bluuebunny/crossref_metadata_2025 huggingface dataset:
Vapor‐Induced Assembly of a Platinum(II) Complex Loaded on Layered Double Hydroxide Nanoparticles
Authors: Morimoto Tamami , Yoshida Masaki , Sato‐Tomita Ayana , Nozawa Shunsuke , Takayama Junichi , Hiura Satoshi , Murayama Akihiro , Kobayashi Atsushi , Kato Masako
Published: August 2023

Controlled self‐assembly of PtII complexes is key to the development of optical and stimuli‐responsive materials, but designing and precisely controlling them is still difficult owing to weak intermolecular interactions. Herein, we report the successful water‐vapor‐induced assembly of an anionic PtII complex [Pt(CN)2(ppy)]− (Hppy=2‐phenylpyridine) electrostatically loaded onto cationically charged layered double hydroxide (LDH) nanoparticles consisting of Mg2+ and Al3+ ions. When the PtII complexes were densely loaded onto the LDH nanoparticles, the assembly was maintained, even in dilute aqueous media. In the case of sparse loading, the PtII complexes were loaded discretely in the dry state; however, when water vapor was adsorbed, the increased mobility of the PtII complexes led to their assembly on the LDH nanoparticles. The presence of water vapor led to a drastic change in luminescence from green to orange.
Giant breast phyllodes tumor with silent thromboembolism: A case report
Authors: Wang Qinbo , Wei Lina , Zhou Yuan , Ou Yingjuan , Li Haiyan
Published: August 2023

Background

Phyllodes tumor (PT) is a solid fibroepithelial breast lesion with proliferation of stromal and epithelial elements, usually presents with a rapidly expanding feature. Venous thromboembolism (VTE) have been reported to increase the burden in terms of mortality and morbidity of malignant tumor, and associate with worsened survival. However, benign PTs with silent thromboembolism that have not yet been reported, we report an unusual case of massive benign PT that grew on the left side of the breast in a cauliflower‐shaped form and presented severe chronic blood loss and deep VTE.

Case

A 37‐year‐old woman with uncontrolled pain presented a rapidly enlarging left breast mass, measuring approximately 30 × 20 × 15 cm3 that first started 25 years ago. color Doppler ultrasound showed a large mass lesion on the left breast and deep VTE, several enlarged lymph nodes in the left axilla and mediastinum, which presented a malignant character. However, the biopsies of the mass did not show evidence of malignancy and the pathology result was considered to be benign PT. The patient was treated with an inferior vena cava and anticoagulation, the operation was arranged according to the surgical procedure, the patient recovered very well after mastectomy.

Conclusion

This case is unique in that the giant breast mass presented with malignant character, was eventually pathologically confirmed to be benign PT, and it's rare that the benign tumor accompanied with silent thromboembolism. This finding describes the atypia features of giant benign PT and reminds the surgeon to consider the factor of VTE and risk when encountering ulcerative benign breast tumor and avoid excessive treatment.
Does corporate social responsibility mediate the relationship between corporate governance and firm performance? Empirical evidence from BRICS countries
Authors: Akhter Waseem , Hassan Arshad
Published: August 2023

This study analyzes how corporate governance affects financial performance and explores the role of corporate social responsibility as a mediator for 495 firms located in emerging economies in BRICS countries, including Brazil, Russia, India, China, and South Africa from 2011 to 2021. This study evaluates the impact of various board characteristics such as board size, board independence, and gender diversity, as well as ownership structure elements such as family, foreign, and institutional shareholding, on firm performance in BRICS countries. This study uses a generalized method of moments (GMM) methodology to examine the relationship between corporate governance, corporate social responsibility (CSR), and firm performance. The results reveal that board attributes including size, independence, and gender diversity positively influence firm performance. All three components of ownership structure, family, foreign, and institutional shareholdings, positively affect firm performance. CSR partially mediates the positive relationship between corporate governance and firm performance. This study contributes to the literature by adding CSR as a mediating variable in the relationship between corporate governance and firm performance in BRICS countries. These findings suggest that managers must understand that effective corporate governance mechanisms are essential for better performance and should align their interests with firms' objectives. The mediation effect of CSR implies that policymakers should consider CSR as an additive tool to enhance firm performance rather than as an additional expenditure.
DC‐link voltage control of small capacitor PMSM drive system based on MPC algorithm
Authors: Song Jian , Song Wenxiang , Lin Hongmin
Published: August 2023

The permanent magnet synchronous motor (PMSM) drive system with small dc‐link capacitor will have the problem of unstable drive system due to the small damping of the LC filter and the negative impedance characteristics of the constant power load. The input LC filter can suppress interference and is essential for the normal operation of the drive, but it may not match the impedance of the post‐stage inverter, causing the drive system to become unstable. In this paper, by constructing the dc‐link voltage prediction model, combined with the PMSM current predictive control, the weighted cost function of the model predictive control (MPC) strategy is designed to realize the motor optimal control and the dc‐link voltage fluctuation suppression control. To avoid introducing additional sensors when constructing the dc‐link voltage model, a source state observer that can estimate the dc‐link voltage and input current is constructed. Simulation and experimental results are provided to verify the effectiveness of the proposed method.
Model predictive and SoC balancing control of a CHB inverter in battery energy storage application using reward functions
Authors: Zhao Yongtian , Wang Xiaogang , Hu Wei , Yang Ru , Zou Tao
Published: August 2023

