to the paucity of accurate screening markers. Precision Medicine includes the use of omics technology and novel analytic approaches for biomarker development. We combined Artificial Intelligence (AI) and DNA methylation analysis of circulating cell-free tumor DNA (ctDNA), to identify putative biomarkers for and to elucidate the pathogenesis of LC.

Methods

Illumina Infinium MethylationEPIC BeadChip array analysis was used to measure cytosine (CpG) methylation changes across the genome in LC. Six different AI platforms including support vector machine (SVM) and Deep Learning (DL) were used to identify CpG biomarkers and for LC detection. Training set and validation sets were generated, and 10-fold cross validation performed. Gene enrichment analysis using g:profiler and GREAT enrichment was used to elucidate the LC pathogenesis.

Results

Using a stringent GWAS significance threshold, p-value <5x10-8, we identified 4389 CpGs (cytosine methylation loci) in coding genes and 1812 CpGs in non-protein coding DNA regions that were differentially methylated in LC. SVM and three other AI platforms achieved an AUC=1.00; 95% CI (0.90-1.00) for LC detection. DL achieved an AUC=1.00; 95% CI (0.95-1.00) and 100% sensitivity and specificity. High diagnostic accuracies were achieved with only intragenic or only intergenic CpG loci. Gene enrichment analysis found dysregulation of molecular pathways involved in the development of small cell and non-small cell LC.

Conclusion

Using AI and DNA methylation analysis of ctDNA, high LC detection rates were achieved. Further, many of the genes that were epigenetically altered are known to be involved in the biology of neoplasms in general and lung cancer in particular.
Nomogram Predicts the Role of Primary Tumor Surgery on De Novo Stage-IV Breast Cancer Patients: A SEER-Based Competing Risk Analysis Model
Authors: Cui Hanxiao , Dai Luyao , Bao Yuanhang , Hu Liqun , Zhou Zhangjian , Wang Meng , Lin Shuai , Wu Hao , Ma Xiaobin , Kang Huafeng
Published: May 2022

Objective

The efficacy of primary tumor surgery on survival in female patients with de novo stage IV breast cancer (BC) remains unclear. Our study endeavored to develop comprehensive competing risk nomograms to predict clinical outcomes and guide precision treatment in these patients.

Participants and Methods

A total of 12281 patients who had distant metastasis at initial BC diagnosis between 2010 and 2017 in the Surveillance Epidemiology and End Results (SEER) database, were enrolled in this study. First, we assessed the impacts of primary tumor surgery on overall survival (OS) and breast cancer-specific survival (BCSS) using the Kaplan-Meier curves. Then subgroup analyses stratified by different metastatic patterns were performed using Cox and competing risk models (CRM). Based on the filtered independent prognostic parameters by CRM, we established two nomograms to predict the probability of breast cancer-specific death (BCSD) at 1-,2- and 3-year intervals. Furthermore, calibration curves and area under the curves (AUC) were conducted for validation.

Results

Kaplan-Meier analysis revealed that surgery was associated with better OS and BCSS (P<0.001). Subgroup analyses demonstrated that in bone-only metastases pattern, relative to breast-conserving surgery (BCS), patients receiving mastectomy had worse prognosis and the poorest survival belonged to non-surgery individuals (BCSS: mastectomy: HR=1.35; 95%CI=1.15-1.60; non-surgery: 2.42; 2.08-2.82; OS: mastectomy: 1.44; 1.23-1.68; non-surgery: 2.40; 2.08-2.78). Additionally, no survival difference was observed between BCS and reconstruction recipients (BCSS: HR=1.10; 95%CI=0.85-1.43; OS: 1.11; 0.86-1.44). Furthermore, patients undergoing BCS possessed similar BCSS with mastectomy recipients as well as reconstruction recipients in viscera metastases pattern, whereas non-surgery individuals had a worse survival (mastectomy: HR=1.04; 95%CI=0.92-1.18; reconstruction: 0.86; 0.69-1.06; non-surgery: 1.83; 1.63-2.05). Two competing risk nomograms of distinct metastatic patterns were established to comprehensively predict the survival of patients. Calibration curves indicated the terrific consistency of the models. Moreover, the AUC values in the training and validation sets were in the range of 0.70–0.80, exhibiting good specificity and sensitivity.

Conclusion

The surgery implementation was associated with a lower probability of BCSD in de novo stage-IV BC patients. Our nomograms could offer a relatively accurate and individualized prediction of the cumulative incidence rate of BCSD after primary tumor resection.
Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI
Authors: Hallinan James Thomas Patrick Decourcy , Zhu Lei , Zhang Wenqiao , Lim Desmond Shi Wei , Baskar Sangeetha , Low Xi Zhen , Yeong Kuan Yuen , Teo Ee Chin , Kumarakulasinghe Nesaretnam Barr , Yap Qai Ven , Chan Yiong Huak , Lin Shuxun , Tan Jiong Hao , Kumar Naresh , Vellayappan Balamurugan A. , Ooi Beng Chin , Quek Swee Tian , Makmur Andrew
Published: May 2022

Background

Metastatic epidural spinal cord compression (MESCC) is a devastating complication of advanced cancer. A deep learning (DL) model for automated MESCC classification on MRI could aid earlier diagnosis and referral.

Purpose

To develop a DL model for automated classification of MESCC on MRI.

Materials and Methods

Patients with known MESCC diagnosed on MRI between September 2007 and September 2017 were eligible. MRI studies with instrumentation, suboptimal image quality, and non-thoracic regions were excluded. Axial T2-weighted images were utilized. The internal dataset split was 82% and 18% for training/validation and test sets, respectively. External testing was also performed. Internal training/validation data were labeled using the Bilsky MESCC classification by a musculoskeletal radiologist (10-year experience) and a neuroradiologist (5-year experience). These labels were used to train a DL model utilizing a prototypical convolutional neural network. Internal and external test sets were labeled by the musculoskeletal radiologist as the reference standard. For assessment of DL model performance and interobserver variability, test sets were labeled independently by the neuroradiologist (5-year experience), a spine surgeon (5-year experience), and a radiation oncologist (11-year experience). Inter-rater agreement (Gwet’s kappa) and sensitivity/specificity were calculated.

Results

Overall, 215 MRI spine studies were analyzed [164 patients, mean age = 62 ± 12(SD)] with 177 (82%) for training/validation and 38 (18%) for internal testing. For internal testing, the DL model and specialists all showed almost perfect agreement (kappas = 0.92–0.98, p < 0.001) for dichotomous Bilsky classification (low versus high grade) compared to the reference standard. Similar performance was seen for external testing on a set of 32 MRI spines with the DL model and specialists all showing almost perfect agreement (kappas = 0.94–0.95, p < 0.001) compared to the reference standard.

Conclusion

A DL model showed comparable agreement to a subspecialist radiologist and clinical specialists for the classification of malignant epidural spinal cord compression and could optimize earlier diagnosis and surgical referral.
Engineering Cancer/Testis Antigens With Reversible S-Cationization to Evaluate Antigen Spreading
Authors: Miyamoto Ai , Honjo Tomoko , Masui Mirei , Kinoshita Rie , Kumon Hiromi , Kakimi Kazuhiro , Futami Junichiro
Published: May 2022

Serum autoantibody to cancer/testis antigens (CTAs) is a critical biomarker that reflects the antitumor immune response. Quantitative and multiplexed anti-CTA detection arrays can assess the immune status in tumors and monitor therapy-induced antitumor immune reactions. Most full-length recombinant CTA proteins tend to aggregate. Cysteine residue-specific S-cationization techniques facilitate the preparation of water-soluble and full-length CTAs. Combined with Luminex technology, we designed a multiple S-cationized antigen-immobilized bead array (MUSCAT) assay system to evaluate multiple serum antibodies to CTAs. Reducible S-alkyl-disulfide-cationized antigens in cytosolic conditions were employed to develop rabbit polyclonal antibodies as positive controls. These control antibodies sensitively detected immobilized antigens on beads and endogenous antigens in human lung cancer-derived cell lines. Rabbit polyclonal antibodies successfully confirmed the dynamic ranges and quantitative MUSCAT assay results. An immune monitoring study was conducted using the serum samples on an adenovirus−mediated REIC/Dkk−3 gene therapy clinical trial that showed a successful clinical response in metastatic castration-resistant prostate cancer. Autoantibody responses were closely related to clinical outcomes. Notably, upregulation of anti-CTA responses was monitored before tumor regression. Thus, quantitative monitoring of anti-CTA antibody biomarkers can be used to evaluate the cancer-immunity cycle. A quality-certified serum autoantibody monitoring system is a powerful tool for developing and evaluating cancer immunotherapy.
RNA Therapeutic Options to Manage Aberrant Signaling Pathways in Hepatocellular Carcinoma: Dream or Reality?
Authors: Sartorius Kurt , Antwi Samuel O. , Chuturgoon Anil , Roberts Lewis R. , Kramvis Anna
Published: May 2022

