bluuebunny/crossref_metadata_2025 huggingface dataset:
Depression, Inflammation, and Intestinal Permeability: Associations with Subjective and Objective Cognitive Functioning throughout Breast Cancer Survivorship
Authors: Madison Annelise A. , Andridge Rebecca , Kantaras Anthony H. , Renna Megan E. , Bennett Jeanette M. , Alfano Catherine M. , Povoski Stephen P. , Agnese Doreen M. , Lustberg Maryam , Wesolowski Robert , Carson William E. , Williams Nicole O. , Reinbolt Raquel E. , Sardesai Sagar D. , Noonan Anne M. , Stover Daniel G. , Cherian Mathew A. , Malarkey William B. , Kiecolt-Glaser Janice K.
Published: September 2023

About one-in-three breast cancer survivors have lingering cognitive complaints and objective cognitive impairment. Chronic inflammation and intestinal permeability (i.e., leaky gut), two risk factors for cognitive decline, can also fuel depression—another vulnerability for cognitive decline. The current study tested whether depression accompanied by high levels of inflammation or intestinal permeability predicted lower subjective and objective cognitive function in breast cancer survivors. We combined data from four breast cancer survivor studies (n = 613); some had repeated measurements for a total of 1015 study visits. All participants had a blood draw to obtain baseline measures of lipopolysaccharide binding protein—a measure of intestinal permeability, as well as three inflammatory markers that were incorporated into an inflammatory index: C-reactive protein, interleukin-6, and tumor necrosis factor-α. They reported depressive symptoms on the Center for Epidemiological Studies depression scale (CES-D), and a binary variable indicated clinically significant depressive symptoms (CES-D ≥ 16). The Kohli (749 observations) and the Breast Cancer Prevention Trial (591 observations) scales assessed subjective cognitive function. Objective cognitive function tests included the trail-making test, Hopkins verbal learning test, Conners continuous performance test, n-back test, FAS test, and animal-naming test (239–246 observations). Adjusting for education, age, BMI, cancer treatment type, time since treatment, study visit, and fatigue, women who had clinically elevated depressive symptoms accompanied by heightened inflammation or intestinal permeability reported poorer focus and marginally poorer memory. However, poorer performance across objective cognitive measures was not specific to inflammation-associated depression. Rather, there was some evidence of lower verbal fluency; poorer attention, verbal learning and memory, and working memory; and difficulties with visuospatial search among depressed survivors, regardless of inflammation. By themselves, inflammation and intestinal permeability less consistently predicted subjective or objective cognitive function. Breast cancer survivors with clinically significant depressive symptoms accompanied by either elevated inflammation or intestinal permeability may perceive greater cognitive difficulty, even though depression-related objective cognitive deficits may not be specific to inflammation- or leaky-gut-associated depression.
Radiomics-Based Prediction of TERT Promotor Mutations in Intracranial High-Grade Meningiomas
Authors: Akkurt Burak Han , Spille Dorothee Cäcilia , Peetz-Dienhart Susanne , Kiolbassa Nora Maren , Mawrin Christian , Musigmann Manfred , Heindel Walter Leonhard , Paulus Werner , Stummer Walter , Mannil Manoj , Brokinkel Benjamin
Published: September 2023

Purpose: In meningiomas, TERT promotor mutations are rare but qualify the diagnosis of anaplasia, directly impacting adjuvant therapy. Effective screening for patients at risk for promotor mutations could enable more targeted molecular analyses and improve diagnosis and treatment. Methods: Semiautomatic segmentation of intracranial grade 2/3 meningiomas was performed on preoperative magnetic resonance imaging. Discriminatory power to predict TERT promoter mutations was analyzed using a random forest algorithm with an increasing number of radiomic features. Two final models with five and eight features with both fixed and differing radiomics features were developed and adjusted to eliminate random effects and to avoid overfitting. Results: A total of 117 image sets including training (N = 94) and test data (N = 23) were analyzed. To eliminate random effects and demonstrate the robustness of our approach, data partitioning and subsequent model development and testing were repeated a total of 100 times (each time with repartitioned training and independent test data). The established five- and eight-feature models with both fixed and different radiomics features enabled the prediction of TERT with similar but excellent performance. The five-feature (different/fixed) model predicted TERT promotor mutation status with a mean AUC of 91.8%/94.3%, mean accuracy of 85.5%/88.9%, mean sensitivity of 88.6%/91.4%, mean specificity of 83.2%/87.0%, and a mean Cohen’s Kappa of 71.0%/77.7%. The eight-feature (different/fixed) model predicted TERT promotor mutation status with a mean AUC of 92.7%/94.6%, mean accuracy of 87.3%/88.9%, mean sensitivity of 89.6%/90.6%, mean specificity of 85.5%/87.5%, and a mean Cohen’s Kappa of 74.4%/77.6%. Of note, the addition of further features of up to N = 8 only slightly increased the performance. Conclusions: Radiomics-based machine learning enables prediction of TERT promotor mutation status in meningiomas with excellent discriminatory performance. Future analyses in larger cohorts should include grade 1 lesions as well as additional molecular alterations.
Primary Colorectal Tumor Displays Differential Genomic Expression Profiles Associated with Hepatic and Peritoneal Metastases
Authors: Gelli Maximiliano , Desterke Christophe , Bani Mohamed Amine , Boige Valérie , Ferté Charles , Dartigues Peggy , Job Bastien , Perkins Geraldine , Laurent-Puig Pierre , Goéré Diane , Mathieu Jacques R. R. , Cartry Jerome , Ducreux Michel , Jaulin Fanny
Published: September 2023

