bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Acid Whey on the Lipid Composition and Oxidative Stability of Organic Uncured Fermented Bacon after Production and during Chilling Storage
Authors: Okoń Anna , Szymański Piotr , Zielińska Dorota , Szydłowska Aleksandra , Siekierko Urszula , Kołożyn-Krajewska Danuta , Dolatowski Zbigniew J.
Published: October 2021

The aim of this research was to evaluate the effect of acid whey on changes in the fatty acid profile, oxidative stability, physico-chemical parameters, and microbiological and sensory quality of traditional organic uncured fermented Polish bacon after production and during chilling storage. Three different treatments of fermented bacon were produced: C—control bacon with a nitrite curing mixture; T—bacon with a nitrate curing mixture; and AW—bacon with acid whey and NaCl. The acid whey used in the production of uncured fermented pork bacon positively changed the sensorial characteristics, directly after the ripening process, and had a positive effect in terms of a decrease in the pH of the product. All of the fermented bacon treatments in general were of good microbiological quality. A higher lactic acid bacteria (LAB) level was observed in the AW treatment after the fermentation process, and the bacteria number did not change during storage, whereas in the C and T treatments, the LAB level increased during storage (p < 0.05). The application of acid whey did not limit the formation of secondary oxidation products (TBARS) during bacon ripening (1.68 mg MDA kg−1), but had a reduced value during storage time (0.73 mg MDA kg−1). The highest polyunsaturated fatty acid (PUFA) levels, after ripening and after four weeks of refrigerated storage, were found in the C treatment. In the AW treatment, it was found that the PUFA level increased; likewise, the content of n-3 and n-6 fatty acids increased, while saturated fatty acids (SFAs) decreased during storage (p < 0.05). The opposite tendency was observed in the C treatment. After four weeks of storage, the PUFA/SFA ratio was the lowest in the nitrate treatment, and higher values of the PUFA/SFA ratio were obtained in the acid whey and nitrite treatment (p < 0.05).
Developing a Measuring System for Monitoring the Thickness of the 6 m Wide HDPE/LDPE Polymer Geomembrane with Its Continuous Flow Using Automation Equipment
Authors: Nikonova Tatyana , Zharkevich Olga , Dandybaev Essim , Baimuldin Murat , Daich Leonid , Sichkarenko Andrey , Kotov Evgeniy
Published: October 2021

As a result of R&D, a measuring system for controlling the thickness of the HDPE/LDPE (high-density polyethylene/low-density polyethylene) polymer geomembrane was developed using automation equipment. The relevance of this work consists of the development of a domestic, relatively inexpensive system for controlling the thickness of the HDPE/LDPE polymer geomembrane in production conditions based on modern equipment for enterprise automation. The scientific novelty consists of the use of original design solutions in the development of hardware and software complex mechanisms that allow controlling the thickness of the HDPE/LDPE polymer geomembrane layers along the entire width of the shaft, excluding deformation of the film as a result of foreign bodies entering during extrusion, cuts, monitoring the quality of the film in real time, as well as the possibility of analyzing the measured parameters in the database of the automated system.
Behaviour Investigation of SMA-Equipped Bar Hysteretic Dampers Using Machine Learning Techniques
Authors: Farhangi Visar , Jahangir Hashem , Eidgahee Danial Rezazadeh , Karimipour Arash , Javan Seyed Alireza Nedaei , Hasani Hamed , Fasihihour Nazanin , Karakouzian Moses
Published: October 2021

Most isolators have numerous displacements due to their low stiffness and damping properties. Accordingly, the supplementary damping systems have vital roles in damping enhancement and lower the isolation system displacement. Nevertheless, in many cases, even by utilising additional dampers in isolation systems, the occurrence of residual displacement is inevitable. To address this issue, in this study, a new smart type of bar hysteretic dampers equipped with shape memory alloy (SMA) bars with recentring features, as the supplementary damper, is introduced and investigated. In this regard, 630 numerical models of SMA-equipped bar hysteretic dampers (SMA-BHDs) were constructed based on experimental samples with different lengths, numbers, and cross sections of SMA bars. Furthermore, by utilising hysteresis curves and the corresponding ideal bilinear curves, the role of geometrical and mechanical parameters in the cyclic behaviour of SMA-BHDs was examined. Due to the deficiency of existing analytical models, proposed previously for steel bar hysteretic dampers (SBHDs), to estimate the first yield point displacement and post-yield stiffness ratio in SMA-BHDs accurately, new models were developed by the artificial neural network (ANN) and group method of data handling (GMDH) approaches. The results showed that, although the ANN models outperform GMDH ones, both ANN- and GMDH-based models can accurately estimate the linear and nonlinear behaviour of SMA-BHDs in pre- and post-yield parts with low errors and high accuracy and consistency.
An Experimental Study on the Mechanical Properties of a High Damping Rubber Bearing with Low Shape Factor
Authors: Gu Zhenyuan , Lei Yahui , Qian Wangping , Xiang Ziru , Hao Fangzheng , Wang Yi
Published: October 2021

A high damping rubber bearing (HDRB) is widely utilized in base-isolation structures due to its good energy dissipation capacity and environmentally friendly properties; however, it is incapable of isolating the vertical vibration caused by earthquakes and subways effectively. Thick rubber bearings with a low shape factor have become one of the important vertical isolation forms. This paper provides an experimental comparative study on high damping rubber bearings with low shape factor (HDRB-LSF), thick lead–rubber bearings (TLRB), and lead–rubber bearings (LRB). The abilities of the bearing and energy dissipation of the above bearings are analyzed contrastively considering the influence of vertical pressure, loading frequency, shear strain, and pre-pressure. Firstly, the HDRB-LSF, TLRB, and LRB are designed according to the Chinese Code for seismic design of buildings. Secondly, cyclic vertical compression tests and horizontal shear tests, as well as their correlation tests, are conducted, respectively. The vibrational characteristics and hysteresis feature of these three bearings are critically compared. Thirdly, a corrected calculation of vertical stiffness for the thick rubber bearings is proposed based on the experimental data to provide a more accurate and realistic tool measuring the vertical mechanical properties of rubber bearings. The test results proved that the HDRB-LSF has the most advanced performance of the three bearings. For the fatigue property, the hysteresis curves of the HDRB-LSF along with TLRB are plump both horizontally and vertically, thus providing a good energy dissipation effect. Regarding vertical stiffness, results from different loading cases show that the designed HDRB-LSF possesses a better vertical isolation effect and preferable environmental protection than LRB, a larger bearing capacity, and, similarly, a more environmentally friendly property than TLRB. Hence, it can avoid the unfavorable resonance effect caused by vertical periodic coupling within the structure. All the experimental data find that the proposed corrected equation can calculate the vertical stiffness of bearings with a higher accuracy. This paper presents the results of an analytical, parametric study that aimed to further explore the low shape factor concepts of rubber bearings applied in three-dimensional isolation for building structures.
Phosphine-Free-Synthesized ZnSe/ZnS Core/Shell Quantum Dots for White Light-Emitting Diodes
Authors: Byambasuren Nyamsuren , Jo Jiyeon , Ko Hyungduk , Ju Byeong-Kwon , Byun Ji Young , Jang Ho Seong
Published: October 2021

Blue-light-emitting ZnSe core (C) and ZnSe/ZnS core/shell (C/S) quantum dots (QDs) were synthesized with phosphine-free precursors by a thermal decomposition method in paraffin oil solvent and applied to QD-converted light-emitting diodes (LEDs). The optical properties of the synthesized ZnSe C and ZnSe/ZnS C/S QDs were characterized by absorption spectroscopy and photoluminescence spectroscopy. Additionally, the quantum efficiency of the QDs was investigated. Their structural properties were studied with X-ray crystallography and transmission electron microscopy. The ZnSe/ZnS C/S QDs showed deep-blue light peaking at 425 nm. The blue-light-emitting ZnSe/ZnS C/S QDs were used as color-converting materials for near-ultraviolet LED-pumped blue LEDs and combined with yellow-light-emitting Zn-Cu-In-S/ZnS C/S QDs to fabricate white LEDs. The white LEDs showed warm white light [(CIE x, CIE y) = (0.4088, 0.3987)], Tc = 3488 K, and Ra = 61.2]. The results indicate that the ZnSe/ZnS C/S QDs have good potential for white light application after further improvements to their optical properties.
Causality Mining in Natural Languages Using Machine and Deep Learning Techniques: A Survey
Authors: Ali Wajid , Zuo Wanli , Ali Rahman , Zuo Xianglin , Rahman Gohar
Published: October 2021

The era of big textual corpora and machine learning technologies have paved the way for researchers in numerous data mining fields. Among them, causality mining (CM) from textual data has become a significant area of concern and has more attention from researchers. Causality (cause-effect relations) serves as an essential category of relationships, which plays a significant role in question answering, future events predication, discourse comprehension, decision making, future scenario generation, medical text mining, behavior prediction, and textual prediction entailment. While, decades of development techniques for CM are still prone to performance enhancement, especially for ambiguous and implicitly expressed causalities. The ineffectiveness of the early attempts is mainly due to small, ambiguous, heterogeneous, and domain-specific datasets constructed by manually linguistic and syntactic rules. Many researchers have deployed shallow machine learning (ML) and deep learning (DL) techniques to deal with such datasets, and they achieved satisfactory performance. In this survey, an effort has been made to address a comprehensive review of some state-of-the-art shallow ML and DL approaches in CM. We present a detailed taxonomy of CM and discuss popular ML and DL approaches with their comparative weaknesses and strengths, applications, popular datasets, and frameworks. Lastly, the future research challenges are discussed with illustrations of how to transform them into productive future research directions.
A Data Loss Recovery Technique Using EMD-BiGRU Algorithm for Structural Health Monitoring
Authors: Liu Die , Bao Yihao , He Yingying , Zhang Likai
Published: October 2021

Missing data caused by sensor faults is a common problem in structural health monitoring systems. Due to negative effects, many methods that adopt measured data to infer missing data have been proposed to tackle this problem in previous studies. However, capturing complex correlations from measured data remains a significant challenge. In this study, empirical mode decomposition (EMD) combined with a bidirectional gated recurrent unit (BiGRU) is proposed for the recovery of the measured data. The proposed EMD-BiGRU converts the missing data task as predicted task of time sequence. The core of the method is to predict missing data using the raw data and decomposed subsequence as the decomposed subsequence can improve the predicted accuracy. In addition, the BiGRU in the hybrid model can extract the pre-post correlations of subsequence compared with traditional artificial neural networks. Raw acceleration data collected from a three-story structure are used to evaluate the performance of the EMD-BiGRU for missing data imputation. The recovery results of measure data show that the EMD-BiGRU exhibits excellent performance from two perspectives. First, the decomposed subsequence can improve the accuracy of the BiGRU predicted model. Second, the BiGRU outperforms other machine learning algorithms because it captures more microscopic changes of measured data. The experimental analysis suggests that the change patterns of raw measured signal data are complex, and therefore it is significant to extract the features before modeling.
Gastrointestinal Tumors: Phytochemical and Drug Combinations Targeting the Hallmarks of Cancer
Authors: Scarpa Emanuele Salvatore , Giammanco Marco , Magnani Mauro
Published: October 2021

Cancer is a worldwide burden resulting in millions of deaths each year. In particular, gastrointestinal tumors are life-threatening malignancies and one of the leading reasons for death in developed countries. Phytochemicals can be found in grains, vegetables, fruits and several foods. Many phytochemicals, such as curcumin, genistein, luteolin, vitexin-2-O-xyloside, avenanthramides, quercetin, epigallocatechin-3-gallate (EGCG), resveratrol, sulforaphane, piperine and thymoquinone have been used in combination with different chemotherapeutic agents for their synergistic anticancer effects against various forms of cancer. In this review, we describe the antitumor properties and biological effects of combinations of phytochemicals and anticancer drugs against gastrointestinal tumors: colon cancer, gastric cancer, liver cancer, pancreatic cancer. We focus on the molecular pathways, oncoproteins and tumor suppressors modulated by the combination of phytochemicals with antitumor drugs and on the biomarkers of the hallmarks of cancer influenced by these therapeutic strategies in cancer cell lines, xenograft models and clinical trials. The increased knowledge of biomarkers and molecular pathways regulated by the combination of phytochemicals and conventional anticancer drugs in both in vitro and in vivo models will remarkably improve the efficacy of these therapeutic strategies against gastrointestinal tumors in future innovative clinical applications.
U-Vectors: Generating Clusterable Speaker Embedding from Unlabeled Data
Authors: Mridha Muhammad Firoz , Ohi Abu Quwsar , Monowar Muhammad Mostafa , Hamid Md. Abdul , Islam Md. Rashedul , Watanobe Yutaka
Published: October 2021

Speaker recognition deals with recognizing speakers by their speech. Most speaker recognition systems are built upon two stages, the first stage extracts low dimensional correlation embeddings from speech, and the second performs the classification task. The robustness of a speaker recognition system mainly depends on the extraction process of speech embeddings, which are primarily pre-trained on a large-scale dataset. As the embedding systems are pre-trained, the performance of speaker recognition models greatly depends on domain adaptation policy, which may reduce if trained using inadequate data. This paper introduces a speaker recognition strategy dealing with unlabeled data, which generates clusterable embedding vectors from small fixed-size speech frames. The unsupervised training strategy involves an assumption that a small speech segment should include a single speaker. Depending on such a belief, a pairwise constraint is constructed with noise augmentation policies, used to train AutoEmbedder architecture that generates speaker embeddings. Without relying on domain adaption policy, the process unsupervisely produces clusterable speaker embeddings, termed unsupervised vectors (u-vectors). The evaluation is concluded in two popular speaker recognition datasets for English language, TIMIT, and LibriSpeech. Also, a Bengali dataset is included to illustrate the diversity of the domain shifts for speaker recognition systems. Finally, we conclude that the proposed approach achieves satisfactory performance using pairwise architectures.
Sequential Riemann–Liouville and Hadamard–Caputo Fractional Differential Equation with Iterated Fractional Integrals Conditions
Authors: Ntouyas Sotiris K. , Sitho Surang , Khoployklang Teerasak , Tariboon Jessada
Published: October 2021

In the present research, we initiate the study of boundary value problems for sequential Riemann–Liouville and Hadamard–Caputo fractional derivatives, supplemented with iterated fractional integral boundary conditions. Firstly, we convert the given nonlinear problem into a fixed point problem by considering a linear variant of the given problem. Once the fixed point operator is available, we use a variety of fixed point theorems to establish results regarding existence and uniqueness. Some properties of iteration that will be used in our study are also discussed. Examples illustrating our main results are also constructed. At the end, a brief conclusion is given. Our results are new in the given configuration and enrich the literature on boundary value problems for fractional differential equations.
Superiority of Multiple-Joint Space Width over Minimum-Joint Space Width Approach in the Machine Learning for Radiographic Severity and Knee Osteoarthritis Progression
Authors: Cheung James Chung-Wai , Tam Andy Yiu-Chau , Chan Lok-Chun , Chan Ping-Keung , Wen Chunyi
Published: October 2021

We compared the prediction efficiency of the multiple-joint space width (JSW) and the minimum-JSW on knee osteoarthritis (KOA) severity and progression by using a deep learning approach. A convolutional neural network (CNN) with ResU-Net architecture was developed for knee X-ray imaging segmentation and has attained a segmentation efficiency of 98.9% intersection over union (IoU) on the distal femur and proximal tibia. Later, by leveraging the image segmentation, the minimum and multiple-JSWs in the tibiofemoral joint were estimated and then validated by radiologist measurements in the Osteoarthritis Initiative (OAI) dataset using Pearson correlation and Bland–Altman plots. The agreement between the CNN-based estimation and radiologist’s measurement of minimum-JSWs reached 0.7801 (p < 0.0001). The estimated JSWs were deployed to predict the radiographic severity and progression of KOA defined by Kellgren-Lawrence (KL) grades using the XGBoost model. The 64-point multiple-JSWs achieved the best performance in predicting KOA progression within 48 months, with the area-under-receiver operating characteristic curve (AUC) of 0.621, outperforming the commonly used minimum-JSW with 0.554 AUC. We provided a fully automated radiographic assessment tool for KOA with comparable performance to the radiologists and showed that the fine-grained measurement of multiple-JSWs yields superior prediction performance for KOA over the minimum-JSW.
Magnetic Resonance Assessment of Ejection Fraction Versus Echocardiography for Cardioverter-Defibrillator Implantation Eligibility
Authors: Schiau Călin , Leucuța Daniel-Corneliu , Dudea Sorin Marian , Manole Simona
Published: October 2021

Background: The aim of this study was to investigate the potential impact of performing two-dimensional echocardiography (2DE) compared to cardiovascular magnetic resonance (CMR) for left ventricular ejection fraction (LVEF) on implantable cardioverter defibrillator (ICD) eligibility. Methods: A prospective cohort of 166 consecutive patients with nonischemic cardiomyopathy (NICM) was designed to compare transthoracic 2DE and CMR imaging. Results: Echocardiography measurements have important differences and large limits of agreement compared to CMR, especially when assessing ventricle volumes, and smaller but relevant differences when assessing LVEF. The agreement between CMR and 2DE regarding the identification of subjects with EF <= 35, respectively <= 30, and thus eligible for an ICD measured by Cohen’s Kappa was 0.78 (95% CI: 0.68–0.88), p < 0.001, respectively 0.65 (95% CI: 0.52–0.78), p < 0.001. The disagreement represented 7.9%/11.3% of the subjects who had EF < 35%/< 30% as observed by CMR, who would have been classified as eligible for an ICD, resulting in an additional need to use an ICD. Moreover, 2.6%/3.3% would have been deemed eligible by echocardiography for an ICD. Conclusions: These measurement problems result in incorrect assignments of eligibility that may have serious implications on the quality of life and the prevention of death events for patients assessed for eligibility of an ICD.
Nucleic Acids Analytical Methods for Viral Infection Diagnosis: State-of-the-Art and Future Perspectives
Authors: Sciuto Emanuele Luigi , Leonardi Antonio Alessio , Calabrese Giovanna , Luca Giovanna De , Coniglio Maria Anna , Irrera Alessia , Conoci Sabrina
Published: October 2021

The analysis of viral nucleic acids (NA), DNA or RNA, is a crucial issue in the diagnosis of infections and the treatment and prevention of related human diseases. Conventional nucleic acid tests (NATs) require multistep approaches starting from the purification of the pathogen genetic material in biological samples to the end of its detection, basically performed by the consolidated polymerase chain reaction (PCR), by the use of specialized instruments and dedicated laboratories. However, since the current NATs are too constraining and time and cost consuming, the research is evolving towards more integrated, decentralized, user-friendly, and low-cost methods. These will allow the implementation of massive diagnoses addressing the growing demand of fast and accurate viral analysis facing such global alerts as the pandemic of coronavirus disease of the recent period. Silicon-based technology and microfluidics, in this sense, brought an important step up, leading to the introduction of the genetic point-of-care (PoC) systems. This review goes through the evolution of the analytical methods for the viral NA diagnosis of infection diseases, highlighting both advantages and drawbacks of the innovative emerging technologies versus the conventional approaches.
fMRI Acoustic Noise Enhances Parasympathetic Activity in Humans
Authors: Schuler Anna-Lisa , Pellegrino Giovanni
Published: October 2021

Background: Functional magnetic resonance imaging (fMRI) is one of the most important neuroimaging techniques; nevertheless, the acoustic noise of the MR scanner is unavoidably linked to the process of data acquisition. We hypothesized that the auditory noise of the scanner has an effect on autonomic activity. Methods: We measured heart rate variability (HRV) while exposing 30 healthy subjects to fMRI noise. In doing so, we demonstrated an increase in parasympathetic nervous system (PNS) activity compared to silence and white noise and a decrease in sympathetic nervous system (SNS) activity compared to white noise. Conclusions: The influence of MR scanner noise on the autonomic nervous system should be taken into account when performing fMRI experiments.
The Urokinase Receptor (uPAR) as a “Trojan Horse” in Targeted Cancer Therapy: Challenges and Opportunities
Authors: Metrangolo Virginia , Ploug Michael , Engelholm Lars H.
Published: October 2021

One of the largest challenges to the implementation of precision oncology is identifying and validating selective tumor-driving targets to enhance the therapeutic efficacy while limiting off-target toxicity. In this context, the urokinase-type plasminogen activator receptor (uPAR) has progressively emerged as a promising therapeutic target in the management of aggressive malignancies. By focalizing the plasminogen activation cascade and subsequent extracellular proteolysis on the cell surface of migrating cells, uPAR endows malignant cells with a high proteolytic and migratory potential to dissolve the restraining extracellular matrix (ECM) barriers and metastasize to distant sites. uPAR is also assumed to choreograph multiple other neoplastic stages via a complex molecular interplay with distinct cancer-associated signaling pathways. Accordingly, high uPAR expression is observed in virtually all human cancers and is frequently associated with poor patient prognosis and survival. The promising therapeutic potential unveiled by the pleiotropic nature of this receptor has prompted the development of distinct targeted intervention strategies. The present review will focus on recently emerged cytotoxic approaches emphasizing the novel technologies and related limits hindering their application in the clinical setting. Finally, future research directions and emerging opportunities in the field of uPAR targeting are also discussed.
Significant Inter- and Intralaboratory Variation in Gleason Grading of Prostate Cancer: A Nationwide Study of 35,258 Patients in The Netherlands
Authors: Flach Rachel N. , Willemse Peter-Paul M. , Suelmann Britt B. M. , Deckers Ivette A. G. , Jonges Trudy N. , van Dooijeweert Carmen , van Diest Paul J. , Meijer Richard P.
Published: October 2021

Purpose: Our aim was to analyze grading variation between pathology laboratories and between pathologists within individual laboratories using nationwide real-life data. Methods: We retrieved synoptic (n = 13,397) and narrative (n = 29,377) needle biopsy reports from the Dutch Pathology Registry and prostate-specific antigen values from The Netherlands Cancer Registration for prostate cancer patients diagnosed between January 2017 and December 2019. We determined laboratory-specific proportions per histologic grade and unadjusted odds ratios (ORs) for International Society of Urological Pathologists Grades 1 vs. 2–5 for 40 laboratories due to treatment implications for higher grades. Pathologist-specific proportions were determined for 21 laboratories that consented to this part of analysis. The synoptic reports of 21 laboratories were used for analysis of case-mix correction for PSA, age, year of diagnosis, number of biopsies and positive cores. Results: A total of 38,321 reports of 35,258 patients were included. Grade 1 ranged between 19.7% and 44.3% per laboratory (national mean = 34.1%). Out of 40 laboratories, 22 (55%) reported a significantly deviant OR, ranging from 0.48 (95% confidence interval (CI) 0.39–0.59) to 1.54 (CI 1.22–1.93). Case-mix correction was performed for 10,294 reports, altering the status of 3/21 (14%) laboratories, but increasing the observed variation (20.8% vs. 17.7%). Within 15/21 (71%) of laboratories, significant inter-pathologist variation existed. Conclusion: Substantial variation in prostate cancer grading was observed between and within Dutch pathology laboratories. Case-mix correction did not explain the variation. Better standardization of prostate cancer grading is warranted to optimize and harmonize treatment.
PARP Inhibitors in Combination with Radiotherapy: To Do or Not to Do?
Authors: Barcellini Amelia , Loap Pierre , Murata Kazutoshi , Villa Riccardo , Kirova Youlia , Okonogi Noriyuki , Orlandi Ester
Published: October 2021

Background: Despite the large use of inhibitors of Poly-ADP ribose polymerase (PARP-I), the feasibility and safety of their combination with radiotherapy (RT) is unclear. Aim: We conducted a literature analysis with the aim to evaluate the efficacy and safety profile of a combination with RT and PARP-I. Method: The key issues for the current review were expressed in two questions according to the Population, Intervention, Control, Outcome (PICO) criteria: 1. What is the outcome and 2. What is the toxicity in patients treated with a combination of PARP-I and RT for a newly diagnosed or recurrent tumors? Results: A total of 12 clinical studies met the inclusion criteria including seven single-arm dose-escalation phase I studies, two phase II (two- and three-arms controlled trials) trials, one parallel-arm phase I study, and two phase I/II studies published between 2015 and 2021. RT was performed with photon beams and several schedules according to the clinical situation. The acute toxicity ≥ grade 3 ranged between 25% and >96%, which was divided into hematological or non-hematological adverse events. Conclusions: despite the heterogeneity of the evaluated patient populations and tumor types, and the limited number of the studies, this review suggests that a combination approach is feasible even though the efficacy profile remains unclear.
The Epithelial and Stromal Immune Microenvironment in Gastric Cancer: A Comprehensive Analysis Reveals Prognostic Factors with Digital Cytometry
Authors: Shen Wenjun , Wang Guoyun , Cooper Georgia R. , Jiang Yuming , Zhou Xin
Published: October 2021

Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Tumor heterogeneity continues to confound researchers’ understanding of tumor growth and the development of an effective therapy. Digital cytometry allows interpretation of heterogeneous bulk tissue transcriptomes at the cellular level. We built a novel signature matrix to dissect epithelium and stroma signals using a scRNA-seq data set (GSE134520) for GC and then applied cell mixture deconvolution to estimate diverse epithelial, stromal, and immune cell proportions from bulk transcriptome data in four independent GC cohorts (GSE62254, GSE15459, GSE84437, and TCGA-STAD) from the GEO and TCGA databases. Robust computational methods were applied to identify strong prognostic factors for GC. We identified an EMEC population whose proportions were significantly higher in patients with stage I cancer than other stages, and it was predominantly present in tumor samples but not typically found in normal samples. We found that the ratio of EMECs to stromal cells and the ratio of adaptive T cells to monocytes were the most significant prognostic factors within the non-immune and immune factors, respectively. The STEM score, which unifies these two prognostic factors, was an independent prognostic factor of overall survival (HR = 0.92, 95% CI = 0.89–0.94, p=2.05×10−9). The entire GC cohort was stratified into three risk groups (high-, moderate-, and low-risk), which yielded incremental survival times (p<0.0001). For stage III disease, patients in the moderate- and low-risk groups experienced better survival benefits from radiation therapy ((HR = 0.16, 95% CI = 0.06–0.4, p<0.0001), whereas those in the high-risk group did not (HR = 0.49, 95% CI = 0.14–1.72, p=0.25). We concluded that the STEM score is a promising prognostic factor for gastric cancer.
Screening Leads to Overestimated Associations of Thyroid Dysfunction and Thyroiditis with Thyroid Cancer Risk
Authors: Song Young , Kim Kyung-Soo , Kim Soo-Kyung , Cho Yong-Wook , Choi Hyo
Published: October 2021

We aimed to assess the relationships of functional thyroid disease and thyroiditis with subsequent thyroid cancer, which is controversial due to various confounders, and the effect of thyroid disease workup on this association. We used the cohort data from 2002 to 2015 (Study I, n = 28,330) and the entire data from 2002 to 2019 (Study II, n = 883,074) of the Korean National Health Insurance Service database, and performed logistic regression and subgroup analyses with various covariates. In Study I, hypothyroidism, thyroiditis, autoimmune thyroiditis, hyperthyroidism, and Graves’ disease showed positive associations with thyroid cancer. In Study II, after adjustment for covariates including the number of thyroid function tests, the ORs for thyroid cancer were significantly reduced in all thyroid diseases. Hypothyroidism, thyroiditis, and autoimmune thyroiditis were positively associated (adjusted odds ratio, OR (95% confidence interval, CI) 1.28 (1.25–1.32), 1.36 (1.31–1.42), and 1.17 (1.11–1.24), respectively), whereas hyperthyroidism and Graves’ disease were negatively associated with thyroid cancer (adjusted OR (95% CI) 0.80 (0.77–0.83) and 0.69 (0.65–0.74), respectively). Multiple subgroup analyses in both studies showed consistent results. In this large population-based, nationwide study, we confirmed that thyroid disease workup leads to overestimation of associations of thyroid dysfunction and thyroiditis with thyroid cancer risk.
Immunotherapy in Medulloblastoma: Current State of Research, Challenges, and Future Perspectives
Authors: Voskamp Marije J. , Li Shuang , van Daalen Kim R. , Crnko Sandra , ten Broeke Toine , Bovenschen Niels
Published: October 2021

Medulloblastoma (MB), a primary tumor of the central nervous system, is among the most prevalent pediatric neoplasms. The median age of diagnosis is six. Conventional therapies include surgical resection of the tumor with subsequent radiation and chemotherapy. However, these therapies often cause severe brain damage, and still, approximately 75% of pediatric patients relapse within a few years. Because the conventional therapies cause such severe damage, especially in the pediatric developing brain, there is an urgent need for better treatment strategies such as immunotherapy, which over the years has gained accumulating interest. Cancer immunotherapy aims to enhance the body’s own immune response to tumors and is already widely used in the clinic, e.g., in the treatment of melanoma and lung cancer. However, little is known about the possible application of immunotherapy in brain cancer. In this review, we will provide an overview of the current consensus on MB classification and the state of in vitro, in vivo, and clinical research concerning immunotherapy in MB. Based on existing evidence, we will especially focus on immune checkpoint inhibition and CAR T-cell therapy. Additionally, we will discuss challenges associated with these immunotherapies and relevant strategies to overcome those.
Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging
Authors: Mittal Paul , Condina Mark R. , Klingler-Hoffmann Manuela , Kaur Gurjeet , Oehler Martin K. , Sieber Oliver M. , Palmieri Michelle , Kommoss Stefan , Brucker Sara , McDonnell Mark D. , Hoffmann Peter
Published: October 2021

Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can determine the spatial distribution of analytes such as protein distributions in a tissue section according to their mass-to-charge ratio. Here, we explored the clinical potential of machine learning (ML) applied to MALDI MSI data for cancer diagnostic classification using tissue microarrays (TMAs) on 302 colorectal (CRC) and 257 endometrial cancer (EC)) patients. ML based on deep neural networks discriminated colorectal tumour from normal tissue with an overall accuracy of 98% in balanced cross-validation (98.2% sensitivity and 98.6% specificity). Moreover, our machine learning approach predicted the presence of lymph node metastasis (LNM) for primary tumours of EC with an accuracy of 80% (90% sensitivity and 69% specificity). Our results demonstrate the capability of MALDI MSI for complementing classic histopathological examination for cancer diagnostic applications.
Cutaneotrichosporon oleaginosus: A Versatile Whole-Cell Biocatalyst for the Production of Single-Cell Oil from Agro-Industrial Wastes
Authors: Di Fidio Nicola , Minonne Filippo , Antonetti Claudia , Raspolli Galletti Anna Maria
Published: October 2021

Cutaneotrichosporon oleaginosus is an oleaginous yeast with several favourable qualities: It is fast growing, accumulates high amounts of lipids and has a very broad substrate spectrum. Its resistance to hydrolysis by-products makes it a promising biocatalyst for custom tailored microbial oils. C. oleaginosus can accumulate up to 60 wt.% of its biomass as lipids. This species is able to grow by using several compounds as a substrate, such as acetic acid, biodiesel-derived glycerol, N-acetylglucosamine, lignocellulosic hydrolysates, wastepaper and other agro-industrial wastes. This review is focused on state-of-the-art innovative and sustainable biorefinery schemes involving this promising yeast and second- and third-generation biomasses. Moreover, this review offers a comprehensive and updated summary of process strategies, biomass pretreatments and fermentation conditions for enhancing lipid production by C. oleaginosus as a whole-cell biocatalyst. Finally, an overview of the main industrial applications of single-cell oil is reported together with future perspectives.
Deactivation and Regeneration Method for Ni Catalysts by H2S Poisoning in CO2 Methanation Reaction
Authors: Ahn Jeongyoon , Chung Woojin , Chang Soonwoong
Published: October 2021

The carbon dioxide (CO2) methanation reaction is a process that produces methane (CH4) by reacting CO2 and H2. Many studies have been conducted on this process because it enables a reduction of greenhouse gases and the production of energy with carbon neutrality. Moreover, it also exhibits a higher efficiency at low temperatures due to its thermodynamic characteristics; thus, there have been many studies, particularly on the catalysts that are driven at low temperatures and have high durability. However, with regards to employing this process in actual industrial processes, studies on both toxic substances that can influence catalyst performance and regeneration are still insufficient. Therefore, in this paper, the activity of a Ni catalyst before and after hydrogen sulfide (H2S) exposure was compared and an in-depth analysis was conducted to reveal the activity performance through the regeneration treatment of the poisoned catalyst. This study observed the reaction activity changes when injecting H2S during the CO2 + H2 reaction to evaluate the toxic effect of H2S on the Ni-Ce-Zr catalyst, in which the results indicate that the reaction activity decreases rapidly at 220 °C. Next, this study also successfully conducted a regeneration of the Ni-Ce-Zr catalyst that was poisoned with H2S by applying H2 heat treatment. It is expected that the results of this study can be used as fundamental data in an alternative approach to performance recovery when a small amount of H2S is included in the reaction gas of industrial processes (landfill gas, fire extinguishing tank gas, etc.) that can be linked to CO2 methanation.
Thickness-Dependent Photocatalysis of Ultra-Thin MoS2 Film for Visible-Light-Driven CO2 Reduction
Authors: Huang Yi-Fan , Liao Kuan-Wei , Fahmi Fariz Rifqi Zul , Modak Varad A. , Tsai Shang-Hsuan , Ke Shang-Wei , Wang Chen-Hao , Chen Li-Chyong , Chen Kuei-Hsien
Published: October 2021

The thickness of transition metal dichalcogenides (TMDs) plays a key role in enhancing their photocatalytic CO2 reduction activity. However, the optimum thickness of the layered TMDs that is required to achieve sufficient light absorption and excellent crystallinity has still not been definitively determined. In this work, ultra-thin molybdenum disulfide films (MoS2TF) with 25 nm thickness presented remarkable photocatalytic activity, and the product yield increased by about 2.3 times. The photocatalytic mechanism corresponding to the TMDs’ thickness was also proposed. This work demonstrates that the thickness optimization of TMDs provides a cogent direction for the design of high-performance photocatalysts.
Dissecting the Crosstalk between Endothelial Mitochondrial Damage, Vascular Inflammation, and Neurodegeneration in Cerebral Amyloid Angiopathy and Alzheimer’s Disease
Authors: Parodi-Rullán Rebecca M. , Javadov Sabzali , Fossati Silvia
Published: October 2021

Alzheimer’s disease (AD) is the most prevalent cause of dementia and is pathologically characterized by the presence of parenchymal senile plaques composed of amyloid β (Aβ) and intraneuronal neurofibrillary tangles of hyperphosphorylated tau protein. The accumulation of Aβ also occurs within the cerebral vasculature in over 80% of AD patients and in non-demented individuals, a condition called cerebral amyloid angiopathy (CAA). The development of CAA is associated with neurovascular dysfunction, blood–brain barrier (BBB) leakage, and persistent vascular- and neuro-inflammation, eventually leading to neurodegeneration. Although pathologically AD and CAA are well characterized diseases, the chronology of molecular changes that lead to their development is still unclear. Substantial evidence demonstrates defects in mitochondrial function in various cells of the neurovascular unit as well as in the brain parenchyma during the early stages of AD and CAA. Dysfunctional mitochondria release danger-associated molecular patterns (DAMPs) that activate a wide range of inflammatory pathways. In this review, we gather evidence to postulate a crucial role of the mitochondria, specifically of cerebral endothelial cells, as sensors and initiators of Aβ-induced vascular inflammation. The activated vasculature recruits circulating immune cells into the brain parenchyma, leading to the development of neuroinflammation and neurodegeneration in AD and CAA.
Additive Manufacturing of Caffeic Acid-Inspired Mineral Trioxide Aggregate/Poly-ε-Caprolactone Scaffold for Regulating Vascular Induction and Osteogenic Regeneration of Dental Pulp Stem Cells
Authors: Tien Ni , Lee Jian-Jr , Lee Alvin Kai-Xing , Lin Yen-Hong , Chen Jian-Xun , Kuo Ting-You , Shie Ming-You
Published: October 2021

Mineral trioxide aggregate (MTA) is a common biomaterial used in endodontics regeneration due to its antibacterial properties, good biocompatibility and high bioactivity. Surface modification technology allows us to endow biomaterials with the necessary biological targets for activation of specific downstream functions such as promoting angiogenesis and osteogenesis. In this study, we used caffeic acid (CA)-coated MTA/polycaprolactone (PCL) composites and fabricated 3D scaffolds to evaluate the influence on the physicochemical and biological aspects of CA-coated MTA scaffolds. As seen from the results, modification of CA does not change the original structural characteristics of MTA, thus allowing us to retain the properties of MTA. CA-coated MTA scaffolds were shown to have 25% to 55% higher results than bare scaffold. In addition, CA-coated MTA scaffolds were able to significantly adsorb more vascular endothelial growth factors (p < 0.05) secreted from human dental pulp stem cells (hDPSCs). More importantly, CA-coated MTA scaffolds not only promoted the adhesion and proliferation behaviors of hDPSCs, but also enhanced angiogenesis and osteogenesis. Finally, CA-coated MTA scaffolds led to enhanced subsequent in vivo bone regeneration of the femur of rabbits, which was confirmed using micro-computed tomography and histological staining. Taken together, CA can be used as a potently functional bioactive coating for various scaffolds in bone tissue engineering and other biomedical applications in the future.
Expression of Endogenous Putative TSH Binding Protein in Orbit
Authors: Draman Mohd Shazli , Grennan-Jones Fiona , Taylor Peter , Muller Ilaria , Evans Sam , Haridas Anjana , Morris Daniel S. , Rees D. Aled , Lane Carol , Dayan Colin , Zhang Lei , Ludgate Marian
Published: October 2021

Thyroid stimulating antibodies (TSAB) cause Graves’ disease and contribute to Graves’ Orbitopathy (GO) pathogenesis. We hypothesise that the presence of TSH binding proteins (truncated TSHR variants (TSHRv)) and/or nonclassical ligands such as thyrostimulin (α2β5) might provide a mechanism to protect against or exacerbate GO. We analysed primary human orbital preadipocyte-fibroblasts (OF) from GO patients and people free of GO (non-GO). Transcript (QPCR) and protein (western blot) expression levels of TSHRv were measured through an adipogenesis differentiation process. Cyclic-AMP production by TSHR activation was studied using luciferase-reporter and RIA assays. After differentiation, TSHRv levels in OF from GO were significantly higher than non-GO (p = 0.039), and confirmed in ex vivo analysis of orbital adipose samples. TSHRv western blot revealed a positive signal at 46 kDa in cell lysates and culture media (CM) from non-GO and GO-OF. Cyclic-AMP decreased from basal levels when OF were stimulated with TSH or Monoclonal TSAB (M22) before differentiation protocol, but increased in differentiated cells, and was inversely correlated with the TSHRv:TSHR ratio (Spearman correlation: TSH r = −0.55, p = 0.23, M22 r = 0.87, p = 0.03). In the bioassay, TSH/M22 induced luciferase-light was lower in CM from differentiated GO-OF than non-GO, suggesting that secreted TSHRv had neutralised their effects. α2 transcripts were present but reduced during adipogenesis (p < 0.005) with no difference observed between non-GO and GO. β5 transcripts were at the limit of detection. Our work demonstrated that TSHRv transcripts are expressed as protein, are more abundant in GO than non-GO OF and have the capacity to regulate signalling via the TSHR.
Methods and Products for the Conservation of Vandalized Urban Art Murals
Authors: Macchia Andrea , Castro Margarida , Curbelo Claudia , Rivaroli Laura , Capriotti Sara , Vieira Eduarda , Moreira Patrícia , Ruffolo Silvestro Antonio , La Russa Mauro Francesco
Published: October 2021

The possibility of contemporary mural paintings to be “tagged” by vandals, with spray and/or markers, represents a serious problem for the conservation of urban art. The present study aims to define the applicability of a protective coating on murals’ surface to preserve them against vandalism. The research has been focused on anti-graffiti products currently used in the field of cultural heritage conservation. These products represent an optimum start point to preserve mural artwork from vandal actions. The commercially available anti-graffiti products have been compared with an innovative product, PRO-ART, specifically formulated by YOCOCU in collaboration with Pelicoat, for the conservation of murals. At the same time, it has tested the cleaning of contemporary murals by using different mixtures of solvents and surfactants. The experimentations have been carried out on external walls, followed by the conducting of in situ tests (application tests, empirical evaluations and colorimetric analysis), as well as laboratory investigations (contact angle and optical/electronic microscopy).
Quaternary Holey Carbon Nanohorns/SnO2/ZnO/PVP Nano-Hybrid as Sensing Element for Resistive-Type Humidity Sensor
Authors: Serban Bogdan-Catalin , Cobianu Cornel , Buiu Octavian , Bumbac Marius , Dumbravescu Niculae , Avramescu Viorel , Nicolescu Cristina Mihaela , Brezeanu Mihai , Radulescu Cristiana , Craciun Gabriel , Romanitan Cosmin , Comanescu Florin Constantin
Published: October 2021

In this study, a resistive humidity sensor for moisture detection at room temperature is presented. The thin film proposed as a critical sensing element is based on a quaternary hybrid nanocomposite CNHox//SnO2/ZnO/PVP (oxidated carbon nanohorns–tin oxide–zinc oxide–polyvinylpyrrolidone) at the w/w/w/w ratios of 1.5/1/1/1 and 3/1/1/1. The sensing structure consists of a Si/SiO2 dielectric substrate and interdigitated transducers (IDT) electrodes, while the sensing film layer is deposited through the drop-casting method. Morphology and composition of the sensing layers were investigated through scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), X-ray diffraction, and Raman spectroscopy. Each quaternary hybrid nanocomposite-based thin film’s relative humidity (RH) sensing capability was analyzed by applying a direct current with known intensity between two electrodes and measuring the voltage difference when varying the RH from 0% to 100% in a humid nitrogen atmosphere. While the sensor with CNHox/SnO2/ZnO/PVP at 1.5/1/1/1 as the sensing layer has the better performance in terms of sensitivity, the structure employing CNHox//SnO2/ ZnO/PVP at 3/1/1/1 (mass ratio) as the sensing layer has a better performance in terms of linearity. The contribution of each component of the quaternary hybrid nanocomposites to the sensing performance is discussed in relation to their physical and chemical properties. Several alternative sensing mechanisms were taken into consideration and discussed. Based on the measured sensing results, we presume that the impact of the p-type semiconductor behavior of CNHox, in conjunction with the swelling of the hydrophilic polymer, is dominant and leads to the overall increasing resistance of the sensing film.