bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of large‐for‐gestational‐age at birth using fetal biometry in type 1 and type 2 diabetes: A retrospective cohort study
Authors: Rathcke Sidsel L. , Sinding Marianne M. , Christensen Trine T. , Uldbjerg Niels , Christiansen Ole Bjarne , Kornblad Julia , Søndergaard Kamilla H. , Krogh Sofie , Sørensen Anne N. W.
Published: June 2024

Objective

To compare ultrasound‐assessed fetal head circumference (HC), abdominal circumference (AC), HC/AC ratio, and estimated fetal weight (EFW) in prediction of large‐for‐gestational‐age (LGA) at birth in pregnancies affected by type 1 (T1DM) and type 2 (T2DM) diabetes.

Methods

This retrospective cohort study included all women with T1DM and T2DM giving birth to singletons between 2010 and 2019 at Aalborg University Hospital, Denmark. Ultrasound scans were performed at 16, 20, 28 and 34 weeks of pregnancy. LGA was defined as birth weight deviation of 15% or greater from the expected for gestational age (≥90th centile). Prediction of LGA was assessed by logistic regression adjusted for maternal characteristics and glycated hemoglobin (HbA1c) and area under the receiver operating characteristics curve (AUC).

Results

Among 180 T1DM pregnancies, 118 (66%) had an LGA neonate at birth. At 28 weeks of pregnancy, they were predicted with AUCHC/AC = 0.67, AUCAC = 0.85, and AUCEFW = 0.86. The multivariate analysis did not improve the predictive performance of the HC/AC ratio or AC. Among 87 T2DM pregnancies, 36 (41%) had an LGA neonate at birth. At 28 weeks, they were predicted with AUCHC/AC = 0.73, AUCAC = 0.83, and AUCEFW = 0.87. In T2DM, the multivariate analysis significantly improved the predictive performance for both HC/AC ratio and AC from 20 weeks of pregnancy.

Conclusion

In T1DM and T2DM pregnancies, LGA is characterized by a general fetal overgrowth including both AC and HC. Therefore, AC and EFW perform better than the HC/AC ratio in the prediction of LGA. In T2DM, as opposed to T1DM, the predictive performance was improved by the inclusion of maternal characteristics and HbA1c in the analysis.
Range‐wide prediction of habitat suitability for king cobras under current and future scenarios
Authors: Mukherjee Subha Shankar , Patra Debidas , Hossain Asif
Published: June 2024

Ophiophagus hannah, commonly known as the king cobra, is listed as vulnerable by the International Union for Conservation of Nature (IUCN) and is protected under national laws in most countries. This charismatic species faces multiple threats, including habitat loss, human persecution, illegal trafficking, and climate change. Due to the king cobra's sensitivity to environmental conditions, its population status and trends are barely understood. This study used the MaxEnt algorithm to predict the potential distribution of king cobras across Asia, a method that has been successfully implemented in modeling distributions of various species in the region. The findings showed that Evergreen Broadleaf Trees emerged as the most influential variable for the distribution of Ophiophagus hannah with a 27.3% contribution, followed by the Mean Diurnal Range and Urban/Built‐up areas. Jackknife analysis identified the Mean Diurnal Range as having the highest testing gain. Approximately 413,268 km2 were found to have the most suitable climatic conditions for sustaining this species. Countries such as India, Myanmar, Bangladesh, Vietnam, Cambodia, Indonesia, and Malaysia were identified as having favorable conditions. Under the future climate scenario SSP5‐8.5, the extent of suitable habitats (maximum) for the king cobra is projected to decrease in the periods 2041–2060 and 2081–2100. This report provides valuable insights that could inform conservation strategies for O. hannah in these regions.
Discovery and characterization of a transient chaetal gland during the development of Capitella teleta (Sedentaria: Annelida)
Authors: Tilic Ekin , Bartolomaeus Thomas , Seaver Elaine C.
Published: June 2024

Chaetae are among the most extensively studied structures in polychaetes, serving as a defining morphological trait for annelids. Capitella teleta stands out as one of the few established annelid models for developmental and morphological studies, thus receiving significant scholarly attention. In this study, we unveil a previously unnoticed glandular structure associated with chaetae within the larvae of C. teleta. Our investigations demonstrate the absence of comparable structures in the chaetal follicles of adults and juveniles (older than 1 week), as well as during active chaetogenesis, underscoring the transient nature of these glands. This indicates that larval chaetal follicles transform into a gland that later disappears. Utilizing histology and transmission electron microscopy, we characterized these glands. Our findings underscore the diversity of chaetal ultrastructure in annelids and show that, even in well‐studied species, novel morphological details can be found. We emphasize the importance of examining various life‐history stages to capture such transient morphological features. This work lays a crucial morphological foundation and deepens our understanding of chaetae and chaetogenesis in C. teleta, paving the way for more accurate interpretations of future experimental studies on chaetogenesis in this species.
Hyper‐parameter optimizedGPRmodel based on chaos game algorithm forRFpower transistors
Authors: Gao Zhiwei , Zhou Tao , Crupi Giovanni , Cai Jialin
Published: June 2024

In this paper, a new frequency domain behavior model for radio frequency (RF) power transistors based on a hyper‐parameter optimized Gaussian process regression (GPR) method is presented. The chaos game optimization (CGO) algorithm is used to optimize GPR hyperparameters, resulting in the CGO‐GPR model. The basic theory as well as the details of the modeling process are presented. Validation of the model is conducted using a 10‐watt GaN power transistor. Compared to the standard GPR model, the proposed model achieved a significant improvement. Furthermore, the comparison with the particle swarm optimization (PSO) based GPR model (PSO‐GPR) showed that the proposed model allows achieving superior performance, thereby confirming the effectiveness of the developed modeling technique.
Profitability in rural restaurants and owners' motivation to agritourism: A case from Nepal
Authors: Bhatta Kumar , Gajurel Ram Prasad , Tanaka Toshinori , Ohe Yasuo
Published: June 2024

Rural Restaurants (RR) are located in rural areas primarily to serve the owner's business interests. However, they also play a crucial role in providing economic opportunities for rural communities and are regarded as a center for rural economy. Rural areas often face challenges such as depopulation due to limited access to public services, inadequate infrastructure, geographical remoteness, economic hardships, educational barriers, and other factors. Thus, this study aims to investigate the profitability of RRs and owners' motivations for agritourism development, as profitability and business expansion are typically positively correlated. Data from 105 samples collected in rural Nepal in 2022 and 2023 were analyzed using Tobit and Ordered Logit regression models, respectively. The study conceptualizes and confirms various contributors to RR profitability, including factors related to the supply side, demand appeal, and those influenced by pandemic‐related factors. Additionally, we explored how owners' motivations for agritourism are influenced by the restaurant's characteristics, quality‐related factors, and other attributes. Policymakers need to support RR owners in developing agritourism initiatives and contribute to quality control through effective enforcement of consumer laws by a responsible and robust quality control team.
Quality of Life Outcomes for Parotid Malignancies
Authors: Tang Anthony , Li Jinhong , Scheff Nicole , Johnson Jonas T. , Contrera Kevin J. , Nilsen Marci L.
Published: June 2024

Background

This study describes patient‐reported outcome measures (PROMs) and associated factors in patients who underwent surgery for malignant parotid tumors (MPT).

Methods

This is a retrospective study of all surgically treated MPT patients in a multidisciplinary head and neck cancer (HNC) survivorship clinic (2017–2023). PROMs included University of Washington Quality of Life Questionnaire (UW‐QOL), Eating Assessment Tool (EAT‐10), Patient Health Questionnaire (PHQ‐8), Generalized Anxiety Disorder (GAD‐7), Neck Disability Index (NDI), and Insomnia Severity Index. Multivariable regression analysis was used to investigate clinical predictors associated with PROMs.

Results

In 62 MPT patients, the prevalence of clinically relevant dysphagia symptoms (EAT‐10), elevated symptoms of depression (PHQ‐8), moderate/severe symptoms of anxiety (GAD‐7), moderate/severe neck pain with activities of daily living (NDI), and moderate/severe symptoms of insomnia at last follow‐up was 32.3%, 15.5%, 7.1%, 17.7%, and 7.2%, respectively. Nonparametric one‐sided test revealed that patients treated with adjuvant CRT had significantly worse physical QOL, social‐emotional QOL, and swallowing scores than patients treated with surgery alone (p = 0.01, p = 0.02, p = 0.03, respectively); that patients treated with surgery and adjuvant RT had significantly worse physical QOL and social‐emotional QOL than patients treated with surgery alone (p < 0.01, p = 0.01, respectively) and that patients treated with surgery and adjuvant CRT had significantly worse swallowing and neck pain than patients treated with surgery and adjuvant RT (p = 0.03, p = 0.05, respectively).

Conclusions

In patients with surgically treated MPT, adjuvant CRT and RT were associated with worse PROMs.

Level of Evidence

4 Laryngoscope, 134:4549–4556, 2024
A strong subadditivity‐like inequality for quantum entropy in semifinite von Neumann algebras
Authors: Łuczak Andrzej
Published: June 2024

Let be a semifinite von Neumann algebra with a normal faithful semifinite trace , and let , , be its subalgebras such that and that restricted to any of these subalgebras is semifinite. Denote by , , and the normal conditional expectations from onto , and , respectively, such that is invariant with respect to any of them. The quadruple , , , is said to be a commuting square if
In this note, we show that the property of being a commuting square is characterized by a sort of the SSA‐like (strong subadditivity of entropy) inequality
for an arbitrary normal state on , where denotes the Segal entropy of the state . The situation when we have equality in the inequality above is also investigated, and various equivalent conditions are obtained, in an especially appealing form for finite von Neumann algebras. For such algebras, one more condition is obtained under the assumption of independence of the algebras and .
Positive solutions for nonhomogenous Choquard equations involving doubly critical exponents
Authors: Zhang Haiqi , Zhang Binlin
Published: June 2024

This paper is concerned with nonhomogenous Choquard equations involving doubly critical exponents. First, we use a fixed point theorem to prove the existence of positive solutions to the above equation under certain assumptions. Then, on the positive solution of the equation, we get the regularity in a bounded domain with estimating the
‐bounds by Moser's iterative technique.
On a composition of Ismail–May operator
Authors: Gupta Vijay , Sharma Vaibhav
Published: June 2024

In this paper, we address a discrete operator based on the composition of Ismail–May operator and Szász–Mirakjan operator and study its approximation properties for various classes of continuous functions using Taylor's formula. We estimate its moments and further give direct theorems employing Peetre's K‐functional and the modulus of continuity. Furthermore, Voronovskaja‐type asymptotic theorems are given. Additionally, we provide further compositions and give a comparison among their approximation properties.
Predicting radiation‐induced immune suppression in lung cancer patients treated with stereotactic body radiation therapy
Authors: Colen Jonathan , Nguyen Cam , Liyanage Seth W. , Aliotta Eric , Chen Joe , Alonso Clayton , Romano Kara , Peach Sean , Showalter Timothy , Read Paul , Larner James , Wijesooriya Krishni
Published: June 2024

Background

Stereotactic body radiation therapy (SBRT) is known to modulate the immune system and contribute to the generation of anti‐tumor T cells and stimulate T cell infiltration into tumors. Radiation‐induced immune suppression (RIIS) is a side effect of radiation therapy that can decrease immunological function by killing naive T cells as well as SBRT‐induced newly created effector T cells, suppressing the immune response to tumors and increasing susceptibility to infections.

Purpose

RIIS varies substantially among patients and it is currently unclear what drives this variability. Models that can accurately predict RIIS in near real time based on treatment plan characteristics would allow treatment planners to maintain current protocol specific dosimetric criteria while minimizing immune suppression. In this paper, we present an algorithm to predict RIIS based on a model of circulating blood using early stage lung cancer patients treated with SBRT.

Methods

This Python‐based algorithm uses DICOM data for radiation therapy treatment plans, dose maps, patient CT data sets, and organ delineations to stochastically simulate blood flow and predict the doses absorbed by circulating lymphocytes. These absorbed doses are used to predict the fraction of lymphocytes killed by a given treatment plan. Finally, the time dependence of absolute lymphocyte count (ALC) following SBRT is modeled using longitudinal blood data up to a year after treatment. This model was developed and evaluated on a cohort of 64 patients with 10‐fold cross validation.

Results

Our algorithm predicted post‐treatment ALC with an average error of cells/L with 89% of the patients having a prediction error below 0.5 × 109 cells/L. The accuracy was consistent across a wide range of clinical and treatment variables. Our model is able to predict post‐treatment ALC < 0.8 (grade 2 lymphopenia), with a sensitivity of 81% and a specificity of 98%. This model has a ∼38‐s end‐to‐end prediction time of post treatment ALC.

Conclusion

Our model performed well in predicting RIIS in patients treated using lung SBRT. With near‐real time model prediction time, it has the capability to be interfaced with treatment planning systems to prospectively reduce immune cell toxicity while maintaining national SBRT conformity and plan quality criteria.
Applications of machine learning in urodynamics: A narrative review
Authors: Liu Xin , Zhong Ping , Gao Yi , Liao Limin
Published: June 2024

Background

Machine learning algorithms as a research tool, including traditional machine learning and deep learning, are increasingly applied to the field of urodynamics. However, no studies have evaluated how to select appropriate algorithm models for different urodynamic research tasks.

Methods

We undertook a narrative review evaluating how the published literature reports the applications of machine learning in urodynamics. We searched PubMed up to December 2023, limited to the English language. We selected the following search terms: artificial intelligence, machine learning, deep learning, urodynamics, and lower urinary tract symptoms. We identified three domains for assessment in advance of commencing the review. These were the applications of urodynamic studies examination, applications of diagnoses of dysfunction related to urodynamics, and applications of prognosis prediction.

Results

The machine learning algorithm applied in the field of urodynamics can be mainly divided into three aspects, which are urodynamic examination, diagnosis of urinary tract dysfunction and prediction of the efficacy of various treatment methods. Most of these studies were single‐center retrospective studies, lacking external validation, requiring further validation of model generalization ability, and insufficient sample size. The relevant research in this field is still in the preliminary exploration stage; there are few high‐quality multi‐center clinical studies, and the performance of various models still needs to be further optimized, and there is still a distance from clinical application.

Conclusions

At present, there is no research to summarize and analyze the machine learning algorithms applied in the field of urodynamics. The purpose of this review is to summarize and classify the machine learning algorithms applied in this field and to guide researchers to select the appropriate algorithm model for different task requirements to achieve the best results.
Density functional theory‐based rapid and accurate estimation of reduction potentials of acridinium derivatives in ground and excited state
Authors: Choi Jiyoon , Kang Kyungtae , Park Ji Hun , Kim Hyungjun
Published: June 2024

We devised a quantum chemical simulation protocol that can rapidly and accurately predict ground and excited state reduction potentials (E0 and E*, respectively) of acridinium photoredox catalysts (PCs). To bypass time‐consuming excited state geometry optimizations, we used ground state equilibrium geometries to compute the electronic energy of excited states, which provides reasonable E0 and E* estimates. The contribution of Hartree‐Fock exchange (HFX) in density functionals was systematically varied to estimate E0 and E*. In addition to reproducing experimental results, physically sensible models, such as correct descriptions of exciton behavior, are highly necessary. Based on the exciton correlation values, the appropriate amount of HFX in the B3LYP functional was determined to be 30 % to yield physically sensible bound electron‐hole pairs for small organic molecules. We also investigated the impact of basis sets on the predictability of E0 and E*. Geometry optimizations with B3LYP‐D2(HFX 20 %)/6‐31G and single point energy refinement with (TD‐)B3LYP‐D2(HFX 30%)/6‐311++G(d,p) yielded the best results. The transferability of the suggested protocol was confirmed with a test set consisting of eight acridinium derivatives. This study can provide reasonably accurate results with relatively small amounts of computational resources, and it is therefore expected to greatly contribute to the development of new acridinium PCs.
A Hybrid Deep Learning‐Based Power Management Strategy for PV‐Assisted Desalination Plant
Authors: Almashnowi Majed Y. A. , AlGhamdi Sami , Alamier Waleed M. , Ali Syed Kashif , Bakather Omer Y. , Hassan Mohamed , Qudsieh Isam Y. , Imran Mohd , Alam Md Mottahir
Published: June 2024

The increasing global need for freshwater has led to the widespread implementation of photovoltaic (PV) assisted desalination facilities as a viable and environmentally friendly remedy. The necessity for these plants resides in executing an effective power management strategy to provide dependable and economically feasible water generation. This paper utilizes a mixed architecture consisting of a convolutional neural network (CNN) and a deep Q‐learning Network (DQN) to implement a hybrid deep learning‐based power management strategy. The presented approach is modeled and executed in matrix laboratory (MATLAB) language, and the experimental findings validated that this algorithm achieved a computational time of 0.2 s and an energy loss of 0.01 megawatts, which is lower than the conventional models. Furthermore, the proposed strategy achieved a remarkable fit with an accuracy rate of 0.99, demonstrating its effectiveness in handling diverse load power and solar profiles in power management. Implementing this hybrid approach holds promise for a substantial reduction in operational expenditures and the advancement of sustainability in freshwater generation, making a valuable contribution toward a more environmentally friendly and optimized future for the desalination sector.
Evaluating drug interaction potential from cytokine release syndrome using a physiologically based pharmacokinetic model: A case study of teclistamab
Authors: Willemin Marie‐Emilie , Wang Lin Shun Xin , De Zwart Loeckie , Wu Liviawati S. , Miao Xin , Verona Raluca , Banerjee Arnob , Liu Baolian , Kobos Rachel , Qi Ming , Ouellet Daniele , Goldberg Jenna D. , Girgis Suzette
Published: June 2024

Cytokine release syndrome (CRS) was associated with teclistamab treatment in the phase I/II MajesTEC‐1 study. Cytokines, especially interleukin (IL)‐6, are known suppressors of cytochrome P450 (CYP) enzymes' activity. A physiologically based pharmacokinetic model evaluated the impact of IL‐6 serum levels on exposure of substrates of various CYP enzymes (1A2, 2C9, 2C19, 3A4, 3A5). Two IL‐6 kinetics profiles were assessed, the mean IL‐6 profile with a maximum concentration (Cmax) of IL‐6 (21 pg/mL) and the IL‐6 profile of the patient presenting the highest IL‐6 Cmax (288 pg/mL) among patients receiving the recommended phase II dose of teclistamab in MajesTEC‐1. For the mean IL‐6 kinetics profile, teclistamab was predicted to result in a limited change in exposure of CYP substrates (area under the curve [AUC] mean ratio 0.87–1.20). For the maximum IL‐6 kinetics profile, the impact on omeprazole, simvastatin, midazolam, and cyclosporine exposure was weak to moderate (mean AUC ratios 1.90–2.23), and minimal for caffeine and s‐warfarin (mean AUC ratios 0.82–1.25). Maximum change in exposure for these substrates occurred 3–4 days after step‐up dosing in cycle 1. These results suggest that after cycle 1, drug interaction from IL‐6 effect has no meaningful impact on CYP activities, with minimal or moderate impact on CYP substrates. The highest risk of drug interaction is expected to occur during step‐up dosing up to 7 days after the first treatment dose (1.5 mg/kg subcutaneously) and during and after CRS.
Gamma‐Ray‐Induced Photoelectric Field Exacerbating Irradiation Damage in Ceramic Capacitors
Authors: Yang Ping , Yang Zenghui , Deng Shuairong , Zhao Wei , Ding Yi , Pan Yongqi , Zhou Hang , Meng Dechao , Wei Su‐Huai
Published: June 2024

Ceramic capacitors are widely used in radioactive environments and are known to take irradiation damages, but most of previous studies of its reliability focus on thermal or electrical issues, and much less is known about the microscopic mechanism of its irradiation damaging process. Herein, it is shown that the capacitance of ceramic capacitors can change significantly under continuous gamma‐ray irradiation. Moreover, it is noticed that ex situ measurements will underestimate the effect comparing with the in situ one. Herein, it is discovered that this difference is due to the gamma‐ray‐induced photoelectric field, which dissipate rapidly in ex situ measurements. While the impact of the photoelectric field on the capacitance can be seen in situ, due to the recombination of photogenerated carriers and annealing of defects after irradiation, ex situ measurements only account for a part of the irradiation damage. This discovery indicates that ex situ measurements, which are prevailing in irradiation damage studies, can miss critical information, and in situ measurements are necessary for revealing the mechanism of the process.
Decentralized adaptive control of large‐scale time‐varying stochastic nonlinear systems with unknown covariance
Authors: Gu Jiabao , Wang Hui , Li Wuquan
Published: June 2024

In this paper, a novel decentralized adaptive state‐feedback design method is proposed for large‐scale stochastic nonlinear systems. Different from the existing results, we consider more practical and more general systems, that is, systems with both unknown covariance and time‐varying powers. When dealing with the unknown time‐varying covariance, we do not need to know its bound, but use the estimator to design an adaptive law function. Then, a new adaptive controller is constructed with the backstepping method to ensure that the closed‐loop system is globally stable in probability, and that the states are regulated to the origin almost surely. Finally, a simulation example is given to illustrate the effectiveness of the design scheme.
New results on exponential estimate for 2‐D positive systems with delays
Authors: Nguyen Tran Ngoc , Nam Phan Thanh , Trinh Hieu
Published: June 2024

We present a new method to the problem of finding ‐exponential state estimates for a class of 2‐D positive discrete‐time systems with bounded time‐delays. A less conservative sufficient condition for the ‐exponential stability is derived and tighter ‐exponential state estimates are provided. The effectiveness of the presented method is illustrated through two numerical examples.
Water stagnancy and wastewater input enhance primary productivity in an engineered river system
Authors: Sarkar Siddhartha , Kumar Sanjeev
Published: June 2024

Under warming conditions and with increasing human perturbations, rivers across the globe are facing drastic shifts in their hydrologic regime, resulting in fragmentation and disconnection from the catchment. Subsequently, a dependency on in situ primary productivity as the source of organic matter increases and warrants detailed investigation of the nature of primary production in urbanized river systems. In this study, primary productivity was estimated at multiple locations along the continuum of an engineered (Sabarmati) and a free flowing (Mahi) river systems in India using 13C tracer incubation method. Significantly enhanced primary productivity in the riverfront (engineered construction along the Sabarmati that holds water supplied by a canal) and polluted downstream of the Sabarmati compared to free flowing Mahi was observed. It was also observed that water stagnancy, temperature, and nutrient availability were the key factors regulating the rates of primary productivity in the urban river system. The study highlights the salient features of riverine primary productivity associated with engineered modifications, which needs to be considered for future river development projects.
Heterogeneity in organizational search behaviors: The case of corporate venture capital units
Authors: Shankar Raj Krishnan , Schückes Magnus , Gutmann Tobias
Published: June 2024

Research Summary

Our qualitative study of five corporate venture capital (CVC) units reveals that CVC is organized along one of two distinct pathways—order‐taker or free‐bird. Our two‐pathway model deconstructs the heterogeneity within CVC designs and provides detailed insights into the processual nature of CVC search mechanisms. We find evidence that the locus of problem formulation influences the chosen search behavior. While order‐takers respond to predefined corporate‐led problem formulation, free‐birds allow the venture market to guide search behavior. Differences in search processes can thus be attributed to the pursuit of distinct problem‐solution pairs. Implications for CVC and organizational search literature are discussed.

Managerial Summary

Organizations search for new knowledge and technologies using corporate venture capital (CVC) units. Despite growing evidence of heterogeneity in CVC designs, managers continue to have limited insights for designing and running such CVC units. In contrast to previous recommendations to use structural attributes and/or institutional logics to design and manage CVCs, we provide managers an organizational search lens which reveals significant variations in how corporations search for new ventures. We identified two extreme CVC designs driven by the locus of problem formulation (internal vs. external): order‐takers—who respond to a predefined and corporate‐led problem formulation approach, and free‐birds—who shape the problem formulation guided by venture market dynamics. We point to design differences across popular CVC subprocesses which can be handy for managers.
Investigating Hydrogen Bonding Interactions in Aniline‐Acetone Binary Mixture through Molecular Dynamics Simulations
Authors: Ajmal Rahman M. K. , Abdulkareem U. , Swathi P. V. , Madhurima V.
Published: June 2024

Binary liquid systems serve as valuable prototypes for comprehending biologically and chemically relevant properties of hydrogen bonds, revealing both noteworthy patterns and anomalies in their behaviour. Aniline, acetone and their binary mixtures with other liquids are used in various industrial processes, drug design, and as cleaning agents. This study is a molecular dynamics exploration of aniline and acetone binary mixture, over a concentration range of 9 : 1–1 : 9 for each component. The investigation includes employing techniques such as radial distribution function (RDF), coordination number calculation, hydrogen bond statistics, and graph theoretical analysis (GTA) through the NetworkX module in python, cluster analysis, Voronoi entropy calculation, interaction energy calculation and FTIR spectroscopy for all concentrations studied. The results uncover a compelling trend: a decrease in the number of hydrogen bonds as the concentration of acetone increases. Additionally, increased acetone concentration correlates positively with the breakdown of larger and more complex hydrogen‐bonded structures, indicating the formation of small hydrogen‐bond structures.
Green Biosynthesis of TiO2Nanoparticles Using Aqueous Extract ofBrassica juncea(L.) Czern Seed: Characterization, Antimicrobial, