bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Accuracy of a Blood-Based Biomarker Panel for Colorectal Cancer Detection: A Pilot Study
Authors: Caraballo Elba V. , Centeno-Girona Hilmaris , Torres-Velásquez Brenda Carolina , Martir-Ocasio Madeline M. , González-Pons María , López-Acevedo Sheila N. , Cruz-Correa Marcia
Published: December 2024

Background: Colorectal cancer (CRC) is a leading cause of death worldwide. Despite its preventability through screening, compliance still needs to improve due to the invasiveness of current tools. There is a growing demand for validated molecular biomarker panels for minimally invasive blood-based CRC screening. This study assessed the diagnostic accuracy of four promising blood-based CRC biomarkers, individually and in combination. Methods: This case–control study involved plasma samples from 124 CRC cases and 124 age- and sex-matched controls. Biomarkers tested included methylated DNA encoding the Septin-9 gene (mSEPT9) using Epi proColon® 2.0 CE, insulin-like growth factor binding protein 2 (IGFBP2), dickkopf-3 (DKK3), and pyruvate kinase M2 (PKM2) by ELISA. Diagnostic accuracy was measured using the receiver operating characteristic (ROC), area under the curve (AUC), as well as sensitivity and specificity. Results: Diagnostic accuracy for mSEPT9, IGFBP2, DKK3, and PKM2 was 62.9% (95% CI: 56.8–62.9%), 69.7% (95% CI: 63.1–69.7%), 61.6% (95% CI: 54.6–61.6%), and 50.8% (95% CI: 43.4–50.8%), respectively. The combined biomarkers yielded an AUC of 74.4% (95% CI: 68.1–80.6%), outperforming all biomarkers except IGFBP2. Conclusions: These biomarkers show potential for developing a minimally invasive CRC detection tool as an alternative to existing approaches, potentially increasing adherence, early detection, and survivorship.
Antibody-Based Immunotherapies for the Treatment of Hematologic Malignancies
Authors: Jureczek Justyna , Kałwak Krzysztof , Dzięgiel Piotr
Published: December 2024

Despite the great advancements in treatment strategies for hematological malignancies (HMs) over the years, their effective treatment remains challenging. Conventional treatment strategies are burdened with several serious drawbacks limiting their effectiveness and safety. Improved understanding of tumor immunobiology has provided novel anti-cancer strategies targeting selected immune response components. Currently, immunotherapy is counted as the fourth pillar of oncological treatment (together with surgery, chemo- and radiotherapy) and is becoming standard in the treatment regimen, alone or in combination therapy. Several categories of immunotherapies have been developed and are currently being assessed in clinical trials for the treatment of blood cancers, including immune checkpoint inhibitors, antigen-targeted antibodies, antibody–drug conjugates, tumor vaccines, and adoptive cell therapies. However, monoclonal antibodies (mAbs) and their derivatives have achieved the most notable clinical outcome so far. Since the approval of rituximab for treating B-cell malignancies, the availability of mAbs against tumor-specific surface molecules for clinical use has flourished. Antibody-based therapy has become one of the most successful strategies for immunotherapeutic cancer treatment in the last few decades, and many mAbs have already been introduced into standard treatment protocols for some hematologic malignancies. To further increase the efficacy of mAbs, they can be conjugated to radioisotopes or cytostatic drugs, so-called antibody–drug conjugates. Moreover, with the growing recognition of T-cell immunity’s role in cancer development, strategies aimed at enhancing T cell activation and inhibiting mechanisms that suppress T cell function are actively being developed. This review provides a comprehensive overview of the current status of immunotherapeutic strategies based on monoclonal antibodies and their derivatives, including antibody–drug conjugates, bispecific T-cell engagers, and checkpoint inhibitors, approved for the treatment of various HMs.
Additional Value of Pertechnetate Scintigraphy to American College of Radiology Thyroid Imaging Reporting and Data Systems and European Thyroid Imaging Reporting and Data Systems for Thyroid Nodule Classification in Euthyroid Patients
Authors: Sollmann Lea , Eveslage Maria , Danzer Moritz Fabian , Schäfers Michael , Heitplatz Barbara , Conrad Elke , Hescheler Daniel , Riemann Burkhard , Noto Benjamin
Published: December 2024

