bluuebunny/crossref_metadata_2025 huggingface dataset:
Shift in Tissue-Specific Immune Niches and CD137 Expression in Tuberculoma of Pembrolizumab-Treated Nasopharyngeal Carcinoma Patients
Authors: Kam Ngar Woon , Lo Anthony Wing Ip , Hung Desmond Tae Yang , Ko Ho , Wu Ka Chun , Kwong Dora Lai Wan , Lam Ka On , Leung To Wai , Che Chi Ming , Lee Victor Ho Fun
Published: January 2024

The use of immune checkpoint inhibitors (ICIs) in cancer treatment has shown promise but can also have unintended consequences, such as reactivating latent tuberculosis (TB). To develop treatments that address ICIs-related adverse events, it is essential to understand cellular heterogeneity across healthy and pathological tissues. We performed cross-tissue multiplexed staining analysis on samples from two patients with TB reactivation during pembrolizumab treatment for metastatic nasopharyngeal carcinoma. CD8+ T cells, rather than CD4+ T cells, accumulated preferentially in the tuberculoma and were associated with increased production of IFNγ and expression of CD137. Additionally, CD137 enrichment played a role in the spatial organization of the tuberculoma, with specific interaction limited to spatial proximal cells between IFNγ+ CD137+ CD8+ T cells and IL12+ CD137+ type-1 macrophages. This unique feature was not observed in non-tumoral or tumoral tissues. Our analysis of public transcriptomic datasets supported the notion that this cellular interaction was more prominent in patients with durable ICI responses compared to those with non-ICI-related TB. We suggest that shifts towards CD137-rich immune niches are correlated with both off-target immune-related adverse events and anti-tumor efficacy. Targeting the tumor microenvironment through conditional activation of anti-CD137 signaling in combination with ICIs can modulate the reactivity of T cells and macrophages for localized tumor killing without the potential off-target immune-related risks associated with ICIs alone.
MR-LINAC, a New Partner in Radiation Oncology: Current Landscape
Authors: Ocanto Abrahams , Torres Lisselott , Montijano Miguel , Rincón Diego , Fernández Castalia , Sevilla Beatriz , Gonsalves Daniela , Teja Macarena , Guijarro Marcos , Glaría Luis , Hernánz Raúl , Zafra-Martin Juan , Sanmamed Noelia , Kishan Amar , Alongi Filippo , Moghanaki Drew , Nagar Himanshu , Couñago Felipe
Published: January 2024

Technological advances in radiation oncology are oriented towards improving treatment precision and tumor control. Among these advances, magnetic-resonance-image-guided radiation therapy (MRgRT) stands out, with technological advances to deliver targeted treatments adapted to a tumor’s anatomy on the day while minimizing incidental exposure to organs at risk, offering an unprecedented therapeutic advantage compared to X-ray-based IGRT delivery systems. This new technology changes the traditional workflow in radiation oncology and requires an evolution in team coordination to administer more precise treatments. Once implemented, it paves the way for newer indication for radiation therapy to safely deliver higher doses than ever before, with better preservation of healthy tissues to optimize patient outcomes. In this narrative review, we assess the technical aspects of the novel linear accelerators that can deliver MRgRT and summarize the available published experience to date, focusing on oncological results and future challenges.
Features of Studies on Transition Interventions for Childhood Cancer Survivors: A Scoping Review
Authors: Ma Jun , Xiao Xueling , Zhou Siqi , Gu Can , Liu Fei , Wang Honghong
Published: January 2024

Purpose: in this scoping review, previously reported data were described and synthesized to document transition interventions in CCSs, and the features of intervention components of the current transition studies for CCSs were summarized. Methods: A literature search was conducted in PubMed, Web of Science, EMBASE, PsycINFO, CINAHL, Ovid, and the Cochrane Library following the PRISMA-ScR statement. All original studies (n = 9) investigating transition interventions in CCSs were included. Results: The current studies identified essential elements for transition programs, such as delivering knowledge, developing skills for coordination of care, and addressing psychosocial needs. However, the current transition interventions were generally in their infancy, and major deficits were found, including poorly reported intervention components and procedures, a limited number of relevant validated outcomes, and a failure to incorporate conceptual frameworks and international consensus statements. Conclusions: This scoping review mapped current evidence of transition interventions for CCSs and highlighted the paucity of data in this area. More high-quality and well-reported randomized controlled trials are needed for the enrichment and standardization of future transition interventions.
Current Treatment Concepts for Extra-Abdominal Desmoid-Type Fibromatosis: A Narrative Review
Authors: Lee Yong-Suk , Joo Min Wook , Shin Seung-Han , Hong Sungan , Chung Yang-Guk
Published: January 2024