This article presents an improved model predictive current control algorithm combined with a novel state of charge (SoC) balancing approach for a three‐phase cascaded H‐bridge inverter in battery energy storage applications. Based on the model predictive control with elimination of redundant voltage vectors, neighboring vectors of the last voltage vectors are used to find the optimal ones in only one control cycle, which solves the problems of high computational burden and slow dynamic response. To overcome the unsuitability of the conventional cost function in SoC balancing, the reward functions that effectively balance the inter‐phase SoCs, inner‐phase SoCs, and inner‐phase dc voltages are presented respectively. Simulation and hardware‐in‐the‐loop‐based experimental results validate the effectiveness of the proposed strategy.
A high‐speed and low‐latency hardware implementation of RC4 cryptographic algorithm
Authors: Sun Caiban , Liu Wenrui , Cheng Jiafeng , Sun Nengyuan , Peng Zhaokang , Sha Heng , Yu Weize
Published: August 2023

In this letter, a high‐speed and low‐latency Ron Rivest‐4 (RC4) encryption algorithm is designed based on SMIC 14 nm process. Since the key issue of limiting the throughput of RC4 encryption algorithm is the swapping operation of S‐box, this proposed design is capable of achieving four swapping operations of S‐box within a clock cycle by utilizing fully combinational logic designs and advanced computations. All 256 swapping operations of key scheduling algorithm (KSA) can be done in 64 clock cycles. Moreover, the novel design greatly improves the encryption efficiency of RC4 since each clock cycle offers 4 bytes of key stream. The whole area can be further optimized by reusing the existing modules, and a lightweight countermeasure is embedded into the RC4 design to break the correlation between the processed data and power dissipation against differential power analysis (DPA) attacks. Finally, the whole design is assessed by the SMIC 14 nm process design kits (PDK). The corresponding clock frequency, throughput, area, and latency, respectively, are achieved as 1 GHz, 32 Gbps, 51,596  m2, and 74 clock cycles.
Elemental composition and material properties of radular teeth in the heterobranch snail Gastropteron rubrum (Mollusca, Gastropoda, Cephalaspidea) foraging on hard organisms
Authors: Krings Wencke , Neumann Charlotte , Gorb Stanislav N. , Koehnsen Alexander , Wägele Heike
Published: August 2023

The molluscan feeding structure is the radula, a chitinous membrane with teeth, which are highly adapted to the food and the substrate to which the food is attached. In Polyplacophora and Patellogastropoda, the handling of hard ingesta can be facilitated by high content of chemical compounds containing Fe or Si in the tooth cusps. Other taxa, however, possess teeth that are less mineralized, even though animals have to avoid structural failure or high wear during feeding as well. Here, we investigated the gastropod Gastropteron rubrum, feeding on hard Foraminifera, diatoms and Porifera. Tooth morphologies and wear were documented by scanning electron microscopy and their mechanical properties were tested by nanoindentation. We determined that gradients of hard‐ and stiffness run along each tooth, decreasing from cusp to basis. We also found that inner lateral teeth were harder and stiffer than the outer ones. These findings allowed us to propose hypotheses about the radula‐ingesta interaction. In search for the origins of the gradients, teeth were visualized using confocal laser scanning microscopy, to determine the degree of tanning, and analyzed with energy‐dispersive X‐ray spectroscopy, to test the elemental composition. We found that the mechanical gradients did not have their origins in the elemental content, as the teeth did not contain high proportions of metals or other minerals. This indicates that their origin might be the degree of tanning. However, in the tooth surfaces that interact with the ingesta high Si and Ca contents were determined, which is likely an adaptation to reduce wear.
An elevational shift facilitated the Mesoamerican diversification of Azure‐hooded Jays (Cyanolyca cucullata) during the Great American Biotic Interchange
Authors: McCormack John E. , Hill Molly M. , DeRaad Devon A. , Kirsch Eliza J. , Reckling Kelsey R. , Mutchler Marquette J. , Ramirez Brenda R. , Campbell Russell M. L. , Salter Jessie F. , Pizarro Alana K. , Tsai Whitney L. E. , Bonaccorso Elisa
Published: August 2023

The Great American Biotic Interchange (GABI) was a key biogeographic event in the history of the Americas. The rising of the Panamanian land bridge ended the isolation of South America and ushered in a period of dispersal, mass extinction, and new community assemblages, which sparked competition, adaptation, and speciation. Diversification across many bird groups, and the elevational zonation of others, ties back to events triggered by the GABI. But the exact timing of these events is still being revealed, with recent studies suggesting a much earlier time window for faunal exchange, perhaps as early as 20 million years ago (Mya). Using a time‐calibrated phylogenetic tree, we show that the jay genus Cyanolyca is emblematic of bird dispersal trends, with an early, pre‐land bridge dispersal from Mesoamerica to South America 6.3–7.3 Mya, followed by a back‐colonization of C. cucullata to Mesoamerica 2.3–4.8 Mya, likely after the land bridge was complete. As Cyanolyca species came into contact in Mesoamerica, they avoided competition due to a prior shift to lower elevation in the ancestor of C. cucullata. This shift allowed C. cucullata to integrate itself into the Mesoamerican highland avifauna, which our time‐calibrated phylogeny suggests was already populated by higher‐elevation, congeneric dwarf‐jays (C. argentigula, C. pumilo, C. mirabilis, and C. nanus). The outcome of these events and fortuitous elevational zonation was that C. cucullata could continue colonizing new highland areas farther north during the Pleistocene. Resultingly, four C. cucullata lineages became isolated in allopatric, highland regions from Panama to Mexico, diverging in genetics, morphology, plumage, and vocalizations. At least two of these lineages are best described as species (C. mitrata and C. cucullata). Continued study will further document the influence of the GABI and help clarify how dispersal and vicariance shaped modern‐day species assemblages in the Americas.
Trapping an Unexpected/Unprecedented Hexanuclear Ce(III) Hydrolysis Product with Neutral 4‐Amino‐1,2,4‐triazole
Authors: Wineinger Hannah , Smetana Volodymyr , Hiti Ethan , Baryshnikov Glib , Qu Fengrui , Ågren Hans , Mudring Anja‐Verena , Rogers Robin D.
Published: August 2023

Using Ce(III) as both a representative lanthanide and actinide analog, the ability of mixtures of acidic and basic azoles to allow direct access to homoleptic N‐donor f‐element complexes in one pot reactions from hydrated salts as starting materials was examined by reacting mixtures of 4‐amino‐1,2,4‐triazole (4‐NH2‐1,2,4‐Triaz), 5‐amino‐tetrazole (5‐NH2‐HTetaz), and 1,2,3‐triazole (1,2,3‐HTriaz) in 1 : 1 and 1 : 3 ratios with CeCl3 ⋅ 7H2O, [C2mim]3[CeCl6] ([C2mim]+=1‐ethyl‐2‐methylimidazolium), and Ce(NO3)3 ⋅ 6H2O. Although unsuccessful in our goal, structural analysis revealed that neutral 4‐NH2‐1,2,4‐Triaz is structure directing via η2μ2κ2 bridging, with the formation of the dinuclear complexes [Ce2Cl2(μ2‐4‐NH2‐1,2,4‐Triaz)4(H2O)8]Cl4 ⋅ 4H2O, [Ce2(μ2‐4‐NH2‐1,2,4‐Triaz)4(4‐NH2‐1,2,4‐Triaz)2(Cl)6], and [4‐NH2‐1,2,4‐HTriaz][Ce2(μ2‐4‐NH2‐1,2,4‐Triaz)2(μ2‐NO3)(NO3)6(H2O)2]. When the synthetic conditions favored hydrolysis, the hexanuclear Ce(III) complex [Ce6(μ3‐O)4(μ3‐OH)2(μ3‐Cl)2(Cl)6(μ2‐4‐NH2‐1,2,4‐Triaz)12] ⋅ 7H2O was isolated. This unexpected hydrolysis product represents the first example of a high nuclearity lanthanide complex where all Ln atoms are pairwise connected through 12 N‐donor ligands or 12 neutral bridging ligands of any type, a rare example of incorporation of non‐oxo coordinating anions in the M6X8 core, and the first reported Ce(III) hexanuclear complex of this type.
Elucidating the impacts of trees on landslide initiation throughout a typhoon: Preferential infiltration, wind load and root reinforcement
Authors: Zhuang Yu , Xing Aiguo , Petley Dave , Jiang Yuehua , Sun Qiang , Bilal Muhammad , Yan Jinkai
Published: August 2023

Typhoon‐induced landslides are widespread, damaging and deadly. In this study, we elucidated their spatiotemporal features through investigations in Southeast coastal China and proposed a numerical model that involves typhoon wind load, preferential infiltration and root reinforcement. The wind load is calculated through a combination of the autoregressive method and a multi‐degree‐of‐freedom tree swaying mode, transmitting to the slope through the wind–tree interaction. Taproots of trees are modelled as piles, and root–soil interfaces are modelled as preferential infiltration boundaries. Using the numerical model, we quantitatively assessed the impacts of wind load, rainfall infiltration and root reinforcement on the slope stability and compared results with cases in Waipaoa and Wairoa (New Zealand). Results suggest that the impacts of trees depend heavily on meteorological and geological conditions. Trees play a destabilizing role in Southeast China during a typhoon but a stabilizing role in the cases in New Zealand. For slopes in Southeast China with a thick soil layer (>root depth), strong wind load and preferential flow resulting from root–soil interfaces, rather than slope surface infiltration, significantly decrease the slope stability in a short time. Slope failure occurred in all scenarios that account for the preferential infiltration, and its combination with a Force 14 typhoon wind load can fail the slope at 10 h after the typhoon initiation. Differently, tree roots in cases in New Zealand can penetrate through the thin soil layer (<1 m) and provide considerable additional resistance to stabilize the slope.
Biomechanical Stimulation of Muscle Constructs Influences Phenotype of Bone Constructs by Modulating Myokine Secretion
Authors: Suresh Kumar Harshini , Barnett Edwina N. , Fowlkes John L. , Kalaitzoglou Evangelia , Annamalai Ramkumar T.
Published: August 2023

Diabetes is a chronic metabolic disorder that can lead to diabetic myopathy and bone diseases. The etiology of musculoskeletal complications in such metabolic disorders and the interplay between the muscular and osseous systems are not well understood. Exercise training promises to prevent diabetic myopathy and bone disease and offer protection. Although the muscle‐bone interaction is largely biomechanical, the muscle secretome has significant implications for bone biology. Uncoupling effects of biophysical and biochemical stimuli on the adaptive response of bone during exercise training may offer therapeutic targets for diabetic bone disease. Here, we have developed an in vitro model to elucidate the effects of mechanical strain on myokine secretion and its impact on bone metabolism decoupled from physical stimuli. We developed bone constructs using cross‐linked gelatin, which facilitated osteogenic differentiation of osteoprogenitor cells. Then muscle constructs were made from fibrin, which enabled myoblast differentiation and myotube formation. We investigated the myokine expression by muscle constructs under strain regimens replicating endurance (END) and high‐intensity interval training (HIIT) in hyperglycemic conditions. In monocultures, both regimens induced higher expression of Il15 and Igf1, whereas END supported more myoblast differentiation and myotube maturation than HIIT. When co‐cultured with bone constructs, HIIT regimen increased Glut4 expression in muscle constructs more than END, supporting higher glucose uptake. Likewise, the muscle constructs under the HIIT regimen promoted a healthier and more matured bone phenotype than END. Under static conditions, myostatin (Mstn) expression was significantly downregulated in muscle constructs co‐cultured with bone constructs compared with monocultures. Together, our in vitro co‐culture system allowed orthogonal manipulation of mechanical strain on muscle constructs while facilitating bone‐muscle biochemical cross‐talk. Such systems can provide an individualized microenvironment that allows decoupled biomechanical manipulation, help identify molecular targets, and develop engineered therapies for metabolic bone disease. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.
Identifying vulnerability to human trafficking in Bangladesh: An ecosystem approach using weak‐signal analysis
Authors: van der Vink Gregory E. , Carlson Katherine N. , Phillips Erica , Szeto Sabrina H. , Park Jeffrey , Jackson Michael E.
Published: August 2023

We present an ecosystem approach to analyze open‐source data to identify populations vulnerable to human trafficking and to reveal underlying causal relationships. In the case of Bangladesh, our analysis suggests combinations of indicators that are highly predictive of human trafficking. The traditional narrative that poverty and unemployment are the main drivers for human trafficking may be an oversimplification. We find many areas where vulnerability is highest within lower‐middle to middle‐class societies with (a) moderate levels of income and education, (b) adherence to traditional gender norms of a male‐dominated patriarchal society, and (c) access to an urban center.
Deep learning‐based detection and classification of lumbar disc herniation on magnetic resonance images
Authors: Zhang Weicong , Chen Ziyang , Su Zhihai , Wang Zhengyan , Hai Jinjin , Huang Chengjie , Wang Yuhan , Yan Bin , Lu Hai
Published: August 2023

Background

The severity assessment of lumbar disc herniation (LDH) on MR images is crucial for selecting suitable surgical candidates. However, the interpretation of MR images is time‐consuming and requires repetitive work. This study aims to develop and evaluate a deep learning‐based diagnostic model for automated LDH detection and classification on lumbar axial T2‐weighted MR images.

Methods

A total of 1115 patients were analyzed in this retrospective study; both a development dataset (1015 patients, 15 249 images) and an external test dataset (100 patients, 1273 images) were utilized. According to the Michigan State University (MSU) classification criterion, experts labeled all images with consensus, and the final labeled results were regarded as the reference standard. The automated diagnostic model comprised Faster R‐CNN and ResNeXt101 as the detection and classification network, respectively. The deep learning‐based diagnostic performance was evaluated by calculating mean intersection over union (IoU), accuracy, precision, sensitivity, specificity, F1 score, the area under the receiver operating characteristics curve (AUC), and intraclass correlation coefficient (ICC) with 95% confidence intervals (CIs).

Results

High detection consistency was obtained in the internal test dataset (mean IoU = 0.82, precision = 98.4%, sensitivity = 99.4%) and external test dataset (mean IoU = 0.70, precision = 96.3%, sensitivity = 97.8%). Overall accuracy for LDH classification was 87.70% (95% CI: 86.59%–88.86%) and 74.23% (95% CI: 71.83%–76.75%) in the internal and external test datasets, respectively. For internal testing, the proposed model achieved a high agreement in classification (ICC = 0.87, 95% CI: 0.86–0.88, P < 0.001), which was higher than that of external testing (ICC = 0.79, 95% CI: 0.76–0.81, P < 0.001). The AUC for model classification was 0.965 (95% CI: 0.962–0.968) and 0.916 (95% CI: 0.908–0.925) in the internal and external test datasets, respectively.

Conclusions

The automated diagnostic model achieved high performance in detecting and classifying LDH and exhibited considerable consistency with experts' classification.
Is reinfection negligible effect in COVID‐19? A mathematical study on the effects of reinfection in COVID‐19
Authors: Tamilalagan P. , Krithika B. , Manivannan P. , Karthiga S.
Published: August 2023