Background: Thyroid nodules are common yet remain a diagnostic challenge. While ultrasound and Thyroid Imaging Reporting and Data Systems (TIRADS) are accepted as standard, the use of thyroid scintigraphy in euthyroid patients is debated. The European Association of Nuclear Medicine advocates it, whereas the American Thyroid Association and European Thyroid Association do not. However, it has not been evaluated whether scintigraphy adds value to TIRADS in a multimodal approach. Our study addresses this gap by assessing the impact of integrated pertechnetate scintigraphy on TIRADS accuracy. Methods: The diagnostic performance of ACR-TIRADS, EU-TIRADS, pertechnetate scintigraphy, and multimodal models were retrospectively analyzed for 322 nodules (231 benign, 91 malignant) in 208 euthyroid patients with histopathology as a reference. Generalized estimating equations were used for statistical analysis. Results: On scintigraphy, 210 nodules were hypofunctional, 99 isofunctional, and 13 hyperfunctional. The AUC for thyroid scintigraphy, ACR-TIRADS, and EU-TIRADS were 0.6 (95% CI: 0.55–0.66), 0.83 (95% CI: 0.78–0.88), and 0.78 (95% CI: 0.72–0.83). Integrating scintigraphy with ACR-TIRADS and EU-TIRADS slightly increased diagnostic accuracy (AUC 0.86 vs. 0.83, p = 0.039 and AUC 0.80 vs. 0.78, p = 0.008) and adjusted the malignancy probability for intermediate risk TIRADS categories, with iso- or hyperfunctioning nodules in ACR-TIRADS-TR4 or EU-TIRADS-4 showing comparable malignancy probabilities as hypofunctioning nodules in TR3 or EU-TIRADS-3, respectively. Conclusions: Integrating thyroid scintigraphy with ACR- or EU-TIRADS moderately improves diagnostic performance, potentially benefiting management, especially in complex cases like multinodular goiter or indeterminate FNA. Further research is warranted to validate these findings and explore their clinical implications.
Joint-Sparing Resection of Juxta-Articular Primary Tumors of the Knee Using Titanium Alloy 3D-Printed Cutting Guides and Allograft Reconstruction
Authors: Scorianz Maurizio , Scoccianti Guido , Guariento Lorenzo , Carfagni Monica , Campanacci Domenico Andrea
Published: December 2024

Background: Joint-sparing resection of juxta-articular knee tumors is challenging. With the development of 3D printing technology, custom-made cutting guides were introduced with the aim to improve the accuracy of tumor resection margins and to shape the allograft for adequate matching in biological reconstruction. Materials and Methods: Between December 2017 and July 2023, 13 patients underwent joint-sparing juxta-articular resection of the knee for a primary bone tumor at our institution. Resection was performed using a custom-made 3D-printed titanium alloy cutting guide and reconstruction was performed using a custom-shaped allograft. The mean follow up was 50 months (min 14–max 81). The study of cutting accuracy was performed by digital examination of CT images of the resection specimen in eight patients. Results: The average cutting error was 2.3 mm. Surgical margins were wide in all patients. Four patients developed postoperative complications that led to the removal of the allograft in one case. The average functional result according to the Musculoskeletal Tumor Society Score was 26 (min 14–max 30), and according to the Oxford Knee Score it was 44 (min 22–max 48). Conclusions: Custom-made titanium cutting guides resulted effective in improving the accuracy of joint-sparing juxta-articular resection of the knee and allograft matching.
Connexin-43 in Cancer: Above and Beyond Gap Junctions!
Authors: Paunikar Shishir , Tamagnone Luca
Published: December 2024

Connexin-43 (Cx43) is the most characterized gap junction protein, primarily involved in the Gap Junctional Intercellular Communication (GJIC) between adjacent cells to facilitate molecule exchange and the formation of a signaling network. It is increasingly evident that the importance of Cx43 is not only limited to its GJIC function, but rather includes its role in connecting the intracellular and extracellular environment by forming membrane hemichannels, as well as its intracellular signaling function mediated by its C-terminal tail (Cx43-CT). Notably, Cx43 has been implicated in a variety of cancers, with earlier notions suggesting a tumor-suppressor function, whereas new studies shed light on its pro-tumorigenic role. Moreover, apart from GJIC-based activities, the relevance of the non-canonical functions of Cx43 in tumor progression is being actively studied. This review provides an analysis of the current research on the pro-tumorigenic roles of Cx43, with a focus on Cx43-CT interactions and the function of hemichannels in cancer progression. A better understanding of the multifaceted functions of Cx43 in cancer biology could foster its recognition as a pivotal target for the development of innovative therapeutic strategies.
Acute Promyelocytic Leukemia-like AML: Genetic Perspective and Clinical Implications
Authors: Guarnera Luca , Fabiani Emiliano , Falconi Giulia , Silvestrini Giorgia , Catanoso Maria Luigia , Divona Mariadomenica , Voso Maria Teresa
Published: December 2024

Acute promyelocytic leukemia (APL) is a rare type of AML, characterized by the t(15;17) translocation and accounting for 8–15% of cases. The introduction of target therapies, such as all-trans retinoic acid (ATRA) and arsenic trioxide (ATO), radically changed the management of APL, making it the most curable AML subtype. However, a small percentage (estimated to be 2%) of AML presenting with APL-like morphology and/or immunophenotype lacks t(15;17). This rare APL-like AML group, whose first case was described in the early 1990s, now includes over 40 entities. These diseases present great heterogeneity in terms of genetic lesions, clinical presentation, sensitivity to targeted agents and chemotherapy, and prognosis. Furthermore, the diagnosis is very challenging. Thus, in this paper, we aim to comprehensively review the literature reports and studies addressing APL-like entities, investigate the biological mechanisms of leukemogenesis, evaluate the clinical characteristics, and discuss future lines of research and possible clinical approaches.
Distinct UPR and Autophagic Functions Define Cell-Specific Responses to Proteotoxic Stress in Microglial and Neuronal Cell Lines
Authors: Domínguez-Martín Helena , Gavilán Elena , Parrado Celia , Burguillos Miguel A. , Daza Paula , Ruano Diego
Published: December 2024

Autophagy is a catabolic process involved in different cellular functions. However, the molecular pathways governing its potential roles in different cell types remain poorly understood. We investigated the role of autophagy in the context of proteotoxic stress in two central nervous system cell types: the microglia-like cell line BV2 and the neuronal-like cell line N2a. Proteotoxic stress, induced by proteasome inhibition, produced early apoptosis in BV2 cells, due in part to a predominant activation of the PERK-CHOP pathway. In contrast, N2a cells showcased greater resistance and robust induction of the IRE1α-sXbp1 arm of the UPR. We also demonstrated that proteotoxic stress activated autophagy in both cell lines but with different kinetics and cellular functions. In N2a cells, autophagy restored cellular proteostasis, while in BV2 cells, it participated in regulating phagocytosis. Finally, proteotoxic stress predominantly activated the mTORC2-AKT-FOXO1-β-catenin pathway in BV2 cells, while N2a cells preferentially induced the PDK1-AKT-FOXO3 axis. Collectively, our findings suggest that proteotoxic stress triggers cell-specific responses in microglia and neurons, with different physiological outcomes.
Comparison of Endoplasmic Reticulum Stress and Pyroptosis Induced by Pathogenic Calcium Oxalate Monohydrate and Physiologic Calcium Oxalate Dihydrate Crystals in HK-2 Cells: Insights into Kidney Stone Formation
Authors: Nong Wei-Jian , Tong Xin-Yi , Ouyang Jian-Ming
Published: December 2024

Endoplasmic reticulum stress (ERS) can activate pyroptosis through CHOP and TXNIP; however, the correlation between this process and the formation of kidney stones has not been reported. The purpose is to investigate the effects of calcium oxalate monohydrate (COM) and calcium oxalate dihydrate (COD) on ERS and pyroptosis in HK-2 cells and to explore the formation mechanism of calcium oxalate stones. HK-2 cells were injured by 3 μm COM and COD. COM and COD significantly upregulated the expression levels of GRP78, CHOP, TXNIP, and pyroptosis-related proteins (NLRP3, caspase-1, GSDMD-N, and IL-1β). Fluorescence colocalization revealed that COM induced pyroptosis by inducing the interaction between TXNIP and NLRP3. Both COM and COD crystals can induce ERS and pyroptosis in HK-2 cells. COM induces the interaction with NLRP3 by the upregulation of CHOP and TXNIP and then promotes pyroptosis, while COD only promotes pyroptosis by the upregulation of CHOP. The cytotoxicity and the ability of COM to promote crystal adhesion and aggregation are higher than COD, suggesting that COM is more dangerous for calcium oxalate kidney stone formation.
NEK2 Phosphorylates RhoGDI1 to Promote Cell Proliferation, Migration and Invasion Through the Activation of RhoA and Rac1 in Colon Cancer Cells
Authors: Lim Jeewon , Hwang Yo-Sep , Kim Jong-Tae , Yoon Hyang-Ran , Park Hyo-Min , Han Jahyeong , Kwon Taeho , Lee Kyung-Ho , Cho Hee-Jun , Lee Hee-Gu
Published: December 2024

Rho guanine nucleotide dissociation inhibitor 1 (RhoGDI1) plays a critical role in regulating the activity of Rho guanosine triphosphatases (GTPases). Phosphorylation of RhoGDI1 dynamically modulates the activation of Rho GTPases, influencing cell proliferation and migration. This study explored the involvement of Never In Mitosis A (NIMA)-related serine/threonine protein kinase 2 (NEK2) in phosphorylating RhoGDI1 and its implications in cancer cell behavior associated with tumor progression. We employed GST pull-down assays and immunoprecipitation to investigate the interaction between NEK2 and RhoGDI1. Truncation fragments identified the region of RhoGDI1 responsible for binding with NEK2. Phosphorylation assays determined the site of NEK2-mediated phosphorylation on RhoGDI1. Functional assays were conducted using overexpression of the RhoGDI1 substitution mutant to assess their impact on cancer cell behavior. NEK2 directly bound to RhoGDI1 and phosphorylated it at Ser174. This phosphorylation event facilitated cancer cell proliferation and motility by activating RhoA and Rac1. The RhoGDI1 aa 112–134 region was critical for the binding to NEK2. Disruption of the NEK2–RhoGDI1 interaction through overexpression of a RhoGDI1 truncated fragment (aa 112–134) led to diminished RhoGDI1 phosphorylation and RhoA/Rac1 activation induced by NEK2, resulting in reduced cancer cell proliferation and migration. Moreover, in vivo studies showed reduced tumor growth and lung metastasis when the NEK2–RhoGDI1 interaction was disrupted. This study indicates that NEK2 promotes the metastatic behaviors of cancer cells by activating RhoA and Rac1 by phosphorylating RhoGDI1.
PML Nuclear Bodies and Cellular Senescence: A Comparative Study of Healthy and Premature Aging Syndrome Donors’ Cells
Authors: Smirnov Eugene Y. , Silonov Sergey A. , Shmidt Eva A. , Nozdracheva Aleksandra V. , Pleskach Nadezhda M. , Kuranova Mirya L. , Gavrilova Anastasia A. , Romanovich Anna E. , Kuznetsova Irina M. , Turoverov Konstantin K. , Fonin Alexander V.
Published: December 2024

Natural aging and age-related diseases involve the acceleration of replicative aging, or senescence. Multiple proteins are known to participate in these processes, including the promyelocytic leukemia (PML) protein, which serves as a core component of nuclear-membrane-less organelles known as PML nuclear bodies (PML-NBs). In this work, morphological changes in PML-NBs and alterations in PML protein localization at the transition of primary fibroblasts to a replicative senescent state were studied by immunofluorescence. The fibroblasts were obtained from both healthy donors and donors with premature aging syndromes (ataxia-telangiectasia and Cockayne syndrome). Our data showed an increase in both the size and the number of PML-NBs, along with nuclear enlargement in senescent cells, suggesting these changes could serve as potential cellular aging markers. Bioinformatic analysis demonstrated that 30% of the proteins in the PML interactome and ~45% of the proteins in the PML-NB predicted proteome are directly associated with senescence and aging processes. These proteins are hypothesized to participate in post-translational modifications and protein sequestration within PML-NBs, thereby influencing transcription factor regulation, DNA damage response, and negative regulation of apoptosis. The findings confirm the significant role of PML-NBs in cellular aging processes and open new avenues for investigating senescence mechanisms and age-associated diseases.
The Flip Side of the Coin: Giftedness in Pediatric Acute-Onset Neuropsychiatric Syndrome
Authors: Calaprice Denise , Terreri Ryan , Whitty Christopher , Whitty Ryan , Tona Janice
Published: December 2024

Background/Objectives: Individuals with Pediatric Acute-onset Neuropsychiatric Syndrome (PANS), an immune-modulated disorder, experience exacerbation-related neuropsychiatric symptoms, functional impairments, and high rates of developmental diagnosis. The literature describes links between giftedness and mental illness, and giftedness and autoimmune disorders. We sought to explore rates of giftedness among children with PANS as perceived by their caregivers, and to examine whether giftedness was related to PANS symptom severity, persistence, or duration. Methods: Data were extracted from a larger, 146-item survey, with 680 respondents meeting inclusion criteria of being a parent/guardian of a child with PANS and answering questions regarding perceived giftedness in empathy, social skills, verbal ability, reading, memory, math, creativity, or “other.” Results: In all, 604 respondents indicated some type of giftedness; the categories of giftedness were each endorsed by 30–57% of respondents. We found no significant associations between giftedness and severity of worst symptoms, persistence of symptoms, or length of time since symptom onset, once Bonferonni corrections were applied. Significantly more females than males were identified as gifted in creativity, but no other sex-related differences were seen. Thematic analysis of optional comments revealed three themes: (1) Elaboration on Types of Giftedness; (2) Objective Basis for Perceptions of Giftedness; and (3) Impact of PANS on Giftedness. Conclusions: The rate of giftedness reported by parents of PANS subjects in this study is much higher than would be expected in the general population, even when adjusting generously for potential overestimation. This study of the “flip side” of PANS should serve as impetus for future studies regarding giftedness in this population; a robust finding of exceptionally high rates of giftedness would have implications for diagnosis, interpretation of symptoms (for example, perfectionism and social challenges) and disease management.
Extended Lifetime of Dual-Layer Yttria-Stabilized Zirconia APS/Gadolinium Zirconate SPS Thermal Barrier Coatings in Furnace Cycle Tests
Authors: Igel Jens , Razak Raseem Ahmed , Mack Daniel Emil , Guillon Olivier , Vaßen Robert
Published: December 2024

Gadolinium zirconate (Gd2Zr2O7, GZO) has been investigated for two decades as a thermal barrier coating (TBC) material in gas turbines. The advantages of this material over conventional yttria-stabilized zirconia (YSZ) are its lower thermal conductivity, phase stability, and low sintering tendency at elevated temperatures above 1200 °C. However, a major disadvantage is the low fracture toughness of the material and the reaction with the thermally growing oxide layer (TGO). As a result, single-layer GZO coatings cannot be used as TBCs. To overcome these challenges, the present study focuses on the development of double-layer TBC systems, produced with a single gun to keep the manufacturing time low. The respective layers were optimized for specific requirements using a porous atmospheric plasma spray (APS)-YSZ interlayer covered by a suspension plasma sprayed (SPS)-GZO top layer. In furnace cycling tests at 1100 °C, the double-layer systems developed in this study were able to achieve a significant increase in thermal cycle life compared to single-layer APS-YSZ coatings. In addition, the failure mechanism after thermal cycling was investigated, and phase analysis was performed using XRD. The examination of Young’s modulus and the hardness of the layers revealed sintering in the GZO layer due to thermal cycling, while the APS layer showed only minor changes.
The Effects of Surface Plasma Carburization on the Microstructure and Molten Salt Corrosion Resistance of Ta
Authors: Lv Xuming , Wei Dongbo , Huang Xianpu , Gao Zeyu , Zhang Pingze
Published: December 2024

In order to enhance the corrosion resistance of tantalum, the double-glow plasma (DGP) metallurgy technique was used to prepare TaC coatings on the tantalum. The morphology, microstructure, and phase constituents of TaC were examined by scanning electron microscopy (SEM) and X-ray diffraction (XRD). Nano-indentation tests were used to evaluate the mechanical properties of the coatings. The specimens were immersed in NaCl-KCl molten salt at 830 °C to evaluate their corrosion resistance. The results showed that the coating prepared by the DGP technique has a thickness of approximately 5 µm, the diffusion layer has a thickness of 2.5 µm, and the nano-indentation hardness is measured to be 17.27 GPa. The high-temperature stable ceramic phase enhances the high-temperature oxidation resistance of pure tantalum (Ta), while the dense corroded surface and oxidation products improve the anti-corrosion property of TaC coatings.
Batch Cooling Crystallization of a Model System Using Direct Nucleation Control and High-Performance In Situ Microscopy
Authors: Budimir Sacher Josip , Bolf Nenad , Sejdić Marko
Published: December 2024

The aim of this study was to investigate the use of automated high performance in situ microscopy (HPM) for monitoring and direct nucleation control (DNC) during cooling crystallization. Compared to other techniques, HPM enables the detection of small crystals in the range of 1 to 10 μm. Therefore, a novel DNC-controlled variable was investigated to determine the potential improvement of the method. The laboratory system and process control software were developed in-house. A well-studied crystallization model system, the seeded batch cooling crystallization of α-glycine from water, was investigated under normal conditions and temperatures below 60 °C. It was postulated that length-weighted edge-to-edge counts in the range of 1 to 10 μm would be most sensitive to the onset of secondary nucleation and are therefore, used as a control variable. Linear cooling experiments were conducted to determine the initial setpoint for the DNC experiments. Three DNC experiments were then performed with different setpoints and an upper and lower counts limit. It was found that the DNC method can be destabilized with a low setpoint and narrow counts limits. In addition, the new controlled variable is highly sensitive to the formation of bubbles at the microscope window and requires careful evaluation. To address the advantages of the DNC method, an additional linear cooling experiment of the same duration was performed, and it was found that the DNC method resulted in a larger average crystal size. Overall, it can be concluded that the HPM method is suitable for DNC control and could be improved by modifying the image processing algorithm.
Efficient Dye Contaminant Elimination and Simultaneous Electricity Production via a Carbon Quantum Dots/TiO2 Photocatalytic Fuel Cell
Authors: Feng Zixuan , Li Xuechen , Lv Yueying , He Jie
Published: December 2024

Conventional wastewater treatment methods do not fully utilize the energy in wastewater. This study uses a photocatalytic fuel cell (PFC) to remove dye impurities and generate electricity with that energy. Pt serves as the PFC’s cathode, while the carbon quantum dots (CQDs)/anatase TiO2 (A-TiO2) serve as its photoanode. The visible light absorption range of A-TiO2 can be increased by combining CQDs with A-TiO2. The composite of CQD and A-TiO2 broadens the absorption edge from 364 nm to 538 nm. TiO2’s different crystal structures and particle sizes impact the PFC’s power generation and dye contaminant removal. The 30 min photodegradation rate of methylene blue by the 20 nm A-TiO2 was 97.3%, higher than that of the 5 nm A-TiO2 (75%), 100 nm A-TiO2 (92.1%), and A-TiO2 (93%). The photocurrent density of the 20 nm A-TiO2 can reach 4.41 mA/cm2, exceeding that of R-TiO2 (0.64 mA/cm2), 5 nm A-TiO2 (1.97 mA/cm2), and 100 nm A-TiO2 (3.58 mA/cm2). The photodegradative and electrochemical test results show that the 20 nm A-TiO2 delivers a better degradation and electrochemical performance than other samples. When the 20 nm A-TiO2 was used in the PFC photoanode, the photocurrent density, open-circuit voltage, and maximum power density of the PFC were found to be 0.6 mA/cm2, 0.41 V, and 0.1 mW/cm2, respectively. The PFC prepared in this study shows a good level of performance compared to recent similar systems.
Ab Initio Investigation of the Mechanics and Thermodynamics of the Cubic EuAlO3 and GdAlO3 Perovskites for Optoelectronic Applications
Authors: Alruqi Adel Bandar , Ongwen Nicholas O.
Published: December 2024

Perovskites are currently becoming common in the field of optoelectronics, owing to their promising properties such as electrical, optical, thermoelectric, and electronic. Although mechanical and thermal properties also play a crucial part in the functioning of the optoelectronic devices, they have scarcely been explored. The present work performed an ab initio study of the mechanical and thermal properties of the cubic EuAlO3 and GdAlO3 perovskites for the first time using density functional theory. Quantum Espresso and Themo_pw codes were utilized by employing the generalized gradient approximation. Although the results showed that both materials have good mechanical and thermal properties that are ideal for the above–mentioned applications, EuAlO3 possessed better structural and thermal stability, bulk modulus, Poisson ratio, thermal expansion coefficient, and thermal stress; while GdAlO3 possessed better Young’s modulus and shear modulus. Moreover, the mechanical properties of the two materials turned out to be much better than those of the common materials for optoelectronic applications, while their thermal properties were comparable to that of sapphire glass. Since this study was computational, an experimental verification of the computed properties of the two materials needs to be carried out before they can be commercialized.
Fleas (Insecta: Siphonaptera) of Peru: A Review of Their Diversity and the Host Specificity in the Country
Authors: Minaya David , Flores-Bancayan Carolina , Pellón Juan J. , Iannacone José , Lareschi Marcela
Published: December 2024

In the Neotropical biogeographic region, there are about 290 known species and subspecies of fleas, which have as their main hosts to the rodent subfamily Sigmodontinae. In Peru, more than 22 years have passed since the last list of known flea species was published. This study presents a review and update of the fleas recorded in Peru from 1908 to 2024. This list contains information on the flea species, including their known hosts, the localities in Peru where they were reported, the main references and some comments. In addition, the specificity of flea–host interactions was assessed using an interaction network approach. In the literature review, 86 flea species were found distributed among 9 families, 34 genera and 19 subspecies. These fleas were recorded parasitizing at least71 species of mammals and birds (14 orders, 28 families, 54 genera), 15 reported only at the genera level and seven undetermined ones. The flea–host interaction network exhibited a modular structure, indicating that these interactions tend to be specialized. A sigmodontine rodent (Akodon mollis) and a Rhopalopsyllidae flea (Polygenis litargus) were highly connected across modules and the overall network, and thus were important to maintain the structure. This review contributes to the knowledge of fleas in Peru, synthesizing the scattered information and providing information on the interaction they have with their hosts.
Diagnosis, Pathophysiology and Management of Microvascular Dysfunction in Diabetes Mellitus
Authors: Jan Yih-Kuen , Kelhofer Nicolas , Tu Tony , Mansuri Owaise , Onyemere Kingsley , Dave Shruti , Pappu Suguna
Published: December 2024

Microcirculation is an essential system that regulates oxygen and nutrients to cells and tissues in response to various environmental stimuli and pathophysiological conditions. Diabetes mellitus can cause microvascular complications including nephropathy, neuropathy, and retinopathy. The pathogenesis of microvascular dysfunction in diabetes is associated with hyperglycemia and the result of an interplay of various factors. Research studies have demonstrated that functional microvascular dysfunction appears much earlier than structural alterations in vasculature in diabetes. This finding of the progression from microvascular dysfunction to macrovascular disease establishes a foundation for the screening and early diagnosis of diabetes by assessing the microvascular function. This comprehensive review discusses technologies (laser Doppler, transcutaneous oximetry, infrared thermography and near-infrared spectroscopy) with computational methods (linear (time and frequency domains), nonlinear and machine learning approaches) for diagnosing microvascular dysfunction in diabetes. Pathophysiological changes of microvascular dysfunction leading to impaired vasomotion and blood flow oscillations in diabetes are reviewed. Recent findings in managing microvascular dysfunction using lifestyle modifications and force-based modulations are evaluated. A consensus endorsed by the American Diabetes Association has been reached that an effective exercise program would greatly slow down the progression of microvascular dysfunction and its impact on diabetic foot ulcers, muscle fatigue and weakness and peripheral neuropathy. However, it is imperative to determine the dose–response relationship of exercise and microvascular responses in patients with diabetes. Research studies have demonstrated that local vibration and whole-body vibration can improve microcirculation in various pathological conditions, including diabetes. Due to the complex nature of microvascular regulation, various computational methods have been developed to shed light on the influence of diabetes on microvascular dysfunction. This comprehensive review will contribute to the diagnosis and management of microvascular dysfunction in diabetes.
Optimization-Assisted Filter for Flow Angle Estimation of SUAV Without Adequate Measurement
Authors: Wang Ziyi , Li Jie , Liu Chang , Yang Yu , Li Juan , Wu Xueyong , Yang Yachao , Ye Bobo
Published: December 2024

The accurate estimation of flow angles is crucial for enhancing flight performance and aircraft safety. Flow angles of fixed-wing small unmanned aerial vehicles (SUAVs) are more vulnerable due to their low airspeed. Current flow angle measurement devices have not been widely implemented in SUAVs due to their substantial cost and size constraints. Moreover, there are no general estimation methods suitable for SUAVs based on their rudimentary sensor suite. This study presents a generalized optimization-assisted filter estimation (OAFE) method for estimating the relative velocity and flow angles of fixed-wing SUAVs based on a standard sensor suite. This OAFE method mainly consists of a cubature Kalman filter and an optimizer. The filter serves as the main loop with which to generate flow angles in real time by fusing the acceleration, angular rate, attitude, and airspeed. Without flow angle measurements, the optimizer generates approximate aerodynamic derivatives, which serve as pseudo-measurements with which to refine the performance of the filter. The results demonstrate that the estimated angle of attack and side slip angle displayed root mean square errors of around 0.11° and 0.24° in the simulation. The feasibility was also verified in field tests. The OAFE method does not require flow angle measurements, the prior acquisition of aerodynamic parameters, or model training, making it suitable for quick deployment on different SUAVs.
Thermodynamic Behavior of Doped Graphene: Impact of Heavy Dopant Atoms
Authors: Palma-Chilla L. , Lazzús Juan A.
Published: December 2024

This study investigates the effect of incorporating heavy dopant atoms on the topological transitions in the energy spectrum of graphene, as well as on its thermodynamic properties. A tight-binding model is employed that incorporates a lattice composition parameter associated with the dopant’s effect to obtain the electronic spectrum of graphene. Thus, the substitutional atoms in the lattice impact the electronic structure of graphene by altering the connectivity of the Dirac cones and the symmetry of the energy surface in their spectrum. The Gibbs entropy is numerically calculated from the energy surface of the electronic spectrum, and other thermodynamic properties, such as temperature, specific heat, and Helmholtz free energy, are derived from theoretical principles. The results show that topological changes induced by the heavy dopant atoms in the graphene lattice significantly affect its electronic structure and thermodynamic properties, leading to observable changes in the distances between Dirac cones, the range of the energy spectrum, entropy, positive and negative temperatures, divergences in specific heat, and instabilities within the system.
A Definition of a Heywood Case in Item Response Theory Based on Fisher Information
Authors: Verkuilen Jay , Johnson Peter J.
Published: December 2024

Heywood cases and other improper solutions occur frequently in latent variable models, e.g., factor analysis, item response theory, latent class analysis, multilevel models, or structural equation models, all of which are models with response variables taken from an exponential family. They have important consequences for scoring with the latent variable model and are indicative of issues in a model, such as poor identification or model misspecification. In the context of the 2PL and 3PL models in IRT, they are more frequently known as Guttman items and are identified by having a discrimination parameter that is deemed excessively large. Other IRT models, such as the newer asymmetric item response theory (AsymIRT) or polytomous IRT models often have parameters that are not easy to interpret directly, so scanning parameter estimates are not necessarily indicative of the presence of problematic values. The graphical examination of the IRF can be useful but is necessarily subjective and highly dependent on choices of graphical defaults. We propose using the derivatives of the IRF, item Fisher information functions, and our proposed Item Fraction of Total Information (IFTI) decomposition metric to bypass the parameters, allowing for the more concrete and consistent identification of Heywood cases. We illustrate the approach by using empirical examples by using AsymIRT and nominal response models.
Stochastic Model for a Piezoelectric Energy Harvester Driven by Broadband Vibrations
Authors: Sanfelice Angelo , Costanzo Luigi , Lo Schiavo Alessandro , Sarracino Alessandro , Vitelli Massimo
Published: December 2024

We present an experimental and numerical study of a piezoelectric energy harvester driven by broadband vibrations. This device can extract power from random fluctuations and can be described by a stochastic model, based on an underdamped Langevin equation with white noise, which mimics the dynamics of the piezoelectric material. A crucial point in the modelisation is represented by the appropriate description of the coupled load circuit that is necessary to harvest electrical energy. We consider a linear load (resistance) and a nonlinear load (diode bridge rectifier connected to the parallel of a capacitance and a load resistance), and focus on the characteristic curve of the extracted power as a function of the load resistance, in order to estimate the optimal values of the parameters that maximise the collected energy. In both cases, we find good agreement between the numerical simulations of the theoretical model and the results obtained in experiments. In particular, we observe a non-monotonic behaviour of the characteristic curve which signals the presence of an optimal value for the load resistance at which the extracted power is maximised. We also address a more theoretical issue, related to the inference of the non-equilibrium features of the system from data: we show that the analysis of high-order correlation functions of the relevant variables, when in the presence of nonlinearities, can represent a simple and effective tool to check the irreversible dynamics.
Federated Collaborative Learning with Sparse Gradients for Heterogeneous Data on Resource-Constrained Devices
Authors: Li Mengmeng , He Xin , Chen Jinhua
Published: December 2024

Federated learning enables devices to train models collaboratively while protecting data privacy. However, the computing power, memory, and communication capabilities of IoT devices are limited, making it difficult to train large-scale models on these devices. To train large models on resource-constrained devices, federated split learning allows for parallel training of multiple devices by dividing the model into different devices. However, under this framework, the client is heavily dependent on the server’s computing resources, and a large number of model parameters must be transmitted during communication, which leads to low training efficiency. In addition, due to the heterogeneous distribution among clients, it is difficult for the trained global model to apply to all clients. To address these challenges, this paper designs a sparse gradient collaborative federated learning model for heterogeneous data on resource-constrained devices. First, the sparse gradient strategy is designed by introducing the position Mask to reduce the traffic. To minimize accuracy loss, the dequantization strategy is applied to restore the original dense gradient tensor. Second, the influence of each client on the global model is measured by Euclidean distance, and based on this, the aggregation weight is assigned to each client, and an adaptive weight strategy is developed. Finally, the sparse gradient quantization method is combined with an adaptive weighting strategy, and a collaborative federated learning algorithm is designed for heterogeneous data distribution. Extensive experiments demonstrate that the proposed algorithm achieves high classification efficiency, effectively addressing the challenges posed by data heterogeneity.
Decoupling Algorithm for Online Identification of Inductance in Permanent Magnet Synchronous Motors Based on Virtual Axis Injection Method and Sensorless Control
Authors: Chen Kai , Xiao Long , Zhang Botao , Yang Mingjie , Yang Xianhua , Guo Xing
Published: December 2024

Among the existing sensorless control algorithms for permanent magnet synchronous motors (PMSMs), the model reference adaptive system (MRAS) is widely utilized due to its merits of good robustness, high stability, and rapid response. Nevertheless, the performance of the sensorless control is largely determined by the identified inductance parameters. The virtual-rotary-axis high-frequency injection (VHFSI) method is an online identification strategy for PMSM inductance parameters which is not affected by the observed rotor position errors among inductance identification algorithms. However, the existing PMSM inductance online identification algorithm based on VHFSI has ignored the influence of the error components, resulting in low accuracy and the weak dynamic performance of the inductance identification algorithm. In response to the problems existing in the original method, this paper improves VHFSI by designing a feedforward decoupling algorithm to compensate for the error components. Theoretical verification and simulation results indicate that the improved identification algorithm enhances the accuracy of inductance parameter identification, significantly improves the dynamic tracking performance of inductance identification, and combines it with the MRAS sensorless control method to constitute a sensorless control system for the motor, thereby enhancing control performance and system stability.
Driving Profile Optimization for Energy Management in the Formula Student Técnico Prototype
Authors: Pires Tomás R. , Fernandes João F. P. , Branco Paulo J. Costa
Published: December 2024

This study addresses the challenge of optimizing energy management in the electric vehicle industry, specifically focusing on motorsport. It particularly targets optimizing energy management during an endurance event at the Formula Student competition. The research involves detailed simulation of a complete endurance event, including developing precise track and vehicle models and their application in real-time energy management of our motorsport vehicle. The primary objective is to develop an energy reference profile that optimizes point scoring following the event’s specific rules. The energy reference profile serves as a strategic guideline for energy consumption and its regeneration throughout the endurance event. What sets this study apart is its emphasis on the real-time feedback controller’s implementation in the Formula Student prototype, FST12, specifically during the endurance event. This controller dynamically regulates the inverter’s power output, ensuring the vehicle closely follows the pre-established energy reference profile. This real-time energy management approach enhances overall performance by optimizing energy utilization for maximum scoring potential. The developed distance estimation method presented an error of less than 0.7% compared to experimental measurements. The Formula Student prototype, FST12, underwent experimental validation on a real 20 km closed-loop track. Results showed that the optimized strategy can be implemented with less than 0.5% of error in energy consumption and 6.8% of error in the obtained competing points.
Low-Frequency AC Multiport Asynchronous Grid Connection System to Optimize Generation Costs and Mitigate Bottlenecks
Authors: Park Jae-Deok , Oh Jeong-Sik , Kim Tae-Hun , An Byeong-Hyeon , Lee Seung-Yun , Park Tae-Sik
Published: December 2024

Renewable energy sources continue to increase due to the energy transition; thus, the generation output of conventional power sources is decreasing. The installation of renewable energy sources can lead to the concentration of these sources depending on geographical characteristics, which may cause bottlenecks between the renewable energy generation sites and load centers, and such bottlenecks can result in power shortages in load centers and may cause issues that limit the integration of renewable energy. Thus, this paper proposes the application of an LFAC multiport asynchronous grid connection system to solve these problems, where the frequency conversion device uses a variable frequency transformer (VFT). In addition, the installation location of the proposed LFAC multiport asynchronous grid connection system is selected using a grid partitioning technique, and the optimal power flow is performed to minimize the generation costs. The grid partitioning was conducted using the IEEE 39 bus system, and the feasibility of the proposed LFAC multiport asynchronous grid connection system was verified through simulation tests of the generation and load demands in the grid. In addition, the VFT control and optimal power flow control performances were confirmed through MATLAB/Simulink.
Induction Motors Under Voltage Unbalance Combined with Voltage Subharmonics
Authors: Gnaciński Piotr , Pepliński Marcin , Muc Adam , Hallmann Damian
Published: December 2024

In power systems, various power quality disturbances are present, including voltage deviation, voltage unbalance, and voltage waveform distortions. Voltage waveform distortions are usually identified with harmonics, but in some systems, subharmonics (subsynchronous interharmonics) and interharmonics may also occur—that is, components of frequency less than the fundamental frequency, or not an integer multiple of it. This study examines torque pulsations of an induction motor under voltage subharmonics combined with voltage unbalance. The motor and the driven DC generator vibrations were analysed under the power quality disturbances. Investigations were carried out using finite element and empirical methods. Experimental tests were performed for the maximal levels of the power quality disturbances specified or proposed in the relevant standards. For the investigated motor, under voltage subharmonics or voltage unbalance occurring as a single power quality disturbance, the vibration level was within the prescribed limit. However, under unbalance combined with subharmonics, the level could be accepted for only a limited time. Consequently, the permissible level of voltage subharmonics in non-generation installations should be interconnected with the voltage unbalance in the power system.
Early Prediction of Remaining Useful Life for Lithium-Ion Batteries with the State Space Model
Authors: Liang Yuqi , Zhao Shuai
Published: December 2024

In the realm of lithium-ion batteries (LIBs), issues like material aging and capacity decline contribute to performance degradation or potential safety hazards. Predicting remaining useful life (RUL) serves as a crucial method of assessing the health of batteries, thereby enhancing reliability and safety. To reduce the complexity and improve the accuracy and applicability of early RUL predictions for LIBs, we proposed a Mamba-based state space model for early RUL prediction. Due to the impacts of abnormal data, we first use the interquartile range (IQR) method with a sliding window for data cleansing. Subsequently, the top three highest correlated features are selected, and only the first 300 cycling data are used for training. The model has the ability to make forecasts using these few historical data. Extensive experiments are conducted using CALCE CS2 datasets. The MAE, RMSE, and RE are less than 0.015, 0.019, and 0.0261; meanwhile, R2 is higher than 0.99. Compared to the baseline approaches (CNN, BiLSTM, and CNN-BiLSTM), the average MAE, RMSE, and RE of the proposed approach are reduced by at least 29%, 21%, and 36%, respectively. According to the experimental results, the proposed approach performs better in terms of accuracy, robustness, and efficiency.