Extra-abdominal desmoid-type fibromatosis (EADTF) is a rare neoplastic condition of monoclonal fibroblastic proliferation characterized by local aggressiveness with a distinct tendency to recur. Although EADTF is a benign disease entity, these tumors have a tendency to infiltrate surrounding normal tissues, making it difficult to completely eliminate them without adjacent healthy tissue injury. Surgical excision of these locally aggressive tumors without clear resection margins often leads to local recurrence. The aim of this thorough review was to assess the current treatment concepts for these rare tumors. A comprehensive search of articles published in the Cochrane Library, MEDLINE (PubMed), and EMBASE databases between January 2008 and February 2023 was conducted. Surgical intervention is no longer the first-line approach for most cases; instead, strategies like active surveillance or systemic therapies are used as initial treatment options. With the exception of EADTFs situated near vital structures, a minimum of 6–12 months of active surveillance is currently advocated for, during which some disease progression may be considered acceptable. Non-surgical interventions such as radiation or cryoablation may be employed in certain patients to achieve local control. The currently preferred systemic treatment options include tyrosine kinase inhibitors, low-dose chemotherapy, and gamma-secretase inhibitors, while hormone therapy is not advised. Nonsteroidal anti-inflammatory drugs are utilized primarily for pain management.
Metastatic Lymph Node Detection on Ultrasound Images Using YOLOv7 in Patients with Head and Neck Squamous Cell Carcinoma
Authors: Eida Sato , Fukuda Motoki , Katayama Ikuo , Takagi Yukinori , Sasaki Miho , Mori Hiroki , Kawakami Maki , Nishino Tatsuyoshi , Ariji Yoshiko , Sumi Misa
Published: January 2024

Ultrasonography is the preferred modality for detailed evaluation of enlarged lymph nodes (LNs) identified on computed tomography and/or magnetic resonance imaging, owing to its high spatial resolution. However, the diagnostic performance of ultrasonography depends on the examiner’s expertise. To support the ultrasonographic diagnosis, we developed YOLOv7-based deep learning models for metastatic LN detection on ultrasonography and compared their detection performance with that of highly experienced radiologists and less experienced residents. We enrolled 462 B- and D-mode ultrasound images of 261 metastatic and 279 non-metastatic histopathologically confirmed LNs from 126 patients with head and neck squamous cell carcinoma. The YOLOv7-based B- and D-mode models were optimized using B- and D-mode training and validation images and their detection performance for metastatic LNs was evaluated using B- and D-mode testing images, respectively. The D-mode model’s performance was comparable to that of radiologists and superior to that of residents’ reading of D-mode images, whereas the B-mode model’s performance was higher than that of residents but lower than that of radiologists on B-mode images. Thus, YOLOv7-based B- and D-mode models can assist less experienced residents in ultrasonographic diagnoses. The D-mode model could raise the diagnostic performance of residents to the same level as experienced radiologists.
Photodegradation of Wastewater Containing Organic Dyes Using Modified G-C3N4-Doped ZrO2 Nanostructures: Towards Safe Water for Human Beings
Authors: Mosleh Ahmed T. , Al-Harbi Fatemah F. , Gouadria Soumaya M. , Zyoud Samer H. , Zahran Heba Y. , Hussien Mai S. A. , Yahia Ibrahim S.
Published: January 2024

Historically, the photocatalytic efficacy of graphitic carbon nitride (g-C3N4) has been constrained by a rapid charge recombination rate and restricted sensitivity to visible light. To overcome these limitations and enhance the performance of g-C3N4, the strategic formation of heterojunctions with semiconductor materials is deemed the optimal approach. The present study employed a facile sonication-assisted pyrolysis method to synthesize a g-C3N4@ZrO2 nanocomposite photocatalyst. This hybrid material was characterized extensively using a comprehensive suite of analytical techniques, including XRD, SEM, EDX, FTIR, and UV-Vis DRS. A comparative analysis of photocatalytic applications under identical conditions was conducted for all synthesized materials, wherein they were subjected to UVc light irradiation. The photocatalytic degradation of various dye models, such as MB, EY, and a combination of dyes, was assessed using the prepared nanocomposites. The g-C3N4@ZrO2 photocatalysts showcased superior photocatalytic performance, with a particular variant, g-CNZ6, exhibiting remarkable activity. With a bandgap energy of 2.57 eV, g-CNZ6 achieved impressive degradation efficiencies of 96.5% for MB and 95.6% for EY within 40 min. Following previous studies, the superoxide radical anions (O2−. and h+) were largely accountable for the degradation of MB. Therefore, the observed efficacy of the g-C3N4@ZrO2 nanocomposite photocatalyst can be attributed to the increased generation of these reactive species.
Visible Light-Driven Organic Pollutant Removal Using Fe-Based Photocatalysts Supported by Wheat Straw Biochar
Authors: Subramaniam Mahesan Naidu , Zheng Jiaojiao , Wu Zhentao , Goh Pei Sean , Zhang Guangru
Published: January 2024

Researchers are actively pursuing the development of highly functional photocatalyst materials using environmentally friendly and sustainable resources. In this study, wheat straw biochar (BC), a by-product of biomass pyrolysis, was explored as a green, porous substrate and a carbon-based sensitizer to activate Fe-based photocatalysts under visible light. The research also delved into the impact of doping copper (Cu), chromium (Cr), and zinc (Zn) to enhance the photocatalytic activity of BC-Fe-based catalysts for the removal of methylene orange (MO) from water. Characterization results revealed a more than twofold increase in surface area and greater porosity, contributing to improved radical generation. BC demonstrated its dual functionality as a high surface area substrate and an electron sink, facilitating multistep electron movement and enhancing the photoactivity of the composite catalyst. Photodegradation experiments indicated that the combination of BC with Fe and Zn exhibited the highest performance, removing over 80% of MO within 120 min. Parametric studies highlighted the preference for an alkali pH, and the photocatalyst demonstrated efficient performance up to 30 ppm of dye. Radical scavenging experiments identified •OH and h+ as the most generated radicals. This study establishes that the green and sustainable BC holds promise as a material in the quest for more sustainable photocatalysts.
Tissue-Predisposition to Cancer Driver Mutations
Authors: Peters Luriano , Venkatachalam Avanthika , Ben-Neriah Yinon
Published: January 2024

Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their mutation frequency in premalignant tissue is expected to exceed the basal mutation rate. In old terms, that translates to “the survival of the fittest” and implies that a selective process underlies the frequency of cancer driver mutations. In that sense, each tissue is its own niche that creates a molecular selective pressure that may favor the propagation of a mutation or not. At the heart of this stands one of the biggest riddles in cancer biology: the tissue-predisposition to cancer driver mutations. The frequency of cancer driver mutations among tissues is non-uniform: for instance, mutations in APC are particularly frequent in colorectal cancer, and 99% of chronic myeloid leukemia patients harbor the driver BCR-ABL1 fusion mutation, which is rarely found in solid tumors. Here, we provide a mechanistic framework that aims to explain how tissue-specific features, ranging from epigenetic underpinnings to the expression of viral transposable elements, establish a molecular basis for selecting cancer driver mutations in a tissue-specific manner.
Site-Specific O-glycosylation of SARS-CoV-2 Spike Protein and Its Impact on Immune and Autoimmune Responses
Authors: Hanisch Franz-Georg
Published: January 2024

The world-wide COVID-19 pandemic has promoted a series of alternative vaccination strategies aiming to elicit neutralizing adaptive immunity in the human host. However, restricted efficacies of these vaccines targeting epitopes on the spike (S) protein that is involved in primary viral entry were observed and putatively assigned to viral glycosylation as an effective escape mechanism. Besides the well-recognized N-glycan shield covering SARS-CoV-2 spike (S) proteins, immunization strategies may be hampered by heavy O-glycosylation and variable O-glycosites fluctuating depending on the organ sites of primary infection and those involved in immunization. A further complication associated with viral glycosylation arises from the development of autoimmune antibodies to self-carbohydrates, including O-linked blood group antigens, as structural parts of viral proteins. This outline already emphasizes the importance of viral glycosylation in general and, in particular, highlights the impact of the site-specific O-glycosylation of virions, since this modification is independent of sequons and varies strongly in dependence on cell-specific repertoires of peptidyl-N-acetylgalactosaminyltransferases with their varying site preferences and of glycan core-specific glycosyltransferases. This review summarizes the current knowledge on the viral O-glycosylation of the SARS-CoV-2 spike protein and its impact on virulence and immune modulation in the host.
CAH3 from Chlamydomonas reinhardtii: Unique Carbonic Anhydrase of the Thylakoid Lumen
Authors: Terentyev Vasily V. , Shukshina Anna K.
Published: January 2024

CAH3 is the only carbonic anhydrase (CA) present in the thylakoid lumen of the green algae Chlamydomonas reinhardtii. The monomer of the enzyme has a molecular weight of ~29.5 kDa with high CA activity. Through its dehydration activity, CAH3 can be involved either in the carbon-concentrating mechanism supplying CO2 for RuBisCO in the pyrenoid or in supporting the maximal photosynthetic activity of photosystem II (PSII) by accelerating the removal of protons from the active center of the water-oxidizing complex. Both proposed roles are considered in this review, together with a description of the enzymatic parameters of native and recombinant CAH3, the crystal structure of the protein, and the possible use of lumenal CA as a tool for increasing biomass production in higher plants. The identified involvement of lumenal CAH3 in the function of PSII is still unique among green algae and higher plants and can be used to understand the mechanism(s) of the functional interconnection between PSII and the proposed CA(s) of the thylakoid lumen in other organisms.
Spectroscopy and Chemometrics for Conformity Analysis of e-Liquids: Illegal Additive Detection and Nicotine Characterization
Authors: Akhtar Zeb , Barhdadi Sophia , De Braekeleer Kris , Delporte Cedric , Adams Erwin , Deconinck Eric
Published: January 2024

Vaping electronic cigarettes (e-cigarettes) has become a popular alternative to smoking tobacco. When an e-cigarette is activated, a liquid is vaporized by heating, producing an aerosol that users inhale. While e-cigarettes are marketed as less harmful than traditional cigarettes, there are ongoing concerns about their long-term health effects, including potential lung damage. Therefore, it is essential to closely monitor and study the composition of e-liquids. E-liquids typically consist of propylene glycol, glycerin, flavorings and nicotine, though there have been reports of non-compliant nicotine concentrations and the presence of illegal additives. This study explored spectroscopic techniques to examine the conformity of nicotine labeling and detect the presence of the not-allowed additives: the caffeine, taurine, vitamin E and cannabidiol (CBD) in e-liquids. A total of 236 e-liquid samples were carefully selected for analysis. Chemometric analysis was applied to the collected data, which included mid-infrared (MIR) and near-infrared (NIR) spectra. Supervised modeling approaches such as partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) were employed to classify the samples, based on the presence of nicotine and the targeted additives. This study demonstrates the efficacy of MIR and NIR spectroscopic techniques in conjunction with chemometric methods (SIMCA and PLS-DA) for detecting specific molecules in e-liquids. MIR with autoscaling data preprocessing and PLS-DA achieved 100% classification rates for CBD and vitamin E, while NIR with the same approach achieved 100% for CBD and taurine. Overall, MIR combined with PLS-DA yielded the best classification across all targeted molecules, suggesting its preference as a singular technique.
Origami Paper-Based Electrochemical Immunosensor with Carbon Nanohorns-Decorated Nanoporous Gold for Zearalenone Detection
Authors: Laza Anabel , Pereira Sirley V. , Messina Germán A. , Fernández-Baldo Martín A. , Raba Julio , Regiart Matías D. , Bertolino Franco A.
Published: January 2024

Nowadays, mycotoxin contamination in cereals and wastewater exposes a safety hazard to consumer health. This work describes the design of a simple, low-cost, and sensitive origami microfluidic paper-based device using electrochemical detection for zearalenone determination. The microfluidic immunosensor was designed on a paper platform by a wax printing process. The graphitized carbon working electrode modified with carbon nanohorns-decorated nanoporous gold showed a higher surface area, sensitivity, and adequate analytical performance. Electrodes were characterized by scanning electron microscopy, energy-dispersive spectroscopy, and cyclic voltammetry. The determination of zearalenone was carried out through a competitive immunoassay using specific antibodies immobilized by a covalent bond on the electrode surface. In the presence of HRP-labeled enzyme conjugate, substrate, and catechol, zearalenone was detected employing the developed immunosensor by applying −0.1 V to the working electrode vs silver as a pseudo-reference electrode. A calibration curve with a linear range between 10 and 1000 µg Kg−1 (R2 = 0.998) was obtained, and the limit of detection and quantification for the electrochemical immunosensor were 4.40 and 14.90 µg Kg−1, respectively. The coefficient of variation for intra- and inter-day assays was less than 5%. The selectivity and specificity of the sensor were evaluated, comparing the response against zearalenone metabolites and other mycotoxins that could affect the corn samples. Therefore, origami is a promising approach for paper-based electrochemical microfluidic sensors coupled to smartphones as a rapid and portable tool for in situ mycotoxins detection in real samples.
Harnessing Natural Polymers for Nano-Scaffolds in Bone Tissue Engineering: A Comprehensive Overview of Bone Disease Treatment
Authors: Saurav Sushmita , Sharma Prashish , Kumar Anil , Tabassum Zeba , Girdhar Madhuri , Mamidi Narsimha , Mohan Anand
Published: January 2024

Numerous surgeries are carried out to replace tissues that have been harmed by an illness or an accident. Due to various surgical interventions and the requirement of bone substitutes, the emerging field of bone tissue engineering attempts to repair damaged tissues with the help of scaffolds. These scaffolds act as template for bone regeneration by controlling the development of new cells. For the creation of functional tissues and organs, there are three elements of bone tissue engineering that play very crucial role: cells, signals and scaffolds. For the achievement of these aims, various types of natural polymers, like chitosan, chitin, cellulose, albumin and silk fibroin, have been used for the preparation of scaffolds. Scaffolds produced from natural polymers have many advantages: they are less immunogenic as well as being biodegradable, biocompatible, non-toxic and cost effective. The hierarchal structure of bone, from microscale to nanoscale, is mostly made up of organic and inorganic components like nanohydroxyapatite and collagen components. This review paper summarizes the knowledge and updates the information about the use of natural polymers for the preparation of scaffolds, with their application in recent research trends and development in the area of bone tissue engineering (BTE). The article extensively explores the related research to analyze the advancement of nanotechnology for the treatment of bone-related diseases and bone repair.
Study on the Corrosion Resistance of Supersonic Plasma Spraying Al2O3 Thin Layer and SiO2 Sealer Alternately Deposited Coating
Authors: Feng Yuxi , Liu Ming , Jia Lei , Bai Yu , Ma Guozheng , Zhou Xinyuan , Wang Haidou , Wang Haozhen
Published: January 2024

The longevity of thermally sprayed ceramic coatings is often difficult to achieve in corrosive environments. In this paper, an alternating sealing coating technology was used to seal supersonic plasma sprayed Al2O3 coatings. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) were used to characterize the coating microstructure of Al2O3 coatings and seal coats. The corrosion behavior of alternating sealing coating, traditional sealed coating, and spray coating at 5 wt.% NaCl was studied by the electrochemical test method (dynamic polarization) and immersion corrosion experiments. The results show that the alternating sealing coating is better in preventing the production of through holes and hindering the inward diffusion of corrosive media than traditional sealed coatings, and further increases the thickness of the sealing layer. Compared with the traditional sealing coating, the porosity of alternating sealing coating is decreased by 70.5%, the corrosion potential is increased by 74 mV, and the corrosion current density is decreased by about 78%, which confers better long-term corrosion resistance.
Aging Effect of Plasma-Treated Carbon Fiber Surface: From an Engineering Point
Authors: Wang Shiwen , Wang Yu , Gao Ming , Huang Yifan
Published: January 2024

Dielectric barrier discharge (DBD) plasma surface modification has certain aging effect. This article studies the aging effect of plasma (DBD) on the surface modification of carbon fibers. The test results show that plasma (DBD) treatment reduces the impurity particles on the surface of carbon fibers and makes the surface texture coarser. In addition, there is no significant change. After plasma (DBD) treatment, the content of C–O–C, C–O and C=O on the surface of carbon fibers increased from 3.20%, 7.76% and 1.64% to 7.06%, 21.50 and 6.08%, respectively. This is due to the high-energy particle bombardment of the fiber surface, which forms activated carbon atoms on the surface. The free electrons of these activated carbon atoms combine with ionized oxygen in the air. However, with the passage of time, the content of C–O–C, C–O and C=O gradually decreases to 3.31%, 8.57% and 1.77%, respectively. This is because some functional groups formed on the treated carbon fiber surface are not firmly bound, and some of these functional groups containing O2 groups will combine with surrounding substances through irreversible chemical oxidation reactions to produce CO2, which leaves the carbon fiber surface as a gas. The treated carbon fibers will immediately become hydrophilic, and the water contact angle decreases from 148.71° to 0°. With the passage of time, the water contact angle gradually increases to 118.16°, and the hydrophobicity recovers.
An Overview of the Copper Oxide Nanofillers Integrated in Food Packaging Systems
Authors: Gopinath Kasi , Sathishkumar Gnanasekar , Xu Liqun
Published: January 2024

Recently, functional nanomaterials with unique sizes, shapes, and surface chemistry have been fabricated for various applications in all facets of science and technology. Among these diverse nanomaterials, copper oxide nanoparticles (CuO NPs) have garnered considerable attention due to their unique physicochemical parameters and semiconductor properties. Doping various functional materials in CuO NPs and the fabrication of CuO nanofillers functionalized with natural or synthetic moieties delivers improved antibacterial efficacy in food packaging applications. Moreover, the bactericidal effect of modified CuO NPs against foodborne pathogens largely contributes to their usage in food packaging technology. Therefore, it is essential to fabricate effective antimicrobial CuO nanofillers with minimal or no adverse side effects. This review discusses the synthesis, characterization, surface modification, antibacterial properties, food packaging applications, and toxicological implications of the diverse CuO nanofillers integrated in films and composites. In addition, it highlights their adverse side effects and ways to combat adverse situations. The forthcoming generation is expected to lead a groundbreaking surge of inventive food packaging systems (FPS) based on CuO hybrid nanofillers in food packaging industries.
Preparation of Alumina Thin Films by Reactive Modulated Pulsed Power Magnetron Sputtering with Millisecond Pulses
Authors: Tumarkin Alexander V. , Kolodko Dobrynya V. , Kharkov Maksim M. , Stepanova Tatiana V. , Kaziev Andrey V. , Samotaev Nikolay N. , Oblov Konstantin Yu.
Published: January 2024

This paper aims to investigate the quality of thin alumina films deposited on glass samples using magnetron sputtering in the reactive modulated pulsed power mode (MPPMS) and evaluate the process productivity. The aluminum target was sputtered in Ar/O2 gas mixtures with different fractions of oxygen in the total gas flow, in the fixed pulsed voltage mode. The pulse-on duration was varied between 5 and 10 ms, while the pulse-off time was 100 or 200 ms. The dependences of mass deposition rate and discharge current on the oxygen flow were measured, and the specific deposition rate values were calculated. Prepared coatings had a thicknesses of 100–400 nm. Their quality was assessed by scratch testing and by measuring density, refractory index, and extinction coefficient for different power management strategies. The strong influence of pulse parameters on the coating properties was observed, resulting in a maximum density of 3.6 g/cm3 and a refractive index of 1.68 for deposition modes with higher duty cycle values. Therefore, adjusting the pulse-on and pulse-off periods in MPPMS can be used not only to optimize the deposition rate but also as a tool to tune the optical characteristics of the films. The performance of the studied deposition method was evaluated by comparing the specific growth rates of alumina coatings with the relevant data for other magnetron discharge modes. In MPPMS, a specific deposition rate of 200 nm/min/kW was obtained for highly transparent Al2O3, without using any dedicated feedback loop system for oxygen pressure stabilization, which makes MPPMS superior to short-pulse high-power impulse magnetron sputtering (HiPIMS) modes.
Metal Halide Perovskites: Promising Materials for Light-Emitting Diodes
Authors: Li Xuyang , Shen Xia , Lv Qihang , Guo Pengfei , Xiao Liantuan
Published: January 2024

Metal halide perovskites have shown excellent optoelectronic properties, including high photoluminescence quantum yield, tunable emission wavelengths, narrow full-width at half-maximums and a low-cost, solution-processed fabrication, which make it exhibit great potential as emission-layer materials of light-emitting diodes. With the joint efforts of researchers from different disciplines, there has been a significant progress in the improvement in the external quantum efficiency (EQE) and stability of perovskite light-emitting diodes (PeLEDs) in recent years, especially in green PeLEDs with EQEs over 30%. However, their operational stability lags behind other commercial organic and chalcogenide quantum dot emitters, limiting their practical application. In this review, we first introduce the basic device structure of PeLEDs, as well as the factors influencing the EQE and stability of PeLEDs. Secondly, the development of lead-based and lead-free PeLEDs are summarized systematically. Thirdly, challenges of PeLEDs are discussed in detail, including low the EQE of blue PeLEDs, poor device stability and EQE roll-off. Finally, some suggestions and perspectives for future research directions for PeLEDs are proposed.
Functionalization of Plasma Electrolytic Oxidation/Sol–Gel Coatings on AZ31 with Organic Corrosion Inhibitors
Authors: Pillado Borja , Matykina Endzhe , Olivier Marie-Georges , Mohedano Marta , Arrabal Raúl
Published: January 2024

In this investigation, the sol–gel method is employed along with a corrosion inhibitor to seal a plasma electrolytic oxidation (PEO) coating, aiming to improve the long-term corrosion resistance of the AZ31 Mg alloy. Following an initial screening of corrosion inhibitors, 8-hydroxyquinoline (8HQ) is incorporated into the hybrid PEO/sol–gel system using two methods: (i) post-treatment of the PEO layer through immersion in an inhibitor-containing solution; (ii) loading the inhibitor into the sol–gel precursor. The characterization includes scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-vis), and water drop contact angle measurements. The rheological properties of the inhibitor-loaded sol–gel precursors are assessed by measuring flow curves. The corrosion processes are evaluated in a saline solution through electrochemical impedance spectroscopy (EIS) and immersion tests with unscratched and scratched specimens, respectively. The results demonstrate the successful incorporation of the inhibitor for both loading strategies. Regardless of the loading approach, systems containing 8HQ exhibit the most favourable long-term corrosion resistance.
Investigation of Polyelectrolyte Multilayers Deposited on Biodegradable Corona-Charged Substrates Used as Drug Delivery Systems
Authors: Viraneva Asya , Marudova Maria , Milenkova Sofia , Grigorov Aleksandar , Yovcheva Temenuzhka
Published: January 2024

Polyelectrolyte multilayers (PEMs) deposited on porous composite polylactic acid/poly(ε-caprolactone) (PDLA/PEC) substrates were studied. The substrates were previously charged in a corona discharge. Time dependences of the normalized surface potential for positively and negatively charged electrets were investigated. The morphology of the obtained porous substrates was examined by means of scanning electron microscopy (SEM). The chitosan and the casein polyelectrolytes were deposited on the substrates using the layer-by-layer (LbL) technique. The drug loading efficiency and the release kinetics were determined spectrophotometrically.
Novel Effect of Post-Oxidation on the Comprehensive Performance of Plasma Nitriding Layer
Authors: Ni Jia , Ma Heng , Wei Wei , An Xulong , Yu Minhua , Hu Jing
Published: January 2024

In order to enhance the comprehensive performance of plasma nitrided heavy load components used in corrosive environments, post-oxidation was conducted under different conditions after plasma nitriding 42CrMo4 steel at 500 °C for 5 h. The results show that an oxide film composed of Fe3O4 and Fe2O3 was formed above the compound layer, resulting in a significant increase in corrosion resistance; the self-corrosion potential was greatly increased from −658.72 mV to −429.23 mV. Meanwhile, it needs to be emphasized that the characteristics of the plasma nitriding layer could be effectively adjusted as expected by post-oxidation. The compound layer thickness decreased from 9.41 μm to 3.62 μm by post-oxidation at 400 °C for 2 h, while the thickness of the effective hardening layer increased from 300 μm to 378 μm. Due to the expected change in the characteristics of the plasma nitriding layer, post-oxidation could simultaneously improve the toughness, hardness, and wear resistance of the samples; the brittleness level decreased from Grade 4 to Grade 1; the surface hardness increased from 765 HV0.05 to 825 HV0.05; and the wear rate decreased from 3 × 10−5 g·m−1·N−1 to 1.19 × 10−5 g·m−1·N−1, illustrating that the wear resistance was greatly improved.
A New Mixed Fractional Derivative with Applications in Computational Biology
Authors: Hattaf Khalid
Published: January 2024

This study develops a new definition of a fractional derivative that mixes the definitions of fractional derivatives with singular and non-singular kernels. This developed definition encompasses many types of fractional derivatives, such as the Riemann–Liouville and Caputo fractional derivatives for singular kernel types, as well as the Caputo–Fabrizio, the Atangana–Baleanu, and the generalized Hattaf fractional derivatives for non-singular kernel types. The associate fractional integral of the new mixed fractional derivative is rigorously introduced. Furthermore, a novel numerical scheme is developed to approximate the solutions of a class of fractional differential equations (FDEs) involving the mixed fractional derivative. Finally, an application in computational biology is presented.
An Event-Centric Knowledge Graph Approach for Public Administration as an Enabler for Data Analytics
Authors: Zeginis Dimitris , Tarabanis Konstantinos
Published: January 2024

In a continuously evolving environment, organizations, including public administrations, need to quickly adapt to change and make decisions in real-time. This requires having a real-time understanding of their context that can be achieved by adopting an event-native mindset in data management which focuses on the dynamics of change compared to the state-based traditional approaches. In this context, this paper proposes the adoption of an event-centric knowledge graph approach for the holistic data management of all data repositories in public administration. Towards this direction, the paper proposes an event-centric knowledge graph model for the domain of public administration that captures these dynamics considering events as first-class entities for knowledge representation. The development of the model is based on a state-of-the-art analysis of existing event-centric knowledge graph models that led to the identification of core concepts related to event representation, on a state-of-the-art analysis of existing public administration models that identified the core entities of the domain, and on a theoretical analysis of concepts related to events, public services, and effective public administration in order to outline the context and identify the domain-specific needs for event modeling. Further, the paper applies the model in the context of Greek public administration in order to validate it and showcase the possibilities that arise. The results show that the adoption of event-centric knowledge graph approaches for data management in public administration can facilitate data analytics, continuous integration, and the provision of a 360-degree-view of end-users. We anticipate that the proposed approach will also facilitate real-time decision-making, continuous intelligence, and ubiquitous AI.
Mining Negative Associations from Medical Databases Considering Frequent, Regular, Closed and Maximal Patterns
Authors: Budaraju Raja Rao , Jammalamadaka Sastry Kodanda Rama
Published: January 2024

Many data mining studies have focused on mining positive associations among frequent and regular item sets. However, none have considered time and regularity bearing in mind such associations. The frequent and regular item sets will be huge, even when regularity and frequency are considered without any time consideration. Negative associations are equally important in medical databases, reflecting considerable discrepancies in medications used to treat various disorders. It is important to find the most effective negative associations. The mined associations should be as small as possible so that the most important disconnections can be found. This paper proposes a mining method that mines medical databases to find regular, frequent, closed, and maximal item sets that reflect minimal negative associations. The proposed algorithm reduces the negative associations by 70% when the maximal and closed properties have been used, considering any sample size, regularity, or frequency threshold.
Synthesis, Crystal Structure and Photoluminescent Properties of Novel 9-Cyano-Pyrrolo[1,2-a][1,10]Phenanthrolines
Authors: Cristea Mihaela , Răducă Mihai , Shova Sergiu , Drăghici Constantin , Neacșu Vlad A. , Maganu Maria , Albotă (Barbu) Loredana , Dumitrescu Denisa , Dumitrascu Florea
Published: January 2024

Novel 9-cyano-pyrrolo[1,2-a][1,10]phenanthrolines 6a–d were obtained by an efficient one-pot regioselective reaction between 1,10-phenanthrolinium bromides 2a–d and acrylonitrile as a dipolarophile, in the presence of triethylamine and tetrakis-pyridino-cobalt(II) dichromate (TPCD) as oxidizing agents. The optical properties of the compounds were investigated through UV–Vis spectrophotometry and steady-state photoluminescence measurements, while their structures were elucidated by single-crystal X-ray diffraction. The structural characterization revealed that the molecular structures of the four compounds were stabilized by hydrogen bonds and π–π interactions.
ADAS Simulation Result Dataset Processing Based on Improved BP Neural Network
Authors: Zhao Songyan , Chen Lingshan , Huang Yongchao
Published: January 2024

The autonomous driving simulation field lacks evaluation and forecasting systems for simulation results. The data obtained from the simulation of target algorithms and vehicle models cannot be reasonably estimated. This problem affects subsequent vehicle improvement and parameter calibration. The authors relied on the simulation results of the AEB algorithm. We selected the BP Neural Network as the basis and improved it with a genetic algorithm optimized via a roulette algorithm. The regression evaluation indicators of the prediction results show that the GA-BP neural network has better prediction accuracy and generalization ability than the original BP neural network and other optimized BP neural networks. This GA-BP neural network also fills the Gap in Evaluation and Prediction Systems.
Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification
Authors: Abdelrahman Khaled , Shiyovich Arthur , Huck Daniel , Berman Adam , Weber Brittany , Gupta Sumit , Cardoso Rhanderson , Blankstein Ron
Published: January 2024

Coronary artery calcium (CAC) is a marker of coronary atherosclerosis, and the presence and severity of CAC have been shown to be powerful predictors of future cardiovascular events. Due to its value in risk discrimination and reclassification beyond traditional risk factors, CAC has been supported by recent guidelines, particularly for the purposes of informing shared decision-making regarding the use of preventive therapies. In addition to dedicated ECG-gated CAC scans, the presence and severity of CAC can also be accurately estimated on non-contrast chest computed tomography scans performed for other clinical indications. However, the presence of such “incidental” CAC is rarely reported. Advances in artificial intelligence have now enabled automatic CAC scoring for both cardiac and non-cardiac CT scans. Various AI approaches, from rule-based models to machine learning algorithms and deep learning, have been applied to automate CAC scoring. Convolutional neural networks, a deep learning technique, have had the most successful approach, with high agreement with manual scoring demonstrated in multiple studies. Such automated CAC measurements may enable wider and more accurate detection of CAC from non-gated CT studies, thus improving the efficiency of healthcare systems to identify and treat previously undiagnosed coronary artery disease.
Analysis of Predictors and Risk Factors of Postpolypectomy Syndrome
Authors: Fusco Stefano , Bauer Michelle E. , Schempf Ulrike , Stüker Dietmar , Blumenstock Gunnar , Malek Nisar P. , Werner Christoph R. , Wichmann Dörte
Published: January 2024

Background and aims: Postpolypectomy syndrome (PPS) is a relevant adverse event that can appear after polypectomy. Several publications mention postpolypectomy syndrome using different criteria to define it. The aim of this study is to detect potential risk factors and predictors for developing PPS and to define the main criteria of PPS. Methods: In this retrospective monocentric study, 475 out of 966 patients who underwent colonoscopy with polypectomy from October 2015 to June 2020 were included. The main criterion of PPS is defined as the development of postinterventional abdominal pain lasting more than six hours. Results: A total of 9.7% of the patients developed PPS, which was defined as local abdominal pain around the polypectomy area after six hours. A total of 8.6% of the study population had abdominal pain within six hours postintervention. A total of 3.7% had an isolated triad of fever, leukocytosis, and increased CRP in the absence of abdominal pain. Increased CRP combined with an elevated temperature over 37.5 °C seems to be a positive predictor for developing PPS. Four independent risk factors could be detected: serrated polyp morphology, polypoid configurated adenomas, polyp localization in the cecum, and the absence of intraepithelial neoplasia. Conclusions: Four independent risk factors for developing PPS were detected. The combination of increased CRP levels with elevated temperature seems to be a predictor for this pathology. As expected, the increasing use of cold snare polypectomies will reduce the incidence of this syndrome. Key summary: Our monocentric study on 966 patients detected four independent risk factors for developing PPS: pedunculated polyp, resected polyps in the cecum, absence of IEN, and serrated polyp morphology. The combination of increased CRP levels with elevated temperature seems to be a predictor for this pathology.
An Interpretable Approach with Explainable AI for Heart Stroke Prediction
Authors: Srinivasu Parvathaneni Naga , Sirisha Uddagiri , Sandeep Kotte , Praveen S. Phani , Maguluri Lakshmana Phaneendra , Bikku Thulasi
Published: January 2024

Heart strokes are a significant global health concern, profoundly affecting the wellbeing of the population. Many research endeavors have focused on developing predictive models for heart strokes using ML and DL techniques. Nevertheless, prior studies have often failed to bridge the gap between complex ML models and their interpretability in clinical contexts, leaving healthcare professionals hesitant to embrace them for critical decision-making. This research introduces a meticulously designed, effective, and easily interpretable approach for heart stroke prediction, empowered by explainable AI techniques. Our contributions include a meticulously designed model, incorporating pivotal techniques such as resampling, data leakage prevention, feature selection, and emphasizing the model’s comprehensibility for healthcare practitioners. This multifaceted approach holds the potential to significantly impact the field of healthcare by offering a reliable and understandable tool for heart stroke prediction. In our research, we harnessed the potential of the Stroke Prediction Dataset, a valuable resource containing 11 distinct attributes. Applying these techniques, including model interpretability measures such as permutation importance and explainability methods like LIME, has achieved impressive results. While permutation importance provides insights into feature importance globally, LIME complements this by offering local and instance-specific explanations. Together, they contribute to a comprehensive understanding of the Artificial Neural Network (ANN) model. The combination of these techniques not only aids in understanding the features that drive overall model performance but also helps in interpreting and validating individual predictions. The ANN model has achieved an outstanding accuracy rate of 95%.
Can the Initial Parameters of Functional Scales Predict Recovery in Patients with Complete Spinal Cord Injury? A Retrospective Cohort Study
Authors: Wasiak Krzysztof , Frasuńska Justyna , Tarnacka Beata
Published: January 2024

Regaining greater independence in performing daily activities constitutes a priority for people with tetraplegia following spinal cord injury (SCI). The highest expectations are connected with the improvement of hand function. Therefore, it is so important for the clinician to identify reliable and commonly applicable prognostic factors for functional improvement. The aim of this study was to conduct an analysis to assess the impact of initial functional factors on the clinical improvement in patients during early neurological rehabilitation (ENR). This study assessed 38 patients with complete SCI aged 17–78 who underwent ENR in 2012–2022. The analysis included the motor score from the AIS (MS), the Barthel Index (BI) and the SCIM scale values at the beginning of the ENR program and after its completion. During ENR, patients achieved a statistically significant improvement in MS, BI and SCIM. The initial MS and the level of neurological injury constituted the predictors of functional improvement during ENR. Significant statistical relationships were observed primarily in the correlations between the initial MS and BI, and the increase in the analyzed functional scales of SCI patients. Higher initial MS may increase the chances of a greater and faster functional improvement during ENR.
The Impact of Specialised Heart Failure Outpatient Care on the Long-Term Application of Guideline-Directed Medical Therapy and on Prognosis in Heart Failure with Reduced Ejection Fraction
Authors: Muk Balázs , Bánfi-Bacsárdi Fanni , Vámos Máté , Pilecky Dávid , Majoros Zsuzsanna , Török Gábor , Vágány Dénes , Polgár Balázs , Solymossi Balázs , Borsányi Tünde , Andréka Péter , Duray Gábor , Kiss Róbert , Dékány Miklós , Nyolczas Noémi
Published: January 2024

(1) Background: Besides the use of guideline-directed medical therapy (GDMT), multidisciplinary heart failure (HF) outpatient care (HFOC) is of strategic importance in HFrEF. (2) Methods: Data from 257 hospitalised HFrEF patients between 2019 and 2021 were retrospectively analysed. Application and target doses of GDMT were compared between HFOC and non-HFOC patients at discharge and at 1 year. 1-year all-cause mortality (ACM) and rehospitalisation (ACH) rates were compared using the Cox proportional hazard model. The effect of HFOC on GDMT and on prognosis after propensity score matching (PSM) of 168 patients and the independent predictors of 1-year ACM and ACH were also evaluated. (3) Results: At 1 year, the application of RASi, MRA and triple therapy (TT: RASi + βB + MRA) was higher (p < 0.05) in the HFOC group, as was the proportion of target doses of ARNI, βB, MRA and TT. After PSM, the composite of 1-year ACM or ACH was more favourable with HFOC (propensity-adjusted HR = 0.625, 95% CI = 0.401–0.974, p = 0.038). Independent predictors of 1-year ACM were age, systolic blood pressure, application of TT and HFOC, while 1-year ACH was influenced by the application of TT. (4) Conclusions: HFOC may positively impact GDMT use and prognosis in HFrEF even within the first year of its initiation.