Despite the early promise of RNA therapeutics as a magic bullet to modulate aberrant signaling in cancer, this field remains a work-in-progress. Nevertheless, RNA therapeutics is now a reality for the treatment of viral diseases (COVID-19) and offers great promise for cancer. This review paper specifically investigates RNAi as a therapeutic option for HCC and discusses a range of RNAi technology including anti-sense oligonucleotides (ASOs), Aptamers, small interfering RNA (siRNA), ribozymes, riboswitches and CRISPR/Cas9 technology. The use of these RNAi based interventions is specifically outlined in three primary strategies, namely, repressing angiogenesis, the suppression of cell proliferation and the promotion of apoptosis. We also discuss some of the inherent chemical and delivery problems, as well as targeting issues and immunogenic reaction to RNAi interventions.
Osteoarticular Infections in Pediatric Hospitals in Europe: A Prospective Cohort Study From the EUCLIDS Consortium
Authors: Trobisch Andreas , Schweintzger Nina A. , Kohlfürst Daniela S. , Sagmeister Manfred G. , Sperl Matthias , Grisold Andrea J. , Feierl Gebhard , Herberg Jethro A. , Carrol Enitan D. , Paulus Stephane C. , Emonts Marieke , van der Flier Michiel , de Groot Ronald , Cebey-López Miriam , Rivero-Calle Irene , Boeddha Navin P. , Agapow Paul-Michael , Secka Fatou , Anderson Suzanne T. , Behrends Uta , Wintergerst Uwe , Reiter Karl , Martinon-Torres Federico , Levin Michael , Zenz Werner ,   The EUCLIDS consortium
Published: May 2022

Background

Pediatric osteoarticular infections (POAIs) are serious diseases requiring early diagnosis and treatment.

Methods

In this prospective multicenter cohort study, children with POAIs were selected from the European Union Childhood Life-threatening Infectious Diseases Study (EUCLIDS) database to analyze their demographic, clinical, and microbiological data.

Results

A cohort of 380 patients with POAIs, 203 with osteomyelitis (OM), 158 with septic arthritis (SA), and 19 with both OM and SA, was analyzed. Thirty-five patients were admitted to the Pediatric Intensive Care Unit; out of these, six suffered from shock, one needed an amputation of the right foot and of four left toes, and two had skin transplantation. According to the Pediatric Overall Performance Score, 36 (10.5%) showed a mild overall disability, 3 (0.8%) a moderate, and 1 (0.2%) a severe overall disability at discharge. A causative organism was detected in 65% (247/380) of patients.Staphylococcus aureus(S. aureus) was identified in 57.1% (141/247) of microbiological confirmed cases, including 1 (0.7%) methicillin-resistantS. aureus(MRSA) and 6 (4.2%) Panton-Valentine leukocidin (PVL)-producingS. aureus, followed by Group AStreptococcus(18.2%) andKingella kingae(8.9%).K. kingaeand PVL production inS. aureuswere less frequently reported than expected from the literature.

Conclusion

POAIs are associated with a substantial morbidity in European children, withS. aureusbeing the major detected pathogen. In one-third of patients, no causative organism is identified. Our observations show an urgent need for the development of a vaccine againstS. aureusand for the development of new microbiologic diagnostic guidelines for POAIs in European pediatric hospitals.
The Potential of Chitosan in Nanomedicine: An Overview of the Cytotoxicity of Chitosan Based Nanoparticles
Authors: Frigaard Julie , Jensen Janicke Liaaen , Galtung Hilde Kanli , Hiorth Marianne
Published: May 2022

The unique properties and applications of nanotechnology in targeting drug delivery, cosmetics, fabrics, water treatment and food packaging have received increased focus the last two decades. The application of nanoparticles in medicine is rapidly evolving, requiring careful investigation of toxicity before clinical use. Chitosan, a derivative of the natural polysaccharide chitin, has become increasingly relevant in modern medicine because of its unique properties as a nanoparticle. Chitosan is already widely used as a food additive and in food packaging, bandages and wound dressings. Thus, with an increasing application worldwide, cytotoxicity assessment of nanoparticles prepared from chitosan is of great interest. The purpose of this review is to provide an updated status of cytotoxicity studies scrutinizing the safety of chitosan nanoparticles used in biomedical research. A search in Ovid Medline from 23 March 1998 to 4 January 2022, with the combination of the search words Chitosan or chitosan, nanoparticle or nano particle or nanosphere or nanocapsule or nano capsule, toxicology or toxic or cytotoxic and mucosa or mucous membrane resulted in a total of 88 articles. After reviewing all the articles, those involving non-organic nanoparticles and cytotoxicity assays conducted exclusively on nanoparticles with anti-tumor effect (i.e., having cytotoxic effect) were excluded, resulting in 70 articles. Overall, the chitosan nanoparticles included in this review seem to express low cytotoxicity regardless of particle composition or cytotoxicity assay and cell line used for testing. Nonetheless, all new chitosan derivatives and compositions are recommended to undergo careful characterization and cytotoxicity assessment before being implemented on the market.
Investigation of the Uptake and Transport of Aspirin Eugenol Ester in the Caco-2 Cell Model
Authors: Tao Qi , Qin Zhe , Liu Xi-Wang , Zhang Zhen-Dong , Li Shi-Hong , Bai Li-Xia , Li Jian-Yong , Yang Ya-Jun
Published: May 2022

Background: Aspirin eugenol ester (AEE) is a novel medicinal compound synthesized by esterification of aspirin with eugenol using the prodrug principle. AEE has the pharmacological activities of being anti-inflammatory, antipyretic, analgesic, anti-cardiovascular diseases, and anti-oxidative stress However, its oral bioavailability is poor, and its intestinal absorption and transport characteristics are still unknown.

Objective: The purpose of this study was to investigate the uptake and transport mechanisms of AEE in Caco-2 cells.

Methods: The effects of time, concentration, and temperature on the transport and uptake of AEE were studied.

Results: The results showed that a higher concentration of salicylic acid (SA) was detected in the supernatant of cell lysates and cell culture medium, while AEE was not detected. Therefore, the content change of AEE was expressed as the content change of its metabolite SA. In the uptake experiment, when the factors of time, concentration, and temperature were examined, the uptake of SA reached the maximum level within 30 min, and there was concentration dependence. In addition, low temperature (4°C) could significantly reduce the uptake of SA in Caco-2 cells. In the transport experiment, under the consideration of time, concentration, and temperature, the transepithelial transport of SA from AP-BL and BL-AP sides was time-dependent. The amount of SA transported in Caco-2 cells increased with the increase of concentration, but the transmembrane transport rate had no correlation with the concentration. This phenomenon may be due to the saturation phenomenon of high concentration. The efflux ratio (ER) was less than 1, which indicated that their intestinal transport mechanism was passive transport. Moreover, the temperature had a significant effect on the transport of AEE.

Conclusion: In summary, intestinal absorption of AEE through Caco-2 cell monolayers was related to passive transport. The uptake and transport of AEE were concentration-dependent, and temperature significantly affected their uptake and transport. The absorption and transport characteristics of AEE may contribute to the exploration of mechanisms of absorption and transport of chemosynthetic drugs in vitro.
Optimization and Performance Evaluation of Foam Discharge Agent for Deep Aquatic Condensate Gas Well
Authors: Ge Lei , Cui Hailin , Li Yingchao , Sui Xiuan
Published: May 2022

The block deep condensate gas reservoir in the basin in the southeast of the South China Sea is a bottom water reservoir and is producing in the late effusion, which faces problems such as scaling, condensate oil–water two-phase flow, and low temperature at the subsea wellhead. The mud line for this kind of gas-well has characteristics including high condensate content in low temperature, high downhole temperature, and injection with a foam discharge agent and scale inhibitor. In this article, the influence of low temperature and scale inhibitor is considered for the first time, and a dynamic liquid-carrying experiment for the optimization and performance evaluation of foam discharge agents was carried out according to these characteristics. The experimental results show that the optimized foam discharge agent, ZHY-01, has good resistance to high temperature and condensate oil, and the optimal concentration of the foam discharge agent is recommended to be 0.25%. Under this concentration, the liquid-carrying capacity of the foam discharge agent decreases slightly by 10.17% at low temperature. The scale inhibitor MA/AA reduced the liquid-carrying capacity by 11.86%, and the scale inhibitor PESA reduced the liquid-carrying capacity by 10.17%. The research results in this article have certain reference significance for the chemical screening and evaluation of the foam drainage gas production process in deep-water condensate gas wells.
On the Role of Molecular Polarizability in Positron Coupling to Vibrations in Homonuclear Diatomics
Authors: Poveda Luis A. , Mohallem Jose R.
Published: May 2022

In a previous work [Poveda, Varella, and Mohallem (Poveda et al., Atoms, 2021, 9: 64) it was shown that the bell-like shape of the 0 → 1 vibrational excitation cross section of H2 as a function of the incoming positron energy, with its characteristic sharp onset at threshold, can be accounted for by a simple model which couples the positron to the vibrational mode of the molecule, throught the behavior of the target polarizabitity with the internuclear bond distance. The study, carried out via time-dependent wave-packet dynamics propagation, relies on a two-dimensional potential energy surface involving just the scattering (positron-target) and vibrational (target) coordinates. Here the model is extended to the full three-dimensional configuration space of the positron-diatomic complex, with the cross sections computed within a time-independent close-coupling approach. The present results confirm the previous findings, shedding light on the mechanisms through which a low-energy positron couples to the molecular vibrations.