bluuebunny/crossref_metadata_2025 huggingface dataset:
The Mean ApoC1 Serum Level in Postoperative Samples from Neurosurgical Patients Is Lower than in Preoperative Samples and during Chemotherapy
Authors: Hilbert Michelle , Kuzman Peter , Mueller Wolf C. , Nestler Ulf
Published: July 2022

Serum levels of apolipoprotein ApoC1 have been described in a number of systemic tumor entities as potential biomarkers, but little is known about ApoC1 in neurosurgical patients. A total of 230 serum samples from 96 patients were analyzed using an ELISA technique. Patient diagnoses comprised 70 glioblastomas WHO IV°, 10 anaplastic astrocytomas III°, one anaplastic oligodendroglioma III°, one oligodendroglioma II°, one diffuse astrocytoma II°, one pilocytic astrocytoma I°, and a single case of a spindle cell tumor without WHO grading, as well as 11 spinal interventions. The mean ApoC1 level of the 230 samples was 132.03 µg/mL (median 86.83, SD 292.91). In the 176 glioblastoma samples, the mean ApoC1 level was 130.0 µg/mL (median 86.23, SD 314.9), which was neither different from the whole group nor from patients with spinal interventions (215.1 μg/mL, median 63.6, SD 404.9). In the postoperative samples, the mean ApoC1 level was significantly lower (85.81 μg/mL) than in the preoperative samples (129.64 μg/mL) and in samples obtained during adjuvant chemotherapy (168.44 μg/mL). While absolute ApoC1 serum levels in a patient do not allow for the distinction between neurosurgical histological entities, future analyses will examine whether the time course of ApoC1 in an individual patient can be related to certain treatment stages.
Multi-Omics and Integrative Approach towards Understanding Salinity Tolerance in Rice: A Review
Authors: Muthuramalingam Pandiyan , Jeyasri Rajendran , Rakkammal Kasinathan , Satish Lakkakula , Shamili Sasanala , Karthikeyan Adhimoolam , Valliammai Alaguvel , Priya Arumugam , Selvaraj Anthonymuthu , Gowri Pandiyan , Wu Qiang-Sheng , Karutha Pandian Shunmugiah , Shin Hyunsuk , Chen Jen-Tsung , Baskar Venkidasamy , Thiruvengadam Muthu , Akilan Manoharan , Ramesh Manikandan
Published: July 2022

Rice (Oryza sativa L.) plants are simultaneously encountered by environmental stressors, most importantly salinity stress. Salinity is the major hurdle that can negatively impact growth and crop yield. Understanding the salt stress and its associated complex trait mechanisms for enhancing salt tolerance in rice plants would ensure future food security. The main aim of this review is to provide insights and impacts of molecular-physiological responses, biochemical alterations, and plant hormonal signal transduction pathways in rice under saline stress. Furthermore, the review highlights the emerging breakthrough in multi-omics and computational biology in identifying the saline stress-responsive candidate genes and transcription factors (TFs). In addition, the review also summarizes the biotechnological tools, genetic engineering, breeding, and agricultural practicing factors that can be implemented to realize the bottlenecks and opportunities to enhance salt tolerance and develop salinity tolerant rice varieties. Future studies pinpointed the augmentation of powerful tools to dissect the salinity stress-related novel players, reveal in-depth mechanisms and ways to incorporate the available literature, and recent advancements to throw more light on salinity responsive transduction pathways in plants. Particularly, this review unravels the whole picture of salinity stress tolerance in rice by expanding knowledge that focuses on molecular aspects.
Effect of Treated Time of Hydrothermal Etching Process on Oxide Layer Formation and Its Antibacterial Properties
Authors: Lee Nayeon , Park Jooyoun , Miralami Raheleh , Yu Fei , Skaines Nikole , Armstrong Megan , McDonald Rachel , Moore Emily , Viveros Alicia , Borow Nicholas , Seo Keun Seok
Published: July 2022

Inspired by natural materials, we developed an antibacterial surface on titanium (Ti) using hydrothermal etching techniques and examined the effect of treated time on oxide layer formation, its antibacterial properties, and surface defects. Hydrothermal etching was conducted on Grade 2 commercially pure Ti immersed in 5M NaOH at 250 °C during a range of time of 0–12 h. Nanopillars generated on the surface had ~100 nm thickness, which resulted in decreased attachment and rupturing of the attached bacteria. The results also showed that 6 h and 8 h of etching time provided a desirable uniform nanopillar structure with the most effective prevention of bacterial adherence on the surface. Multiscale SEM observations revealed that the longer the etching was conducted, the more cracks propagated, which led to an increase in dissociated fragments of the oxide layer. In the 12 h of etching, a higher density of bacterial adherence was observed than that of the untreated and the shorter time treated samples, indicating that etching took longer than 10 h worsened the antibacterial properties of the nano-patterned surface of Ti. This study demonstrated that the optimal time duration is 6–8 h for the oxide layer formation to maximize antibacterial activity and minimize cracking formation on the surface. For future studies, we suggest exploring many possible conditions to generate a more uniform nanopattern without structural defects to secure the integration between a newly deposited oxide layer and the substrate.
Application and Progress of Chemometrics in Voltammetric Biosensing
Authors: Liu Jingjing , Xu Yifei , Liu Shikun , Yu Shixin , Yu Zhirun , Low Sze Shin
Published: July 2022

The voltammetric electrochemical sensing method combined with biosensors and multi-sensor systems can quickly, accurately, and reliably analyze the concentration of the main analyte and the overall characteristics of complex samples. Simultaneously, the high-dimensional voltammogram contains the rich electrochemical features of the detected substances. Chemometric methods are important tools for mining valuable information from voltammetric data. Chemometrics can aid voltammetric biosensor calibration and multi-element detection in complex matrix conditions. This review introduces the voltammetric analysis techniques commonly used in the research of voltammetric biosensor and electronic tongues. Then, the research on optimizing voltammetric biosensor results using classical chemometrics is summarized. At the same time, the incorporation of machine learning and deep learning has brought new opportunities to further improve the detection performance of biosensors in complex samples. Finally, smartphones connected with miniaturized voltammetric biosensors and chemometric methods provide a high-quality portable analysis platform that shows great potential in point-of-care testing.
Development of a Rapid Gold Nanoparticle-Based Lateral Flow Immunoassay for the Detection of Dengue Virus
Authors: Martinez-Liu Cynthia , Machain-Williams Carlos , Martinez-Acuña Natalia , Lozano-Sepulveda Sonia , Galan-Huerta Kame , Arellanos-Soto Daniel , Meléndez-Villanueva Mayra , Ávalos-Nolazco Diana , Pérez-Ibarra Katya , Galindo-Rodríguez Sergio , de Jesús Garza-Juarez Aurora , Rivas-Estilla Ana María
Published: July 2022

Flavivirus detection in humans and mosquito reservoirs has been an important issue since it can cause a variety of illnesses and could represent a health problem in geographical zones where the vector is endemic. In this work, we designed and characterized a biosensor based on gold nanoparticles (AuNPs) and antibody 4G2 for the detection of dengue virus (DENV) in vitro, obtaining different conjugates (with different antibody concentrations). The AuNP–4G2 conjugates at concentrations of 1, 3, and 6 µg/mL presented an increase in the average hydrodynamic diameter compared to the naked AuNPs. Also, as part of the characterization, differences in the UV-Vis absorbance spectrum and electrophoretic migration were observed between the conjugated AuNPs (with BSA or antibody) and naked AuNPs. Additionally, we used this biosensor (AuNP–4G2 conjugate with 3 µg/mL antibody) in the assembly of a competitive lateral flow assay (LFA) for the development of an alternative test to detect the flavivirus envelope protein in isolated DENV samples as a future tool for dengue detection (and other flaviviruses) in the mosquito vector (Aedesaegypti) for the identification of epidemic risk regions. Functionality tests were performed using Dengue virus 2 isolated solution (TCID50/mL = 4.58 × 103) as a positive sample and PBS buffer as a negative control. The results showed that it is possible to detect Dengue virus in vitro with this gold nanoparticle-based lateral flow assay with an estimated detection limit of 5.12 × 102 PFU. We suggest that this biosensor could be used as an additional detection tool by coupling it to different point-of-care tests (POCT) for the easy detection of other flaviviruses.
Experimental Investigation of Cross Laminated Timber Elements with Holes or Notches at In-Plane Beam Loading Conditions
Authors: Jeleč Mario , Damjanović Domagoj , Varevac Damir , Rajčić Vlatka
Published: July 2022

Environmental and urbanisation challenges have encouraged steady growth of mass timber structures where cross laminated timber (CLT) stands out in applications as full-size wall, floor, or beam elements. Beam elements are used mainly in situations where cross layers have a reinforcing effect on the tensile stress perpendicular to the beam axis, such as when introducing holes or notches, which is common practice in beams, due to engineering, installation, or architectural requirements. This paper presents experimental investigations of CLT beams with holes or notches for comparison and validation of an analytical model provided in the literature. Different sizes of holes and notches as well as different placements of the holes were considered in the experiments. All relevant failure modes were analysed and discussed in detail. Two predominant failure modes were indicated, i.e., bending failure and shear failure in crossing areas (mode III). Results further indicate that reduced lamination widths near the hole, notch, or element edges have a relatively small influence on the beam strength. Parametric studies indicate net shear failure (mode II) and tensile failure perpendicular to the beam axis as the critical failure modes in most of the considered cases, indicating their strong underestimation in design verifications according to the analytical model.
Current Trends in the Reconstruction and Rehabilitation of Jaw following Ablative Surgery
Authors: Pu Jane J. , Hakim Samer G. , Melville James C. , Su Yu-Xiong
Published: July 2022

The reconstruction and rehabilitation of jaws following ablative surgery have been transformed in recent years by the development of computer-assisted surgery and virtual surgical planning. In this narrative literature review, we aim to discuss the current state-of-the-art jaw reconstruction, and to preview the potential future developments. The application of patient-specific implants and the “jaw-in-a-day technique” have made the fast restoration of jaws’ function and aesthetics possible. The improved efficiency of primary reconstructive surgery allows for the rehabilitation of neurosensory function following ablative surgery. Currently, a great deal of research has been conducted on augmented/mixed reality, artificial intelligence, virtual surgical planning for soft tissue reconstruction, and the rehabilitation of the stomatognathic system. This will lead to an even more exciting future for the functional reconstruction and rehabilitation of the jaw following ablative surgery.
LncRNA-Associated Genetic Etiologies Are Shared between Type 2 Diabetes and Cancers in the UAE Population
Authors: Giordo Roberta , Gulsha Rida , Kalla Sarah , Calin George A. , Lipovich Leonard
Published: July 2022

Numerous epidemiological studies place patients with T2D at a higher risk for cancer. Many risk factors, such as obesity, ageing, poor diet and low physical activity, are shared between T2D and cancer; however, the biological mechanisms linking the two diseases remain largely unknown. The advent of genome wide association studies (GWAS) revealed large numbers of genetic variants associated with both T2D and cancer. Most significant disease-associated variants reside in non-coding regions of the genome. Several studies show that single nucleotide polymorphisms (SNPs) at or near long non-coding RNA (lncRNA) genes may impact the susceptibility to T2D and cancer. Therefore, the identification of genetic variants predisposing individuals to both T2D and cancer may help explain the increased risk of cancer in T2D patients. We aim to investigate whether lncRNA genetic variants with significant diabetes and cancer associations overlap in the UAE population. We first performed an annotation-based analysis of UAE T2D GWAS, confirming the high prevalence of variants at or near non-coding RNA genes. We then explored whether these T2D SNPs in lncRNAs were relevant to cancer. We highlighted six non-coding genetic variants, jointly reaching statistical significance in T2D and cancer, implicating a shared genetic architecture between the two diseases in the UAE population.
Predicting Active Sites in Photocatalytic Degradation Process Using an Interpretable Molecular-Image Combined Convolutional Neural Network
Authors: Jiang Zhuoying , Hu Jiajie , Samia Anna , Yu Xiong (Bill)
Published: July 2022

Machine-learning models have great potential to accelerate the design and performance assessment of photocatalysts, leveraging their unique advantages in detecting patterns and making predictions based on data. However, most machine-learning models are “black-box” models due to lack of interpretability. This paper describes the development of an interpretable neural-network model on the performance of photocatalytic degradation of organic contaminants by TiO2. The molecular structures of the organic contaminants are represented by molecular images, which are subsequently encoded by feeding into a special convolutional neural network (CNN), EfficientNet, to extract the critical structural features. The extracted features in addition to five other experimental variables were input to a neural network that was subsequently trained to predict the photodegradation reaction rates of the organic contaminants by TiO2. The results show that this machine-learning (ML) model attains a higher accuracy to predict the photocatalytic degradation rate of organic contaminants than a previously developed machine-learning model that used molecular fingerprint encoding. In addition, the most relevant regions in the molecular image affecting the photocatalytic rates can be extracted with gradient-weighted class activation mapping (Grad-CAM). This interpretable machine-learning model, leveraging the graphic interpretability of CNN model, allows us to highlight regions of the molecular structure serving as the active sites of water contaminants during the photocatalytic degradation process. This provides an important piece of information to understand the influence of molecular structures on the photocatalytic degradation process.
Advances in Enhancing the Stability of Cu-Based Catalysts for Methanol Reforming
Authors: Ye Runping , Xiao Shuwei , Lai Qinghua , Wang Dashan , Huang Yuanyuan , Feng Gang , Zhang Rongbin , Wang Tao
Published: July 2022

The advent of fuel cells has led to a series of studies on hydrogen production. As an excellent hydrogen carrier, methanol can be used for reforming to produce hydrogen. Copper-based catalysts have been widely used in methanol reforming due to their high catalytic activity and low-cost preparation. However, copper-based catalysts have been subjected to poor stability due to spontaneous combustion, sintering, and deactivation. Thus, the research on the optimization of copper-based catalysts is of great significance. This review analyzes several major factors that affect the stability of copper-based catalysts, and then comments on the progress made in recent years to improve the catalytic stability through various methods, such as developing preparation methods, adding promoters, and optimizing supports. A large number of studies have shown that sintering and carbon deposition are the main reasons for the deactivation of copper-based catalysts. It was found that the catalysts prepared by the modified impregnation method exhibit higher catalytic activity and stability. For the promoters and supports, it was also found that the doping of metal oxides such as MgO and bimetallic oxides such as CeO2-ZrO2 as the support could present better catalytic performance for the methanol reforming reaction. It is of great significance to discover some new materials, such as copper-based spinel oxide, with a sustained-release catalytic mechanism for enhancing the stability of Cu-based catalysts. However, the interaction mechanism between the metal and the support is not fully understood, and the research of some new material copper-based catalysts in methanol reforming has not been fully studied. These are the problems to be solved in the future.
Role of Circular RNA in Brain Tumor Development
Authors: Ahmed Swalih P. , Castresana Javier S. , Shahi Mehdi H.
Published: July 2022

Central nervous system tumors are a leading cause of cancer-related death in children and adults, with medulloblastoma (MB) and glioblastoma (GBM) being the most prevalent malignant brain tumors, respectively. Despite tremendous breakthroughs in neurosurgery, radiation, and chemotherapeutic techniques, cell heterogeneity and various genetic mutations impacting cell cycle control, cell proliferation, apoptosis, and cell invasion result in unwanted resistance to treatment approaches, with a 5-year survival rate of 70–80% for medulloblastoma, and the median survival time for patients with glioblastoma is only 15 months. Developing new medicines and utilizing combination medications may be viewed as excellent techniques for battling MB and GBM. Circular RNAs (circRNAs) can affect cancer-developing processes such as cell proliferation, cell apoptosis, invasion, and chemoresistance in this regard. As a result, several compounds have been introduced as prospective therapeutic targets in the fight against MB and GBM. The current study aims to elucidate the fundamental molecular and cellular mechanisms underlying the pathogenesis of GBM in conjunction with circRNAs. Several mechanisms were examined in detail, including PI3K/Akt/mTOR signaling, Wnt/-catenin signaling, angiogenic processes, and metastatic pathways, in order to provide a comprehensive knowledge of the involvement of circRNAs in the pathophysiology of MB and GBM.
Gremlin-1 Promotes Colorectal Cancer Cell Metastasis by Activating ATF6 and Inhibiting ATF4 Pathways
Authors: Li Ruohan , Zhou Huaixiang , Li Mingzhe , Mai Qiuyan , Fu Zhang , Jiang Youheng , Li Changxue , Gao Yunfei , Fan Yunping , Wu Kaiming , Costa Clive Da , Sheng Xia , He Yulong , Li Ningning
Published: July 2022

Cancer cell survival, function and fate strongly depend on endoplasmic reticulum (ER) proteostasis. Although previous studies have implicated the ER stress signaling network in all stages of cancer development, its role in cancer metastasis remains to be elucidated. In this study, we investigated the role of Gremlin-1 (GREM1), a secreted protein, in the invasion and metastasis of colorectal cancer (CRC) cells in vitro and in vivo. Firstly, public datasets showed a positive correlation between high expression of GREM1 and a poor prognosis for CRC. Secondly, GREM1 enhanced motility and invasion of CRC cells by epithelial–mesenchymal transition (EMT). Thirdly, GREM1 upregulated expression of activating transcription factor 6 (ATF6) and downregulated that of ATF4, and modulation of the two key players of the unfolded protein response (UPR) was possibly through activation of PI3K/AKT/mTOR and antagonization of BMP2 signaling pathways, respectively. Taken together, our results demonstrate that GREM1 is an invasion-promoting factor via regulation of ATF6 and ATF4 expression in CRC cells, suggesting GREM1 may be a potential pharmacological target for colorectal cancer treatment.
WWOX Controls Cell Survival, Immune Response and Disease Progression by pY33 to pS14 Transition to Alternate Signaling Partners
Authors: Liu Tsung-Yun , Nagarajan Ganesan , Chiang Ming-Fu , Huang Shenq-Shyang , Lin Tzu-Chia , Chen Yu-An , Sze Chun-I , Chang Nan-Shan
Published: July 2022

Tumor suppressor WWOX inhibits cancer growth and retards Alzheimer’s disease (AD) progression. Supporting evidence shows that the more strongly WWOX binds intracellular protein partners, the weaker is cancer cell growth in vivo. Whether this correlates with retardation of AD progression is unknown. Two functional forms of WWOX exhibit opposite functions. pY33-WWOX is proapoptotic and anticancer, and is essential for maintaining normal physiology. In contrast, pS14-WWOX is accumulated in the lesions of cancers and AD brains, and suppression of WWOX phosphorylation at S14 by a short peptide Zfra abolishes cancer growth and retardation of AD progression. In parallel, synthetic Zfra4-10 or WWOX7-21 peptide strengthens the binding of endogenous WWOX with intracellular protein partners leading to cancer suppression. Indeed, Zfra4-10 is potent in restoring memory loss in triple transgenic mice for AD (3xTg) by blocking the aggregation of amyloid beta 42 (Aβ42), enhancing degradation of aggregated proteins, and inhibiting activation of inflammatory NF-κB. In light of the findings, Zfra4-10-mediated suppression of cancer and AD is due, in part, to an enhanced binding of endogenous WWOX and its binding partners. In this perspective review article, we detail the molecular action of WWOX in the HYAL-2/WWOX/SMAD4 signaling for biological effects, and discuss WWOX phosphorylation forms in interacting with binding partners, leading to suppression of cancer growth and retardation of AD progression.
Management of Teeth Affected by Molar Incisor Hypomineralization Using a Resin Infiltration Technique—A Systematic Review
Authors: Bulanda Sylwia , Ilczuk-Rypuła Danuta , Dybek Anna , Pietraszewska Daria , Skucha-Nowak Małgorzata , Postek-Stefańska Lidia
Published: July 2022

In recent years, an increase in children diagnosed with molar incisor hypomineralization (MIH) has been observed. Children with MIH show a high failure rate with conservative treatment. The ICON® system (DMG, Hamburg, Germany), which is an infiltration of decalcified lesions with resin, may strengthen the tooth structure, improve its aesthetics, and cure hypersensitivity. The following article is a systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Scientific articles in the PubMed and Google Scholar databases describing the use of the ICON system in the treatment of MIH published in the years 2012–2022 were analyzed. Two independent study authors selected publications that show that the ICON system can be used during the treatment of children with MIH. So far, in the literature, there are no standardized protocols for the dental treatment of patients with hypomineralization of the incisors using the ICON system. Therefore, clinicians rarely use this method of treatment. The ICON system may be successfully used to infiltrate tooth decalcification in children with MIH. However, the depth of infiltration and the achievement of enamel hardness after such therapy are not precisely defined.
Parametrical Study on the Capillary Flowing Characteristics of the Parallel Microchannel Array
Authors: Xue Lihong , Guo Chunsheng , Zhang Yuankun , Xu Yanfeng , Li Baorui
Published: July 2022

The flow mechanism within a silicon-based micro heat sink plays a crucial role in two-phase thermal dissipation technology. In this study, the effect of geometrical properties on the flow behavior within a silicon-based array parallel microchannel as the evaporator of a silicon-based micro loop heat pipe (s-mLHP) is experimentally and numerically investigated. Here, three arrayed microchannels with different aspect ratio (AR) parameters (depth of 180 μm and AR of 6, 9, and 15) are specially fabricated. A visual experiment platform is established to observe and measure capillary properties of microchannels characterized by the suction distance. In addition, a validated numerical model (the maximum deviation less than 38.3%) is applied to simulate the flow characteristics of microchannels with different ARs. Numerical solutions show that the microchannel with ARs taken between 3 and 4 achieves the best capillary pumping performance within the studied range (suction distance up to 0.8 mm), which provides a theoretical basis for further exploration of silicon-based microchannel array with the optimal flow and thermal performance.
Steer by Image Technology for Intelligent Reflecting Surface Based on Reconfigurable Metasurface with Photodiodes as Tunable Elements
Authors: Rotshild David , Rozban Daniel , Rahamim Efi , Barom Asaf , Yosef Rotem , Bhanam Liel , Abramovich Amir
Published: July 2022

Lately, metasurface has become an essential and promising component in implementing Intelligent Reflecting Surface (IRS) for 5G and 6G. A novel method that simplifies the ability to reconfigure the metasurface is presented in this paper. The suggested technology uses a PIN photodiode as a tuning element. The desired image is projected on the metasurface’s backside, where the PIN photodiodes are placed and reconfigures the metasurface. The projected image’s color and intensity pattern influence the PIN photodiode’s junction capacitance, which leads to local reflection phase control. This enables the required pattern reflection phase distribution to manipulate the reflection beam, for example, 2D beam steering or focusing, and any other beam forming combination, instead of wiring many digital-to-analog converters (DACs) or FPGA outputs, which bias the standard tuning element such as PIN diode or varactor using a complex RF circuit. Using a PIN photodiode as a tunable element instead of a varactor diode, PIN diode, Liquid Crystal and MEMS allows the changing of the internal junction capacitance without direct contact and thus continuously controlling the reflection phase. In addition, an open circuit work mode with negligible energy consumption can be obtained. This technology can be used to implement metasurface based on discrete or continuous phases and is called Steer by Image (SBI). A full description of the SBI technology using PIN photodiode is presented in this paper.
Concrete Reinforced with Sisal Fibers (SSF): Overview of Mechanical and Physical Properties
Authors: Ahmad Jawad , Majdi Ali , Deifalla Ahmed Farouk , Ben Kahla Nabil , El-Shorbagy Mohammed A.
Published: July 2022

Concrete is a commonly used building material; however, it is subject to abrupt failure and limited energy absorption when yielding. The use of short discrete fibers has displayed a lot of potential in overcoming these issues. Sisal is a natural fiber that is renewable, inexpensive, and readily accessible. SSF is a potential reinforcement for use in concrete because of its cheap cost, low density, high specific strength and modulus, negligible health risk, easy accessibility in certain states, and renewability. In current centuries, there has been growing importance in discovering new uses for SSF-reinforced concrete, which is normally utilized to make ropes, mats, carpets, and other decorative items. This article gives an overview of current advancements in SSF and composites. The qualities of SSF, the interface between SSF and the matrix, and SSF-reinforced properties such as fresh, mechanical strength, and durability have all been examined. The results show that SSF increased strength and durability while decreasing its flowability. The review also provides suggestions for further work.
Triple-Negative Breast Cancer: A Review of Current Curative Intent Therapies
Authors: MacDonald Isaiah , Nixon Nancy A. , Khan Omar F.
Published: July 2022

Breast cancer is the most commonly diagnosed malignancy in women, with triple-negative breast cancer (TNBC) accounting for 10–20% of cases. Historically, fewer treatment options have existed for this subtype of breast cancer, with cytotoxic chemotherapy playing a predominant role. This article aims to review the current treatment paradigm for curative-intent TNBC, while also reviewing potential future developments in this landscape. In addition to chemotherapy, recent advances in the understanding of the molecular biology of TNBC have led to promising new studies of targeted and immune checkpoint inhibitor therapies in the curative-intent setting. The appropriate selection of TNBC patient subgroups with a higher likelihood of benefit from treatment is critical to identify the best treatment approach.
Mandibular Radiolucencies: A Differential Diagnosis of a Rare Tumor
Authors: Cabrera-Arcas Antonio , Montes-Carmona Jose-Francisco , Gonzalez-Perez Luis-Miguel
Published: July 2022

The diagnosis and treatment of maxillofacial cystic lesions requires careful evaluation and correlation of the clinical presentation and radiological studies. The Pindborg tumor, also known as the calcifying epithelial odontogenic tumor, is a locally invasive benign neoplasm, with only around 300 cases being published to date. This study presents a new case of this already uncommon neoplasm, not associated with an impacted tooth, and describes the clinicopathological features of this rare entity, along with a review of other reported cases. Despite surgery having been recognized as the treatment of choice for the Pindborg tumor, no firm consensus exists concerning the extension of surgical resection.
Impact of Diffuse Idiopathic Skeletal Hyperostosis on Clinico-Radiological Profiles and Prognosis for Thoracic Ossification of Ligamentum Flavum-Myelopathy: A Propensity-Matched Monocentric Analysis
Authors: Zhang Baoliang , Chen Guanghui , Chen Xi , Chen Zhongqiang , Sun Chuiguo
Published: July 2022

Background: Diffuse idiopathic skeletal hyperostosis (DISH) has been evaluated as a potential risk factor of poor surgical outcomes for lumbar spinal stenosis, whereas the influence of DISH on neuroimaging characteristics and postoperative prognosis of patients with thoracic myelopathy has not been established. Therefore, this study aimed to shed light on this issue. Methods: A monocentric study enrolled 167 eligible patients with thoracic ossification of ligamentum flavum (TOLF), who were followed up for at least 2 years. Clinico-radiological parameters and surgical outcomes were compared between the DISH+ and DISH− groups before and after propensity matching. Subgroup analysis was conducted to compare the functional outcomes between mild DISH (M-DISH) and moderately severe DISH (MS-DISH) groups. Results: Fifty-eight patients were diagnosed as DISH, and its prevalence was 34.7%. Patients with DISH presented with older age, more males, taller stature, heavier weight, more commonly diffuse-type TOLF (p < 0.05). The DISH group showed significantly worse recovery rate (RR) at the final follow-up before and after propensity matching (p < 0.01), and slightly lower preoperative VAS, higher postoperative VAS and lower VAS reduction, despite not reaching the significant differences. Subgroup analysis demonstrated that the M-DISH group was associated with the lower mJOA score (p = 0.01) and RR at the final follow-up (p = 0.001), and tended to present higher preoperative VAS than the MS-DISH group. Conclusions: DISH has a significant predisposition to the elderly males with diffuse-type TOLF. Although the presence of M-DISH might bring about a suboptimal surgical outcome, both DISH and non-DISH patients experienced good neurological function improvements and pain relief through thoracic posterior decompression.
A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls
Authors: De Muzio Federica , Grassi Francesca , Dell’Aversana Federica , Fusco Roberta , Danti Ginevra , Flammia Federica , Chiti Giuditta , Valeri Tommaso , Agostini Andrea , Palumbo Pierpaolo , Bruno Federico , Cutolo Carmen , Grassi Roberta , Simonetti Igino , Giovagnoni Andrea , Miele Vittorio , Barile Antonio , Granata Vincenza
Published: July 2022

Liver cancer is the sixth most detected tumor and the third leading cause of tumor death worldwide. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with specific risk factors and a targeted population. Imaging plays a major role in the management of HCC from screening to post-therapy follow-up. In order to optimize the diagnostic-therapeutic management and using a universal report, which allows more effective communication among the multidisciplinary team, several classification systems have been proposed over time, and LI-RADS is the most utilized. Currently, LI-RADS comprises four algorithms addressing screening and surveillance, diagnosis on computed tomography (CT)/magnetic resonance imaging (MRI), diagnosis on contrast-enhanced ultrasound (CEUS) and treatment response on CT/MRI. The algorithm allows guiding the radiologist through a stepwise process of assigning a category to a liver observation, recognizing both major and ancillary features. This process allows for characterizing liver lesions and assessing treatment. In this review, we highlighted both major and ancillary features that could define HCC. The distinctive dynamic vascular pattern of arterial hyperenhancement followed by washout in the portal-venous phase is the key hallmark of HCC, with a specificity value close to 100%. However, the sensitivity value of these combined criteria is inadequate. Recent evidence has proven that liver-specific contrast could be an important tool not only in increasing sensitivity but also in diagnosis as a major criterion. Although LI-RADS emerges as an essential instrument to support the management of liver tumors, still many improvements are needed to overcome the current limitations. In particular, features that may clearly distinguish HCC from cholangiocarcinoma (CCA) and combined HCC-CCA lesions and the assessment after locoregional radiation-based therapy are still fields of research.
Bayesian Depth-Wise Convolutional Neural Network Design for Brain Tumor MRI Classification
Authors: Ekong Favour , Yu Yongbin , Patamia Rutherford Agbeshi , Feng Xiao , Tang Qian , Mazumder Pinaki , Cai Jingye
Published: July 2022

In recent years, deep learning has been applied to many medical imaging fields, including medical image processing, bioinformatics, medical image classification, segmentation, and prediction tasks. Computer-aided detection systems have been widely adopted in brain tumor classification, prediction, detection, diagnosis, and segmentation tasks. This work proposes a novel model that combines the Bayesian algorithm with depth-wise separable convolutions for accurate classification and predictions of brain tumors. We combine Bayesian modeling learning and Convolutional Neural Network learning methods for accurate prediction results to provide the radiologists the means to classify the Magnetic Resonance Imaging (MRI) images rapidly. After thorough experimental analysis, our proposed model outperforms other state-of-the-art models in terms of validation accuracy, training accuracy, F1-score, recall, and precision. Our model obtained high performances of 99.03% training accuracy and 94.32% validation accuracy, F1-score, precision, and recall values of 0.94, 0.95, and 0.94, respectively. To the best of our knowledge, the proposed work is the first neural network model that combines the hybrid effect of depth-wise separable convolutions with the Bayesian algorithm using encoders.
FASSVid: Fast and Accurate Semantic Segmentation for Video Sequences
Authors: Portillo-Portillo Jose , Sanchez-Perez Gabriel , Toscano-Medina Linda K. , Hernandez-Suarez Aldo , Olivares-Mercado Jesus , Perez-Meana Hector , Velarde-Alvarado Pablo , Orozco Ana Lucila Sandoval , García Villalba Luis Javier
Published: July 2022

Most of the methods for real-time semantic segmentation do not take into account temporal information when working with video sequences. This is counter-intuitive in real-world scenarios where the main application of such methods is, precisely, being able to process frame sequences as quickly and accurately as possible. In this paper, we address this problem by exploiting the temporal information provided by previous frames of the video stream. Our method leverages a previous input frame as well as the previous output of the network to enhance the prediction accuracy of the current input frame. We develop a module that obtains feature maps rich in change information. Additionally, we incorporate the previous output of the network into all the decoder stages as a way of increasing the attention given to relevant features. Finally, to properly train and evaluate our methods, we introduce CityscapesVid, a dataset specifically designed to benchmark semantic video segmentation networks. Our proposed network, entitled FASSVid improves the mIoU accuracy performance over a standard non-sequential baseline model. Moreover, FASSVid obtains state-of-the-art inference speed and competitive mIoU results compared to other state-of-the-art lightweight networks, with significantly lower number of computations. Specifically, we obtain 71% of mIoU in our CityscapesVid dataset, running at 114.9 FPS on a single NVIDIA GTX 1080Ti and 31 FPS on the NVIDIA Jetson Nano embedded board with images of size 1024×2048 and 512×1024, respectively.
Revisiting the Dynamic Response of Chinese Price Level to Crude Oil Price Shocks Based on a Network Analysis Method
Authors: Sun Qingru , Wang Ze , Jia Nanfei
Published: July 2022

Crude oil price shocks have led to a fluctuation in commodity prices through the industrial chain and supply–demand relationships, which can substantially influence a country’s economy. In this paper, we propose a transmission model of oil price shocks to Chinese price levels and explore the direct and indirect impacts of crude oil price shocks on various Chinese price indices, combining the Granger causality test, impulse response function, and network analysis method. The empirical data are the Brent, WTI, Dubai, and Daqing spot crude oil prices and eight categories of Chinese price indices from January 2011 to March 2020. We found the following results: (1) Consumer price index (CPI) and the price index for means of agricultural production (MAPPI) cannot be directly impacted by crude oil price fluctuations, while they could be indirectly affected. (2) The duration and degree of the impacts of oil prices on each price index vary, and the export price index (EPI) is the most significantly affected. (3) The proportion of the indirect impact in the total impact of crude oil price shocks ranges from 0.03% to 100.00%. Thus, indirect influence cannot be ignored when analyzing the influence of crude oil price fluctuation on Chinese price level.
Quantum Oblivious Transfer: A Short Review
Authors: Santos Manuel B. , Mateus Paulo , Pinto Armando N.
Published: July 2022

Quantum cryptography is the field of cryptography that explores the quantum properties of matter. Generally, it aims to develop primitives beyond the reach of classical cryptography and to improve existing classical implementations. Although much of the work in this field covers quantum key distribution (QKD), there have been some crucial steps towards the understanding and development of quantum oblivious transfer (QOT). One can show the similarity between the application structure of both QKD and QOT primitives. Just as QKD protocols allow quantum-safe communication, QOT protocols allow quantum-safe computation. However, the conditions under which QOT is fully quantum-safe have been subject to intense scrutiny and study. In this review article, we survey the work developed around the concept of oblivious transfer within theoretical quantum cryptography. We focus on some proposed protocols and their security requirements. We review the impossibility results that daunt this primitive and discuss several quantum security models under which it is possible to prove QOT security.
A Fault Clearance and Restoration Approach for MMC-Based MTDC Grid
Authors: Alharbi Mohammed , Isik Semih , Alfaris Faris E. , Alkuhayli Abdulaziz , Bhattacharya Subhashish
Published: July 2022

With the growth in continuous energy demand, high-voltage Multi-Terminal DC (MTDC) systems are technically and economically feasible to transmit bulk power and integrate additional energy sources. However, the high vulnerability of the MTDC systems to DC faults, especially pole-to-pole (P2P) faults, is technically challenging. The development of DC fault ride-through techniques such as DC circuit breakers is still challenging due to their high cost and complex operation. This paper presents the DC fault clearance and isolation method for an MMC-based MTDC grid without adopting the high-cost DC circuit breakers. Besides, a restoration sequence is proposed to re-energize the DC grid upon clearing the fault. An MMC-based four-terminal DC grid is implemented in a Control-Hardware-in-Loop (CHIL) environment based on Xilinx Virtex-7 FPGAs and Real-Time Digital Simulator (RTDS). The RTDS results show that the MTDC system satisfactorily rides through DC faults and can safely recover after DC faults.
Detailed Power Loss Analysis of T-Type Neutral Point Clamped Converter for Reactive Power Compensation
Authors: Zygmanowski Marcin
Published: July 2022

The paper presents an analysis of power losses in a three-phase T-type neutral point clamped converter with insulated gate bipolar transistors. The paper’s main aim is to perform a detailed analysis of power losses in the converter operating as an active power filter. The study is based on the use of characteristics of semiconductor devices provided by the manufacturer in the module datasheet. Thanks to the analysis, it is possible to recognise the value of power losses, which facilitates the design of the converter cooling system. Identifying how power losses are distributed between the module switching devices is also possible. Power losses are shown as functions of the output current and module temperature. The analysis results were successfully verified by measuring power losses using a laboratory model of the converter with rated currents of 10 and 20 A. The obtained results indicate relatively low power losses and a relatively even distribution of power losses between the semiconductor devices. This is a superior feature of the three-level T-type neutral point clamped converter topology.
Assessing Lifestyle Transformations and Their Systemic Effects in Energy-System and Integrated Assessment Models: A Review of Current Methods and Data
Authors: Andreou Andreas , Fragkos Panagiotis , Fotiou Theofano , Filippidou Faidra
Published: July 2022

Achieving the ambitious climate targets required to limit global warming to 1.5 °C requires a deep transformation of the supply-and-demand side of energy–environmental–economic systems. Recent articles have shown that environmentally sustainable consumer behaviors driven by lifestyle changes can significantly contribute to climate-change mitigation and sustainable development goals. However, lifestyle changes are not adequately captured by scenarios developed with integrated assessment and energy-system models (IAMs/ESMs), which provide limited policy insights. This article conducts a systematic review of the IAM and ESM literature to identify the most important lifestyle changes in current mitigation pathways for the residential and transport sectors, review the employed state-of-the-art modeling approaches and scenario assumptions, and propose improvements to existing methodological frameworks. The review finds that mode shifts towards public transport and active transport modes, shared mobility, and eco-driving have the greatest impact in the transport sector, while actions that reduce space and water-heating requirements and the circular economy are the most effective practices in households. Common modeling approaches lack sophistication as they omit (1) the dynamics and costs of demand-side transitions, (2) the heterogenous responses of different consumer groups, and (3) the structural effects of lifestyles on the macro-economy. New approaches employing innovative methodologies combined with big data collected from users offer new avenues to overcome these challenges and improve the modeling of lifestyle changes in large-scale models.
Key Points and Current Studies on Seepage Theories of Marine Natural Gas Hydrate-Bearing Sediments: A Narrative Review
Authors: Peng Hao , Li Xiaosen , Chen Zhaoyang , Zhang Yu , You Changyu
Published: July 2022

The internal fluid flow capacity of hydrate-bearing sediment (HBS) is one of the important factors affecting the efficiency of natural gas exploitation. This paper focuses on seepage studies on gas hydrates with the following contents: scope of theories’ application, normalized permeability (Kt) models, extension combined with new technology, and development. No review has elucidated the prediction of original permeability (K0) of sediments without hydrates. Moreover, there are few studies on seepage theories with new technologies, such as Computed Tomography (CT), Nuclear Magnetic Resonance (NMR), Magnetic Resonance Imaging (MRI), and resistivity. However, this review summarizes the prospects, evolution, and application of HBS seepage theories from the perspectives of experiments, numerical simulation, and microscopic visualization. Finally, we discuss the current limitations and directions of the seepage theories of HBS.
Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach
Authors: Aaltonen Harri , Sierla Seppo , Kyrki Ville , Pourakbari-Kasmaei Mahdi , Vyatkin Valeriy
Published: July 2022

Battery storage is emerging as a key component of intelligent green electricitiy systems. The battery is monetized through market participation, which usually involves bidding. Bidding is a multi-objective optimization problem, involving targets such as maximizing market compensation and minimizing penalties for failing to provide the service and costs for battery aging. In this article, battery participation is investigated on primary frequency reserve markets. Reinforcement learning is applied for the optimization. In previous research, only simplified formulations of battery aging have been used in the reinforcement learning formulation, so it is unclear how the optimizer would perform with a real battery. In this article, a physics-based battery aging model is used to assess the aging. The contribution of this article is a methodology involving a realistic battery simulation to assess the performance of the trained RL agent with respect to battery aging in order to inform the selection of the weighting of the aging term in the RL reward formula. The RL agent performs day-ahead bidding on the Finnish Frequency Containment Reserves for Normal Operation market, with the objective of maximizing market compensation, minimizing market penalties and minimizing aging costs.
Recent Progress on Hydrogen Storage and Production Using Chemical Hydrogen Carriers
Authors: Pawelczyk Ewelina , Łukasik Natalia , Wysocka Izabela , Rogala Andrzej , Gębicki Jacek
Published: July 2022

Depleting fossil fuel resources and anthropogenic climate changes are the reasons for the intensive development of new, sustainable technologies based on renewable energy sources. One of the most promising strategies is the utilization of hydrogen as an energy vector. However, the limiting issue for large-scale commercialization of hydrogen technologies is a safe, efficient, and economical method of gas storage. In industrial practice, hydrogen compression and liquefaction are currently applied; however, due to the required high pressure (30–70 MPa) and low temperature (−253 °C), both these methods are intensively energy consuming. Chemical hydrogen storage is a promising alternative as it offers safe storage of hydrogen-rich compounds under ambient conditions. Although many compounds serving as hydrogen carriers are considered, some of them do not have realistic perspectives for large-scale commercialization. In this review, the three most technologically advanced hydrogen carriers—dimethyl ether, methanol, and dibenzyltoluene—are discussed and compared. Their potential for industrial application in relation to the energy storage, transport, and mobility sectors is analyzed, taking into account technological and environmental aspects.