Serological studies show that besides the development of suitable antibodies that are evidenced in people who get infected with SARS‐CoV2 or in people who are vaccinated, the possibility of getting reinfected with SARS‐CoV2 remains non‐zero (may be finite). The present article studies how far this possibility of reinfection impacts the transmission dynamics of COVID‐19. Considering a six compartment mathematical model, we have studied the transmission dynamics of the disease and presented the situations that will lead to endemic‐free (also endemic) state. Considering the COVID‐19 waves in India during the spread of SARS‐CoV‐2, delta variant of SARS‐CoV‐2, and Omicron variant, the parameters of the model are estimated corresponding to these three situations. As expected, the obtained parameters lie in the stable region of endemic state. The changes in dynamics of the system with the reinfection is studied, and it shows that its effects are not neglible. Even finite value of reinfection can significantly vary the number of infected individuals, and it could explain secondary (smaller) rise in the COVID‐19 cases after the COVID‐19 wave. We also study the dynamics of the system through fractional order differential equations.
Computational pathology in cancer diagnosis, prognosis, and prediction – present day and prospects
Authors: Verghese Gregory , Lennerz Jochen K , Ruta Danny , Ng Wen , Thavaraj Selvam , Siziopikou Kalliopi P , Naidoo Threnesan , Rane Swapnil , Salgado Roberto , Pinder Sarah E , Grigoriadis Anita
Published: August 2023

Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging from the prospect of automation of routine diagnostic tasks to the discovery of new prognostic and predictive biomarkers from tissue morphology. Despite the promising potential of computational pathology, its integration in clinical settings has been limited by a range of obstacles including operational, technical, regulatory, ethical, financial, and cultural challenges. Here, we focus on the pathologists’ perspective of computational pathology: we map its current translational research landscape, evaluate its clinical utility, and address the more common challenges slowing clinical adoption and implementation. We conclude by describing contemporary approaches to drive forward these techniques. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Post‐operative flank irradiation using conformal versus highly conformal radiotherapy techniques for paediatric renal tumours: Results from the French registry PediaRT
Authors: Le Quellenec Gaelle , Bernier‐Chastagner Valerie , Sellami Noura , Helfre Sylvie , Satragno Camilla , Leseur Julie , Escande Alexandre , Jolnerovski Maria , Noel Georges , Missohou Fernand , Claude Line , Cantaloube Marie , Laprie Anne , Huchet Aymeri , Scouarnec Cyrielle , Guimard Gregory , Muracciole Xavier , Paul Julie , Supiot Stéphane , Jouglar Emmanuel ,   the Groupe Français de Radiothérapie Pédiatrique
Published: August 2023

Purpose

Three‐dimensional conformal RT (3D‐RT) techniques are gold standard for post‐operative flank radiotherapy (RT) in paediatric renal tumours. Recently, highly conformal RT (HC‐RT) techniques have been implemented without comparative clinical data. The main objective of this multicentre study was to compare locoregional control (LRC) in children treated either with HC‐RT or 3D‐RT techniques.

Methods

Patients treated with post‐operative flank RT for renal tumour registered in the national cohort PediaRT between March 2013 and September 2019 were included. Treatment and follow‐up data, including toxicities and outcomes, were retrieved from the database. LRC was calculated, and dose reconstruction was performed in case of an event.

Results

Seventy‐nine patients were included. Forty patients were treated with HC‐RT and 39 with 3D‐RT. Median follow‐up was 4.5 years. Three patients had locoregional failure (LRF; 4%). HC‐RT was not associated with a higher risk of LRF. Three‐year LRC were 97.4% and 94.7% in the HC‐RT and 3D‐RT groups, respectively. The proportion of planning target volumes receiving 95% or more of the prescribed dose did not significantly differ between both groups (HC‐RT 88%; 3D‐RT 69%; p = .05). HC‐RT was better achieving dose constraints, and a significant mean dose reduction was observed in the peritoneal cavity and pancreas associated with lower incidence of acute gastrointestinal toxicity.

Conclusion

LRF after post‐operative flank RT for renal tumours was rare and did not increase using HC‐RT versus 3D‐RT techniques. Dose to the pancreas and the peritoneal cavity, as well as acute toxicity, were reduced with HC‐RT compared to 3D‐RT.
Tyrosine kinase inhibitor therapy in pediatric sarcoma: Prognostic implications of pulmonary metastatic cavitation
Authors: Morakote Wipawee , Adams Lisa C. , Ramasamy Shakthi K. , Spunt Sheri L. , Baratto Lucia , Liang Tie , Daldrup‐Link Heike E.
Published: August 2023

Purposes

This study aims to ascertain the prevalence of cavitations in pulmonary metastases among pediatric and young adult patients with sarcoma undergoing tyrosine kinase inhibitor (TKI) therapy, and assess whether cavitation can predict clinical response and survival outcomes.

Methods

In a single‐center retrospective analysis, we examined chest computed tomography (CT) scans of 17 patients (median age 16 years; age range: 4–25 years) with histopathologically confirmed bone (n = 10) or soft tissue (n = 7) sarcoma who underwent TKI treatment for lung metastases. The interval between TKI initiation and the onset of lung nodule cavitation and tumor regrowth were assessed. The combination of all imaging studies and clinical data served as the reference standard for clinical responses. Progression‐free survival (PFS) was compared between patients with cavitating and solid nodules using Kaplan–Meier survival analysis and log‐rank test.

Results

Five out of 17 patients (29%) exhibited cavitation of pulmonary nodules during TKI therapy. The median time from TKI initiation to the first observed cavitation was 79 days (range: 46–261 days). At the time of cavitation, all patients demonstrated stable disease. When the cavities began to fill with solid tumor, 60% (3/5) of patients exhibited progression in other pulmonary nodules. The median PFS for patients with cavitated pulmonary nodules after TKI treatment (6.7 months) was significantly longer compared to patients without cavitated nodules (3.8 months; log‐rank p‐value = .03).

Conclusions

Cavitation of metastatic pulmonary nodules in sarcoma patients undergoing TKI treatment is indicative of non‐progressive disease, and significantly correlates with PFS.
Identification of risk factors for adverse drug reactions in a pharmacovigilance database
Authors: Attelind Sofia , Eriksson Niclas , Sundström Anders , Wadelius Mia , Hallberg Pär
Published: August 2023

Introduction

In addition to identifying new safety signals, pharmacovigilance databases could be used to identify potential risk factors for adverse drug reactions (ADRs).

Objective

To evaluate whether data mining in a pharmacovigilance database can be used to identify known and possible novel risk factors for ADRs, for use in pharmacovigilance practice.

Method

Exploratory data mining was performed within the Swedish national database of spontaneously reported ADRs. Bleeding associated with direct oral anticoagulants (DOACs)‐rivaroxaban, apixaban, edoxaban, and dabigatran‐was used as a test model. We compared demographics, drug treatment, and clinical features between cases with bleeding (N = 965) and controls who had experienced other serious ADRs to DOACs (N = 511). Statistical analysis was performed by unadjusted and age adjusted logistic regression models, and the random forest based machine‐learning method Boruta.

Results

In the logistic regression, 13 factors were significantly more common among cases of bleeding compared with controls. Eleven were labelled or previously proposed risk factors. Cardiac arrhythmia (e.g., atrial fibrillation), hypertension, mental impairment disorders (e.g., dementia), renal and urinary tract procedures, gastrointestinal ulceration and perforation, and interacting drugs remained significant after adjustment for age. In the Boruta analysis, high age, arrhythmia, hypertension, cardiac failure, thromboembolism, and pharmacodynamically interacting drugs had a larger than random association with the outcome. High age, cardiac arrhythmia, hypertension, cardiac failure, and pharmacodynamically interacting drugs had odds ratios for bleeding above one, while thromboembolism had an odds ratio below one.

Conclusions

We demonstrated that data mining within a pharmacovigilance database identifies known risk factors for DOAC bleeding, and potential risk factors such as dementia and atrial fibrillation. We propose that the method could be used in pharmacovigilance for identification of potential ADR risk factors that merit further evaluation.
Designed novel nuclear localizing anticancer peptide targets p53 negative regulator MDM2 protein
Authors: Mukherjee Nabanita , Bhunia Debmalya , Garai Prabir Kumar , Mondal Prasenjit , Barman Surajit , Ghosh Surajit
Published: August 2023

Intracellular protein–protein interactions provide a major therapeutic target for the development of peptide‐based anticancer therapeutic agents. MDM2 is the 491‐residue protein encoded by the MDM2 oncogene. Being a ubiquitin‐protein ligase, MDM2 represses the transcription ability of the tumor suppressor p53 by proteasome‐mediated degradation. Under typical cellular circumstances, a sustained p53 expression level is maintained by negative regulation of MDM2, whereas under stress conditions, this is alleviated to increase the p53 level. Modulation of MDM2‐p53 interaction via fabrication of an MDM2‐interacting peptide could be a useful strategy to inhibit subsequent proteasomal degradation of p53 and initiation of p53 signaling leading to the initiation of p53‐mediated apoptosis of tumor cells. Here, in this research work, a novel anticancer peptide mPNC‐NLS targeting the nucleus and the MDM2 protein (p53 negative regulator) was designed to promote the p53 protein activity for the prevention of cancer. It induces effective apoptosis in both A549 and U87 cells and remains non‐cytotoxic to normal lung fibroblast cells (WI38). Further, immunocytochemistry and Western blot results confirm that the designed mPNC‐NLS peptide induces the apoptotic death of lung cancer cells via activation of p53 and p21 proteins and remarkably stifled the in vitro growth of 3D multicellular spheroids composed of A549 cells.
Proximity labeling and identification of endogenous client proteins recruited to Y15‐based artificial granules tethering a bait protein
Authors: Hashimoto Masahiro , Miki Takayuki , Niwa Tatsuya , Mihara Hisakazu
Published: August 2023

Protein clustering is a ubiquitous event in diverse cellular processes. Self‐association of proteins triggers recruitment of downstream proteins to regulate cellular signaling. To investigate the interactions in detail, chemical biology tools to identify proteins recruited to defined assemblies are required. Here, we exploit an identification of proteins recruited in artificial granules (IPRAG) platform that combines intracellular Y15‐based supramolecule construction with a proximity labeling method. We validated the IPRAG tool using Nck1 as a target bait protein. We constructed Nck1‐tethering granules, labeled the recruited proteins with biotin, and analyzed them by LC‐MS/MS. As a result, we successfully identified proteins that directly or indirectly interact with Nck1.
Prevalence of thyroid dysfunction during first trimester of pregnancy: A descriptive cross‐sectional study
Authors: Sharma Sandip K. , Gurung Geeta , Katuwal Neeta , Joshi Padam R. , Chaurasia Hemu , Lamsal Sunita
Published: August 2023

Objectives

Thyroid dysfunction carries large burden during pregnancy and untreated thyroid dysfunction is associated with poor maternal and foetal outcome. The exact burden of thyroid dysfunction during pregnancy in Nepal is not well established. This is descriptive cross‐sectional study done in tertiary care centre of Nepal to know burden of thyroid dysfunction and establish possible need of universal thyroid function screening during pregnancy.

Methods

A descriptive cross‐sectional study was conducted from 4 September 2020 to 3 September 2021 on pregnant women attending to ANC clinic during their first trimester after obtaining ethical approval. Among eligible patients, after taking informed consent, a total of 385 pregnant women were included in the study. Thyroid function status was assessed by measuring serum levels of thyroid stimulating hormone (TSH), free thyroxine (FT4), and free tri‐iodothyronine (FT3). Women with pre‐existing thyroid disorders were excluded. Serum thyroid function was used to detect thyroid disorder based on American Thyroid Association 2011 criteria. A convenience sampling method was used. Point estimate and 95% confidence interval (CI) were calculated.

Results

Among 385 pregnant women, 152 (39.48%) (39.20–39.70, 95% CI) had thyroid disorders. Among thyroid disorders (n = 152), 111 (28.83%) had subclinical hypothyroidism, 37 (9.61%) overt hypothyroidism, 3 (0.78%) subclinical hyperthyroidism and 1 (0.26%) had overt hyperthyroidism.

Conclusion

Around four in every 10 pregnant women had thyroid disorder. Thyroid dysfunction is easily detectable and can be effectively, inexpensively treated, which can prevent adverse maternal and foetal outcome. Thus, we should consider universal screening of pregnant women for thyroid disorder especially in a country like Nepal where there is a high prevalence of undiagnosed thyroid disorder.
On the sample complexity of observers for unknown linear systems with biased dynamics estimations
Authors: Ding Xuda , Wang Han , He Jianping , Chen Cailian , Guan Xinping
Published: August 2023

Observers have broad applications in power systems, whereas observer models are hard to obtain when the system is unknown. This article considers the observer design problems for unknown noisy linear time‐invariant systems based on biased dynamics estimations. Unlike the unbiased methods, biased methods have stronger generalization ability, which benefits obtaining stable estimations for noisy systems. However, the biased estimation's influence on observer design still needs to be investigated. To analyze the influence, we exploit the impact of estimation bias‐variance trade‐off to observer design. Specifically, we propose a support vector regression (SVR) based estimator to provide biased estimations for the system identification of unknown linear systems. The sample complexity results of SVR with bias‐variance trade‐offs are analyzed and used for observer design and performance analysis. Then, a stable observer gain design algorithm is developed based on biased estimation. The observation performance is evaluated by the mean square observation error, which is shown to be adjustable by tuning the trade‐off between bias and variance, thus achieving higher scalability than the unbiased methods. Finally, observing performance analysis demonstrates the influence of the bias‐variance trade‐off for the observer. Extensive simulation validations are conducted to verify the computed estimation error and performance optimality with different bias‐variance trade‐offs and noise settings.
Practical trajectory tracking of output constrained random nonlinear systems
Authors: Yin Ruijie , Wu Zhaojing
Published: August 2023

This article studies practical trajectory tracking of output constrained multi‐input and multi‐output random nonlinear systems. First, the definition of ultimately bounded in the mean square and its Lyapunov criterion are given. Then, by proposing barrier Lyapunov function into the backstepping control design, constraint can be tackled and kept in the given region. Stability analysis is performed to the closed‐loop error system and practical trajectory tracking is achieved, meanwhile the second‐order moment of tracking error can be made arbitrarily small. A simulation example of a mechanical arm demonstrates the effectiveness of this control scheme.
Evaluation of multi‐user multiple‐input multiple‐output digital beamforming algorithms in B5G/6G low Earth orbit satellite systems
Authors: Dakkak M. Rabih , Riviello Daniel Gaetano , Guidotti Alessandro , Vanelli‐Coralli Alessandro
Published: August 2023

Satellite communication systems will be a key component of 5G and 6G networks to achieve the goal of providing unlimited and ubiquitous communications and deploying smart and sustainable networks. To meet the ever‐increasing demand for higher throughput in 5G and beyond, aggressive frequency reuse schemes (i.e., full frequency reuse), combined with digital beamforming techniques to cope with the massive co‐channel interference, are recognized as a key solution. Aimed at (i) eliminating the joint optimization problem among the beamforming vectors of all users, (ii) splitting it into distinct ones, and (iii) finding a closed‐form solution, we propose a beamforming algorithm based on maximizing the users' signal‐to‐leakage‐and‐noise ratio served by a low Earth orbit satellite. We investigate and assess the performance of several beamforming algorithms, including both those based on channel state information at the transmitter, that is, minimum mean square error and zero forcing, and those only requiring the users' locations, that is, switchable multi‐beam. Through a detailed numerical analysis, we provide a thorough comparison of the performance in terms of per‐user achievable spectral efficiency of the aforementioned beamforming schemes, and we show that the proposed signal to‐leakage‐plus‐noise ratio beamforming technique is able to outperform both minimum mean square error and multi‐beam schemes in the presented satellite communication scenario.
Measuring sustainable ergonomics: A hybrid multi‐criteria perspective on ergonomics indicators
Authors: Sarbat Irem , Ozmehmet Tasan Seren
Published: August 2023

Decision making process comprises complexity due to holistically managed requirements. Since this process has diverse effects on stakeholders as decision makers, undoubtedly, the decisions become more significant for organizations having critical decisions in today's globalized sustainable world. If these decisions influence not only providing human well‐being but also improving the quality of working life through measuring the performance of business processes, their results should be monitored more systematically. Through this viewpoint, in this paper, the applicability of ergonomics indicators, as the fundamental part of a systematic approach integrating ergonomics and sustainability to monitor and evaluate processes of organizations, is queried within a hybrid multi‐criteria perspective, including five evaluation criteria consolidated for this paper, through a designed survey by asking practitioners as potential users of such an approach. The used methods, that is, BWM and PROMETHEE, enable presenting a base study to decide which ergonomics indicators are necessary for developing a systematic approach, indicating the prioritization of these indicators to be used as candidates for the approach. Results show that 15 ergonomics indicators can be candidates for facilitating sustainable process performance measurement in ergonomics. Importantly, this paper proposes guidance in making decisions for achieving well‐managed processes in organizations through ergonomics indicators evaluated on a hybrid multi‐criteria perspective.
Does greenwashing obstruct sustainable environmental technologies and green financing from promoting environmental sustainability? Analytical evidence from the Indian economy
Authors: Das Narasingha , Gangopadhyay Partha , Alam Mohammad Mahtab , Mahmood Haider , Bera Pinki , Khudoykulov Khurshid , Dey Labani , Hossain Md. Emran
Published: August 2023

This study aims at assessing the impacts of green growth, in the form of adopting sustainable energy technologies and financing green projects, on environmental conditions in India. Thus, this study is important from the point of view of India's efforts in formulating strategies linked with achieving the environmental development targets enlisted under United Nations SDG‐13 declaration. In this regard, it is assumed that strategies targeted at establishing green growth in India can fail in the presence of greenwashing. To test this hypothesis, a newly introduced econometric technique, namely the Augmented‐ARDL techniques of estimation is used. Accordingly, the results obtained firstly suggest the existence of long‐run and cointegrated relationship exists between the variables of choice. Secondly, it is very much striking to find out that the the there is an inverse relationship between use of sustainable environmental technologies and environmental sustainability across India. Hence, this particular finding points to the possibility of stimulating geenwashing in the context of technology adoption in order to improve the state of the environment in India. Lastly, financing of green projects is seen to promote environmental sustainability which, in turn, affirms the absence of greenwashing in the context of green financing initiatives.
Clustering of trajectories with mixed effects classification model: Inference taking into account classification uncertainties
Authors: Dugourd Charlotte , Abichou‐Klich Amna , Ecochard René , Subtil Fabien
Published: August 2023

Classifying patient biomarker trajectories into groups has become frequent in clinical research. Mixed effects classification models can be used to model the heterogeneity of longitudinal data. The estimated parameters of typical trajectories and the partition can be provided by the classification version of the expectation maximization algorithm, named CEM. However, the variance of the parameter estimates obtained underestimates the true variance because classification uncertainties are not taken into account. This article takes into account these uncertainties by using the stochastic EM algorithm (SEM), a stochastic version of the CEM algorithm, after convergence of the CEM algorithm. The simulations showed correct coverage probabilities of the 95% confidence intervals (close to 95% except for scenarios with high bias in typical trajectories). The method was applied on a trial, called low‐cyclo, that compared the effects of low vs standard cyclosporine A doses on creatinine levels after cardiac transplantation. It identified groups of patients for whom low‐dose cyclosporine may be relevant, but with high uncertainty on the dose‐effect estimate.
Artificial rabbit optimization‐based ANFIS model development for predicting the compressive strength of GGBFS‐based concrete
Authors: Sun Qingmei
Published: August 2023

The carbon dioxide emissions associated with the production of conventional Portland cement may be mitigated through the utilization of ground granulated blast furnace slag (GGBFS). The consideration of compressive strength () is essential in the design and construction of concrete structures, as it is an essential demand in concrete mixtures. The primary objective of this study is to establish an effective approach for conducting a comprehensive evaluation of machine learning algorithms in predicting the of concrete that incorporates GGBFS. The work focuses on using the adaptive neuro‐fuzzy inference system (ANFIS) to create predictive models for . The of the collected datasets ranged from 6.3 to 101.3 MPa. The study included the artificial rabbit optimization (ARO) and Bald Eagle search algorithm (BES) to improve the effectiveness of the ANFIS approaches. The novelty of this study is attributed to several factors, including the utilization of the ARO and BES methodologies, the incorporation of GGBFS in the evaluation of , the comparison with previous research findings, and the utilization of a substantial dataset encompassing multiple input variables. These factors offer a novel method for improving the effectiveness of prediction models and advance our understanding of forecasting the mechanical characteristics of concrete. The integrated ANF‐AR and ANF‐BA systems showed good estimating skills, according to the findings, which showed R2 values of 0.9961 and 0.9967 for the ANF‐AR's training and testing components and 0.9916 and 0.9946 for the ANF‐BA, respectively. Overall, the ANFIS optimized with ARO model is recognized as the outperformed system for prediction purposes.
Erratum to: QCD at the amplitude level: Fock state interference in heavy quark electroproduction
Authors: Lyubovitskij Valery E. , Schmidt Ivan
Published: August 2023

A correction to this paper has been published: https://doi.org/10.1007/JHEP05(2023)054