Background: Despite improvements in characterization of CRC heterogeneity, appropriate risk stratification tools are still lacking in clinical practice. This study aimed to elucidate the primary tumor transcriptomic signatures associated with distinct metastatic routes. Methods: Primary tumor specimens obtained from CRC patients with either isolated LM (CRC-Liver) or PM (CRC-Peritoneum) were analyzed by transcriptomic mRNA sequencing, gene set enrichment analyses (GSEA) and immunohistochemistry. We further assessed the clinico-pathological associations and prognostic value of our signature in the COAD-TCGA independent cohort. Results: We identified a significantly different distribution of Consensus Molecular Subtypes between CRC-Liver and CRC-peritoneum groups. A transcriptomic signature based on 61 genes discriminated between liver and peritoneal metastatic routes. GSEA showed a higher expression of immune response and epithelial invasion pathways in CRC-Peritoneum samples and activation of proliferation and metabolic pathways in CRC-Liver samples. The biological relevance of RNA-Seq results was validated by the immunohistochemical expression of three significantly differentially expressed genes (ACE2, CLDN18 and DUSP4) in our signature. In silico analysis of the COAD-TCGA showed that the CRC-Peritoneum signature was associated with negative prognostic factors and poor overall and disease-free survivals. Conclusions: CRC primary tumors spreading to the liver and peritoneum display significantly different transcriptomic profiles. The implementation of this signature in clinical practice could contribute to identify new therapeutic targets for stage IV CRC and to define individualized follow-up programs in stage II-III CRC.
Enhancing Nickel-Iron Gas Diffusion Electrodes for Oxygen Evolution in Alkaline Water Electrolysis
Authors: Kaiser Marcel , Gäde Felix , Brauns Jörn , Turek Thomas
Published: September 2023

Alkaline water electrolysis is a well-known technology for sustainable hydrogen production powered by renewable energy. The use of gas diffusion electrodes (GDEs) based on nonprecious materials eliminates the need for an anolyte cycle, leading to a cost reduction of the electrolysis process. In this work, the production of GDEs made of nickel particles and different iron precursors is investigated for the improvement of the oxygen evolution reaction. The GDE production followed an established four-step process: dispersing, spraying, hot pressing, and sintering. Physical characterization comprised the determination of the pore size distribution by capillary flow porometry and mercury porosimetry, as well as BET surface area measurements. Electrochemical characterization through linear sweep voltammetry and EIS measurements was performed in a custom half cell. The results show that the overall performance of the GDE based on low-cost iron compounds was comparable to existing GDE formulations, while improvements could be achieved regarding the overpotential in the kinetic region. Nevertheless, future investigations concerning the gas purity and long-term stability of the GDEs will be the next steps of the electrode development.
Exclusive Papers on Environmentally Friendly Catalysis in China
Authors: Dai Hongxing , Wang Xiang , Zhu Yujun , Huang Haibao , Zhao Yunkun
Published: September 2023

With the development of modern industries, environmental pollution has become a serious and urgent issue [...]
Quantum Dot Supernova-like-Shaped Arsenic (III) Sulfide-Oxide/Polypyrrole Thin Film for Optoelectronic Applications in a Wide Optical Range from Ultraviolet to Infrared
Authors: H. Alkallas Fatemah , M. Elsayed Asmaa , Ben Gouider Trabelsi Amira , Rabia Mohamed
Published: September 2023

A quantum dot (QD) thin film of arsenic (III) oxide-hydroxide/polypyrrole (As2S3-As2O3/Ppy) with a supernova-like shape has been developed for optoelectronic applications across a wide optical range, spanning from ultraviolet (UV) to infrared (IR). The fabrication process involves the polymerization of pyrrole to form Ppy in the presence of NaAsO2 and K2S2O8. The resulting QD exhibits a remarkable morphology characterized by a supernova-like structure and a porous nature with a particle size of 4 nm. The unique morphology of the QD contributes to its optical properties. The material demonstrates a maximum optical absorbance that extends up to 600 nm. The chemical structure of the composite has been proved using various characterization techniques. The As2S3-As2O3/Ppy QD thin film holds significant potential for optoelectronic applications, particularly in light detection across multiple optical regions. Its sensitivity has been evaluated through the measurement of photoresponsivity (R), yielding a high value of 0.31 mA/W. This indicates a substantial current density (Jph) of 0.031 mA/cm2 at a wavelength of 340 nm. Additionally, the detectivity (D) of the photodetector has been calculated based on these values, resulting in a detection capability of 6.9 × 107 Jones. This indicates the ability to detect low levels of photons using this photodetector. The highly reproducible nature of this photodetector enables its application in various optoelectronic systems. The As2S3-As2O3/Ppy QD thin film offers great promise as a versatile optoelectronic application with its wide optical range, excellent sensitivity, and detectivity.
ODF2 Negatively Regulates CP110 Levels at the Centrioles/Basal Bodies to Control the Biogenesis of Primary Cilia
Authors: Otto Madeline , Hoyer-Fender Sigrid
Published: September 2023

Primary cilia are essential sensory organelles that develop when an inhibitory cap consisting of CP110 and other proteins is eliminated. The degradation of CP110 by the ubiquitin-dependent proteasome pathway mediated by NEURL4 and HYLS1 removes the inhibitory cap. Here, we investigated the suitability of rapamycin-mediated dimerization for centriolar recruitment and asked whether the induced recruitment of NEURL4 or HYLS1 to the centriole promotes primary cilia development and CP110 degradation. We used rapamycin-mediated dimerization with ODF2 to induce their targeted recruitment to the centriole. We found decreased CP110 levels in the transfected cells, but independent of rapamycin-mediated dimerization. By knocking down ODF2, we showed that ODF2 controls CP110 levels. The overexpression of ODF2 is not sufficient to promote the formation of primary cilia, but the overexpression of NEURL4 or HYLS1 is. The co-expression of ODF2 and HYLS1 resulted in the formation of tube-like structures, indicating an interaction. Thus, ODF2 controls primary cilia formation by negatively regulating the concentration of CP110 levels. Our data suggest that ODF2 most likely acts as a scaffold for the binding of proteins such as NEURL4 or HYLS1 to mediate CP110 degradation.
Lymphatic Endothelial-to-Myofibroblast Transition: A Potential New Mechanism Underlying Skin Fibrosis in Systemic Sclerosis
Authors: Rosa Irene , Romano Eloisa , Fioretto Bianca Saveria , El Aoufy Khadija , Bellando-Randone Silvia , Matucci-Cerinic Marco , Manetti Mirko
Published: September 2023

At present, only a few reports have addressed the possible contribution of the lymphatic vascular system to the pathogenesis of systemic sclerosis (SSc). Based on the evidence that blood vascular endothelial cells can undertake the endothelial-to-myofibroblast transition (EndMT) contributing to SSc-related skin fibrosis, we herein investigated whether the lymphatic endothelium might represent an additional source of profibrotic myofibroblasts through a lymphatic EndMT (Ly-EndMT) process. Skin sections from patients with SSc and healthy donors were immunostained for the lymphatic endothelial cell-specific marker lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1) in combination with α-smooth muscle actin (α-SMA) as the main marker of myofibroblasts. Commercial human adult dermal lymphatic microvascular endothelial cells (HdLy-MVECs) were challenged with recombinant human transforming growth factor-β1 (TGFβ1) or serum from SSc patients and healthy donors. The expression of lymphatic endothelial cell/myofibroblast markers was measured by quantitative real-time PCR, Western blotting and immunofluorescence. Collagen gel contraction assay was performed to assess myofibroblast-like cell contractile ability. Lymphatic endothelial cells in intermediate stages of the Ly-EndMT process (i.e., coexpressing LYVE-1 and α-SMA) were found exclusively in the fibrotic skin of SSc patients. The culturing of HdLy-MVECs with SSc serum or profibrotic TGFβ1 led to the acquisition of a myofibroblast-like morphofunctional phenotype, as well as the downregulation of lymphatic endothelial cell-specific markers and the parallel upregulation of myofibroblast markers. In SSc, the Ly-EndMT might represent a previously overlooked pathogenetic process bridging peripheral microlymphatic dysfunction and skin fibrosis development.
Human iPSCs as Model Systems for BMP-Related Rare Diseases
Authors: Sánchez-Duffhues Gonzalo , Hiepen Christian
Published: September 2023

Disturbances in bone morphogenetic protein (BMP) signalling contribute to onset and development of a number of rare genetic diseases, including Fibrodysplasia ossificans progressiva (FOP), Pulmonary arterial hypertension (PAH), and Hereditary haemorrhagic telangiectasia (HHT). After decades of animal research to build a solid foundation in understanding the underlying molecular mechanisms, the progressive implementation of iPSC-based patient-derived models will improve drug development by addressing drug efficacy, specificity, and toxicity in a complex humanized environment. We will review the current state of literature on iPSC-derived model systems in this field, with special emphasis on the access to patient source material and the complications that may come with it. Given the essential role of BMPs during embryonic development and stem cell differentiation, gain- or loss-of-function mutations in the BMP signalling pathway may compromise iPSC generation, maintenance, and differentiation procedures. This review highlights the need for careful optimization of the protocols used. Finally, we will discuss recent developments towards complex in vitro culture models aiming to resemble specific tissue microenvironments with multi-faceted cellular inputs, such as cell mechanics and ECM together with organoids, organ-on-chip, and microfluidic technologies.
MicroRNA-375 Is Induced during Astrocyte-to-Neuron Reprogramming and Promotes Survival of Reprogrammed Neurons when Overexpressed
Authors: Chen Xuanyu , Sokirniy Ivan , Wang Xin , Jiang Mei , Mseis-Jackson Natalie , Williams Christine , Mayes Kristopher , Jiang Na , Puls Brendan , Du Quansheng , Shi Yang , Li Hedong
Published: September 2023

While astrocyte-to-neuron (AtN) reprogramming holds great promise in regenerative medicine, the molecular mechanisms that govern this unique biological process remain elusive. To understand the function of miRNAs during the AtN reprogramming process, we performed RNA-seq of both mRNAs and miRNAs on human astrocyte (HA) cultures upon NeuroD1 overexpression. Bioinformatics analyses showed that NeuroD1 not only activated essential neuronal genes to initiate the reprogramming process but also induced miRNA changes in HA. Among the upregulated miRNAs, we identified miR-375 and its targets, neuronal ELAVL genes (nELAVLs), which encode a family of RNA-binding proteins and were also upregulated by NeuroD1. We further showed that manipulating the miR-375 level regulated nELAVLs’ expression during NeuroD1-mediated reprogramming. Interestingly, miR-375/nELAVLs were also induced by the reprogramming factors Neurog2 and ASCL1 in HA, suggesting a conserved function to neuronal reprogramming, and by NeuroD1 in the mouse astrocyte culture and spinal cord. Functionally, we showed that miR-375 overexpression improved NeuroD1-mediated reprogramming efficiency by promoting cell survival at early stages in HA and did not appear to compromise the maturation of the reprogrammed neurons. Lastly, overexpression of miR-375-refractory ELAVL4 induced apoptosis and reversed the cell survival-promoting effect of miR-375 during AtN reprogramming. Together, we demonstrated a neuroprotective role of miR-375 during NeuroD1-mediated AtN reprogramming.
Investigation of Overflow-Water-Assisted Femtosecond Laser-Induced Plasma Modulation of Microchannel Morphology
Authors: Zhao Runhan , Ma Chenbin , Gao Xiaojie , Zhang Hailong , Wang Xingsheng
Published: September 2023

Laser-induced plasma micromachining (LIPMM) process is an effective approach to create microfeatures with high aspect ratio (AR) and reduced heat affected zone (HAZ). Therefore, LIPMM plays a crucial role in improving the morphology of microchannels. In this study, microchannels were fabricated using a femtosecond laser with two distinct sets of process parameters under three different processing methods: overflow-water-assisted laser-induced plasma micromachining (OF-LIPMM), laser direct writing (LDW), and static water laser-induced plasma micromachining (S-LIPMM). Furthermore, single-factor experiments were conducted to systematically analyze the effects of four parameters, namely single-pulse energy, scanning speed, scanning times, and frequency, on the HAZ, AR, and material removal rate (MRR) of the microchannels. Finally, the optimized parameters determined from the single-factor experiments were applied for large-scale grid fabrication on a surface. The experimental results revealed that OF-LIPMM enables the creation of two different kinds of microchannel surfaces: one microchannel was fabricated with a higher AR of 3:1 and a larger HAZ, while another microchannel was created with a lower AR of 1:1 and a reduced HAZ. Moreover, the parameters investigated in the single-factor experiments can be applied to large-scale processing. The results also indicate that variations of the scanning speed, frequency, and single-pulse energy have similar effects on the machining characteristics of the three processing methods. The findings enable the generation of microchannels with favorable morphological characteristics and have significant implications for the large-scale production of both types of microchannels.
Effect of Different Fibers on Shrinkage Properties and Bonding Properties of Geopolymer Mortar Repair Materials and Analysis of the Mechanism
Authors: Sui Jingyu , Li Xiaoyan , Zhang Hanbin , Xu Fang , Deng Jingjing , Hu Ruiyang , Chen Muqun
Published: September 2023

The geopolymer uses fly ash, slag, and other solid wastes as raw materials and is widely used in building repair, but it is brittle and can be made tougher by incorporating fibers. In this study, polyvinyl alcohol (PVA) fibers, polyoxymethylene (POM) fibers, and polypropylene (PP) fibers were incorporated into the geopolymer mortar repair material, and the geopolymer was tested by changing the amount of fibers incorporation as well as the type. The effect of different fibers on the geopolymer mortar repair material was analyzed by comparing the flexural strength, compressive strength, flexural toughness, shrinkage, and bonding properties with cement mortar of different samples. The geopolymer was analyzed by Diffraction of X-rays (XDR) and Scanning Electron Microscopy (SEM) to further understand the hydration products and microstructure of the geopolymer. The results showed that the incorporation of fibers reduced the flexural strength and increased the compressive strength of the geopolymer mortar repair material; the mechanical properties of the geopolymer mortar repair material decreased with the increase in fiber incorporation, and the best mechanical properties of the geopolymer mortar repair material incorporated with 1.0% PP fibers; the toughening effect of PVA fiber was best when the amount of fiber incorporated was the same; the shrinkage properties of the geopolymer were good and had little effects on the building repair; the bonding properties of repaired specimens repaired with geopolymer mortar repair materials depended on the bonding area of the fracture surface, and the bonding area was enhanced with the increase in fiber incorporation; the XRD pattern showed that the hydration products of the geopolymer were mainly CaCO3 and C–S–H gels.
In Situ Synthesis of Graphene Oxide-Sealed LDHs Coatings: A Novel Approach to Enhancing Corrosion Resistance and Tribological Performance on Magnesium Alloys
Authors: Li Weiming , Wang Ping , Wang Shaoqing , Duan Zhihong , Liu Lele , Wang Yimeng , Xu Min
Published: September 2023

This study introduces an innovative approach to enhancing the corrosion resistance and tribological performance of magnesium alloys by in situ growing zinc-aluminum layered double hydroxide (ZnAl-LDHs) with graphene oxide (GO) sealing. Traditional LDHs coatings exhibit limitations in corrosion protection due to their porous structure. This paper advances the LDHs coating technology by integrating GO, forming a composite LDHs/GO coating on magnesium alloys. The novel incorporation of GO provides a unique two-layered defense system against corrosion: the GO layer serves as a high-resistance barrier to corrosive agents, while the LDHs layer absorbs NO3− ions, offering a secondary protection. The coating’s properties were meticulously characterized using techniques such as scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared (FTIR) Raman spectroscopy, electrochemical assays, and friction-wear tests. Experimental findings reveal that the synergistic action between LDHs and GO results in significant improvements in corrosion resistance and friction reduction. Specifically, GO’s adherence to the LDHs coating’s pores and its ability to transfer into the friction layer during wear significantly enhances the coating’s integrity and stability. The successful in situ synthesis of LDHs /GO coatings opens new horizons for composite coatings, with potential implications across various industrial applications.
Study on the Effectiveness of Water Mist on Suppressing Thermal Runaway in LiFePO4 Batteries
Authors: Li Qian , Yu Jinshan , Liu Guangzhen , Ma Xiaoguang , Si Wei , Hu Xiangyu , Zhu Guoqing , Liu Tong
Published: September 2023

Lithium-ion batteries experience rapid temperature increases with a high risk of combustion and explosion during thermal runaway, and water mist has been considered as one of the most effective cooling strategies. The water mist field can be impacted by the safety valve airflow, subsequently affecting the cooling characteristics. In this paper, the water mist nozzle with a fixed working pressure is located 1 m above the 100 Ah LiFePO4 battery to suppress the thermal runaway, and the cooling characteristics under various stages have been compared and analyzed. The results show that the development of thermal runaway can be inhibited before thermal runaway is initiated, and the water mist presents a better cooling effect after the battery safety valve is opened. The critical accumulation heat density of 155 kJ/kg has been identified, which is the threshold for thermal runaway suppression. The confrontation between water mist and the flame has been analyzed, and the water mist droplets cannot fall on the battery surface, resulting in a poor cooling rate of 0.57 kW. This means the suppression effect of water mist will be affected by the airflow impact of the safety valve.
Thailand Raw Water Quality Dataset Analysis and Evaluation
Authors: Krohkaew Jaturapith , Nilaphruek Pongpon , Witthayawiroj Niti , Uapipatanakul Sakchai , Thwe Yamin , Crisnapati Padma Nyoman
Published: September 2023

Sustainable water quality data are important for understanding historical variability and trends in river regimes, as well as the impact of industrial waste on the health of aquatic ecosystems. Sustainable water management practices heavily depend on reliable and comprehensive data, prompting the need for accurate monitoring and assessment of water quality parameters. This research describes a reconstructed daily water quality dataset that complements rare historical observations for six station points along the Chao Phraya River in Thailand. Internet of Things technology and a Eureka water probe sensor is used to collect and reconstruct the water quality dataset for the period from June 2022–February 2023, with Turbidity, Optical Dissolved Oxygen, Dissolved Oxygen Saturation, Spatial Conductivity, Acidity/Basicity, Total Dissolved Solids, Salinity, Temperature, Chlorophyll, and Depth as the recorded parameters from six different stations. The presented dataset comprises a total of 211,322 data points, which are separated into six CSV files. The dataset is then evaluated using the Long Short-Term Memory (LSTM) algorithm with a Mean Squared Error (MSE) of 0.0012256, and Root Mean Squared Error (RMSE) of 0.0350080. The proposed dataset provides valuable insights for researchers studying river ecosystems, supporting informed decision-making and sustainable water management practices.
Quantitative Chest X-ray Radiomics for Therapy Response Monitoring in Patients with Pulmonary Tuberculosis
Authors: Du Plessis Tamarisk , Rae William Ian Duncombe , Ramkilawon Gopika , Martinson Neil Alexander , Sathekge Mike Michael
Published: September 2023

Tuberculosis (TB) remains the second leading cause of death globally from a single infectious agent, and there is a critical need to develop improved imaging biomarkers and aid rapid assessments of responses to therapy. We aimed to utilize radiomics, a rapidly developing image analysis tool, to develop a scoring system for this purpose. A chest X-ray radiomics score (RadScore) was developed by implementing a unique segmentation method, followed by feature extraction and parameter map construction. Signature parameter maps that showed a high correlation to lung pathology were consolidated into four frequency bins to obtain the RadScore. A clinical score (TBscore) and a radiological score (RLscore) were also developed based on existing scoring algorithms. The correlation between the change in the three scores, calculated from serial X-rays taken while patients received TB therapy, was evaluated using Spearman’s correlation. Poor correlations were observed between the changes in the TBscore and the RLscore (0.09 (p-value = 0.36)) and the TBscore and the RadScore (0.02 (p-value = 0.86)). The changes in the RLscore and the RadScore had a much stronger correlation of 0.22, which is statistically significant (p-value = 0.02). This shows that the developed RadScore has the potential to be a quantitative monitoring tool for responses to therapy.
The Role of Ultrasound in Epicutaneo-Caval Catheter Insertion in Neonates: Systematic Review, Meta-Analysis and Future Perspectives
Authors: D’Andrea Vito , Cascini Valentina , Russo Rosellina , Perri Alessandro , Prontera Giorgia , Ancora Gina , Vento Giovanni , Lisi Gabriele , Barone Giovanni
Published: September 2023

Chest and abdominal X-rays after the insertion of an epicutaneo-caval catheter in infants are the standard method of checking the tip location in many neonatal intensive care units. The role of ultrasound in the tip location of the epicutaneo-caval catheter in neonates has been the subject of many recent studies. This systematic review investigates the accuracy of epicutaneo-caval catheter tip location by comparing ultrasound and conventional radiology. We performed a systematic literature search in multiple databases. The selection of studies yielded nineteen articles. The systematic review and meta-analysis were performed according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analysis). The analyses showed that ultrasound is a better imaging technique for epicutaneo-caval catheter tip location in the neonatal intensive care unit than conventional radiology. By improving operator training and selecting a standardized echography protocol, ultrasound could become the gold standard for visualizing the epicutaneo-caval catheter tip in the neonatal intensive care unit. This would have some important benefits: (1) increased accuracy in tip location (2); a more rapid use of the central venous access (3); and a significant reduction in radiation exposure.
Orofacial Pain and Dentistry Management: Guidelines for a More Comprehensive Evidence-Based Approach
Authors: Labanca Mauro , Gianò Marzia , Franco Caterina , Rezzani Rita
Published: September 2023

Orofacial pain represents one of the most common health problems that negatively affects the activities of daily living. However, the mechanisms underlying these conditions are still unclear, and their comprehensive management is often lacking. Moreover, even if pain is a common symptom in dentistry, differential diagnostic procedures are needed to exclude other pain origins. Misinterpretation of the pain origin, in fact, can lead to misdiagnosis and to subsequent mismanagement. Pain in the orofacial area is the most common reason for patients to visit the dentist, but this area is complex, and the pain could be associated with the hard and soft tissues of the head, face, oral cavity, or to a dysfunction of the nervous system. Considering that the origins of orofacial pain can be many and varied, a thorough assessment of the situation is necessary to enable the most appropriate diagnostic pathway to be followed to achieve optimal clinical and therapeutic management.
Hepatic Inflammatory Pseudotumor—Focusing on Its Heterogeneity
Authors: Kim Soo Ryang , Kim Soo Ki , Koma Yu-ichiro , Sasaki Motoko , Asai Akira , Nishikawa Hiroki
Published: September 2023

Hepatic inflammatory pseudotumors (IPTs) are defined as benign, non-malignant, non-metastasizing tumors characterized by the presence of myofibroblastic spindle cells, hetorogenous populations of inflammatory cells, particularly plasma cells, lymphocytes and macrophages, as well as locations of fibrosis and necrosis without cellular anaplasia or atypical mitoses. Despite subsequent reports in the references, hepatic IPT remains difficult to diagnose; while posing major issues specifically for its differential diagnosis compared with that of other various benign diseases and malignant hepatic tumors. Histopathological findings are always a requisite for confirming the diagnosis, particularly given that the pathogenesis of IPT remains ambiguous to date. Hepatic IPT is a heterogeneous entity in terms of its clinical features, pathological findings, and pathogenesis. Once the diagnosis is confirmed, however, needless surgery such as wedge resection and lobectomy should be avoided. Here, we discuss the heterogeneity of hepatic IPT, its clinical features, pathological findings, and pathogenesis, and describe its differential diagnosis.
Identification of Autoantibodies to a Hybrid Insulin Peptide in Type 1 Diabetes
Authors: Wenzlau Janet M. , Gu Yong , Michels Aaron , Rewers Marian , Haskins Kathryn , Yu Liping
Published: September 2023

Type 1 diabetes (T1D) is a chronic autoimmune disease that attacks the insulin-producing b cells of the pancreatic islets. Autoantibodies to b cell proteins typically appear in the circulation years before disease onset, and serve as the most accurate biomarkers of T1D risk. Our laboratory has recently discovered novel b cell proteins comprising hybrid proinsulin:islet amyloid polypeptide peptides (IAPP). T cells from a diabetic mouse model and T1D patients are activated by these hybrid peptides. In this study, we asked whether these hybrid molecules could serve as antigens for autoantibodies in T1D and prediabetic patients. We analyzed sera from T1D patients, prediabetics and healthy age-matched donors. Using a highly sensitive electrochemiluminescence assay, sera were screened for binding to recombinant proinsulin:IAPP probes or truncated derivatives. Our results show that sera from T1D patients contain antibodies that bind larger hybrid proinsulin:IAPP probes, but not proinsulin or insulin, at significantly increased frequencies compared to normal donors. Examination of sera from prediabetic patients confirms titers of antibodies to these hybrid probes in more than 80% of individuals, often before seroconversion. These results suggest that hybrid insulin peptides are common autoantigens in T1D and prediabetic patients, and that antibodies to these peptides may serve as valuable early biomarkers of the disease.
Data Fusion Analysis and Synthesis Framework for Improving Disaster Situation Awareness
Authors: Aksit Mehmet , Say Hanne , Eren Mehmet Arda , de Camargo Valter Vieira
Published: September 2023

To carry out required aid operations efficiently and effectively after an occurrence of a disaster such as an earthquake, emergency control centers must determine the effect of disasters precisely and and in a timely manner. Different kinds of data-gathering techniques can be used to collect data from disaster areas, such as sensors, cameras, and unmanned aerial vehicles (UAVs). Furthermore, data-fusion techniques can be adopted to combine the data gathered from different sources to enhance the situation awareness. Recent research and development activities on advanced air mobility (AAM) and related unmanned aerial systems (UASs) provide new opportunities. Unfortunately, designing these systems for disaster situation analysis is a challenging task due to the topological complexity of urban areas, and multiplicity and variability of the available data sources. Although there are a considerable number of research publications on data fusion, almost none of them deal with estimating the optimal set of heterogeneous data sources that provide the best effectiveness and efficiency value in determining the effect of disasters. Moreover, existing publications are generally problem- and system-specific. This article proposes a model-based novel analysis and synthesis framework to determine the optimal data fusion set among possibly many alternatives, before expensive implementation and installation activities are carried out.
Generating Datasets for Real-Time Scheduling on 5G New Radio
Authors: Jin Xi , Chai Haoxuan , Xia Changqing , Xu Chi
Published: September 2023

A 5G system is an advanced solution for industrial wireless motion control. However, because the scheduling model of 5G new radio (NR) is more complicated than those of other wireless networks, existing real-time scheduling algorithms cannot be used to improve the 5G performance. This results in NR resources not being fully available for industrial systems. Supervised learning has been widely used to solve complicated problems, and its advantages have been demonstrated in multiprocessor scheduling. One of the main reasons why supervised learning has not been used for 5G NR scheduling is the lack of training datasets. Therefore, in this paper, we propose two methods based on optimization modulo theories (OMT) and satisfiability modulo theories (SMT) to generate training datasets for 5G NR scheduling. Our OMT-based method contains fewer variables than existing work so that the Z3 solver can find optimal solutions quickly. To further reduce the solution time, we transform the OMT-based method into an SMT-based method and tighten the search space of SMT based on three theorems and an algorithm. Finally, we evaluate the solution time of our proposed methods and use the generated dataset to train a supervised learning model to solve the 5G NR scheduling problem. The evaluation results indicate that our SMT-based method reduces the solution time by 74.7% compared to existing ones, and the supervised learning algorithm achieves better scheduling performance than other polynomial-time algorithms.
Asymptotically Optimal Adversarial Strategies for the Probability Estimation Framework
Authors: Patra Soumyadip , Bierhorst Peter
Published: September 2023

The probability estimation framework involves direct estimation of the probability of occurrences of outcomes conditioned on measurement settings and side information. It is a powerful tool for certifying randomness in quantum nonlocality experiments. In this paper, we present a self-contained proof of the asymptotic optimality of the method. Our approach refines earlier results to allow a better characterisation of optimal adversarial attacks on the protocol. We apply these results to the (2,2,2) Bell scenario, obtaining an analytic characterisation of the optimal adversarial attacks bound by no-signalling principles, while also demonstrating the asymptotic robustness of the PEF method to deviations from expected experimental behaviour. We also study extensions of the analysis to quantum-limited adversaries in the (2,2,2) Bell scenario and no-signalling adversaries in higher (n,m,k) Bell scenarios.
Design, Evolution, and Evaluation of a General Chemistry-Bridging Course
Authors: Reid Scott A.
Published: September 2023

General chemistry I/II courses are important gateway courses for a variety of STEM majors, as poor performance in these courses is often associated with lower rates of student success and retention. Much research has explored preparatory or remedial strategies to improve student outcomes. In this article, we report a different approach, which involved the development of a bridging or intervention course designed to capture students who are not or have not succeeded in general chemistry I and prepare them to retake the course in the following semester or summer. The course was initially developed as an eight-week module in the second half of the fall semester, where students were required to withdraw from general chemistry I prior to enrolling. After three years of this offering modality, with the inception of a winter J-term, the course was redesigned and moved online, where it was taught for another three years. We describe here in detail the design, evolution, and evaluation of this course over the six-year period.
Robust Visual Recognition in Poor Visibility Conditions: A Prior Knowledge-Guided Adversarial Learning Approach
Authors: Yang Jiangang , Yang Jianfei , Luo Luqing , Wang Yun , Wang Shizheng , Liu Jian
Published: September 2023

Deep learning has achieved remarkable success in numerous computer vision tasks. However, recent research reveals that deep neural networks are vulnerable to natural perturbations from poor visibility conditions, limiting their practical applications. While several studies have focused on enhancing model robustness in poor visibility conditions through techniques such as image restoration, data augmentation, and unsupervised domain adaptation, these efforts are predominantly confined to specific scenarios and fail to address multiple poor visibility scenarios encountered in real-world settings. Furthermore, the valuable prior knowledge inherent in poor visibility images is seldom utilized to aid in resolving high-level computer vision tasks. In light of these challenges, we propose a novel deep learning paradigm designed to bolster the robustness of object recognition across diverse poor visibility scenes. By observing the prior information in diverse poor visibility scenes, we integrate a feature matching module based on this prior knowledge into our proposed learning paradigm, aiming to facilitate deep models in learning more robust generic features at shallow levels. Moreover, to further enhance the robustness of deep features, we employ an adversarial learning strategy based on mutual information. This strategy combines the feature matching module to extract task-specific representations from low visibility scenes in a more robust manner, thereby enhancing the robustness of object recognition. We evaluate our approach on self-constructed datasets containing diverse poor visibility scenes, including visual blur, fog, rain, snow, and low illuminance. Extensive experiments demonstrate that our proposed method yields significant improvements over existing solutions across various poor visibility conditions.
Software Design for Airborne GNSS Air Service Performance Evaluation under Ionospheric Scintillation
Authors: Hu Tieqiao , Zhang Gaojian , Zhong Lunlong
Published: September 2023

The performance analysis and evaluation of satellite navigation systems under ionospheric scintillation have been a focal point in the field of modern aviation. With the development and upgrading of satellite navigation systems, the performance indicators and evaluation techniques of these systems also require continuous iteration and optimization. In this study, based on the ionospheric scintillation model and satellite navigation algorithm, we designed a software tool to evaluate the performance of GNSS aviation services under various ionospheric scintillation intensities. The software is implemented in the C/C++ programming language and provides assessment capabilities for different ionospheric scintillation environments and flight phases. By encapsulating the software task modules using technologies such as dynamic link libraries and thread pools, the software can flexibly adjust the ionospheric scintillation intensity and control the flight trajectory. This ensures the strong scalability and reusability of the software. The software supports the performance evaluation of aviation services during all flight phases of global flights and is compatible with GPS, BDS, GALILEO, and GLONASS systems. Through verification of the accuracy, integrity, continuity, and availability of the GNSS system under different flight phases and ionospheric scintillation effects, the effectiveness of the software design has been validated.
Cooperative Environmental Perception Task Offloading for Connected and Autonomous Vehicles
Authors: Lv Pin , Huang Jie , Liu Heng
Published: September 2023

Cooperative environmental perception is an effective way to provide connected and autonomous vehicles (CAVs) with the necessary environmental information. The research goal of this paper is to achieve efficient sharing of cooperative environmental perception information. Hence, a novel vehicular edge computing scheme is proposed. In this scheme, the environmental perception tasks are selected to be offloaded based on their shareability, and the edge server directly delivers the task results to the CAVs who need the perception information. The experimental results show that the proposed task offloading scheme can decrease the perception information delivery latency up to 20%. Therefore, it is an effective way to improve cooperative environmental perception efficiency by taking the shareability of the perception information into consideration.
An Off-Line Error Compensation Method for Absolute Positioning Accuracy of Industrial Robots Based on Differential Evolution and Deep Belief Networks
Authors: Tao Yong , Liu Haitao , Chen Shuo , Lan Jiangbo , Qi Qi , Xiao Wenlei
Published: September 2023

Industrial robots have been increasingly used in the field of intelligent manufacturing. The low absolute positioning accuracy of industrial robots is one of the difficulties in their application. In this paper, an accuracy compensation algorithm for the absolute positioning of industrial robots is proposed based on deep belief networks using an off-line compensation method. A differential evolution algorithm is presented to optimize the networks. Combined with the evidence theory, a position error mapping model is proposed to realize the absolute positioning accuracy compensation of industrial robots. Experiments were conducted using a laser tracker AT901-B on an industrial robot KR6_R700 sixx_CR. The absolute position error of the end of the robot was reduced from 0.469 mm to 0.084 mm, improving the accuracy by 82.14% after the compensation. Experimental results demonstrated that the proposed compensation algorithm could improve the absolute positioning accuracy of industrial robots, as well as its potential uses for precise operational tasks.
Feasibility Study of Closed-Loop Recycling for Plastic Generated from Waste Electrical and Electronic Equipment (WEEE) in South Korea
Authors: Choi Won Hee , Pae Kook Pyo , Kim Nam Seok , Kang Hong Yoon , Hwang Yong Woo
Published: September 2023

Plastics follow a linear economic structure, leading to detrimental environmental effects, such as global warming and ecosystem destruction, through incineration and accumulation throughout their life cycle. This study examined the types, potential generation amounts, and properties of recycled plastics from waste electrical and electronic equipment (WEEE) to assess the feasibility of the closed-loop recycling of plastics from WEEE under South Korea’s EPR system. Actual data from companies were used to determine the factors, such as the processing volume of WEEE. As of 2021, acrylonitrile-butadiene-styrene (53,363 tons), polypropylene (14,320 tons), and polystyrene (8199 tons) were the recycled plastics produced by both large and small WEEE. The properties of recycled plastics meet the specifications of new electrical and electronic products. In addition, an analysis using Life Cycle Assessment (LCA) methodology showed that the recycling effect (avoided emissions) reached 262,033 tons of CO2 eq. per year. Therefore, closed-loop recycling is the most suitable and effective method for reducing greenhouse gases. This paper presents the potential amount of recycled plastics generated from WEEE within South Korea’s regulatory framework, providing valuable foundational data for policy development for promoting the use of recycled plastics.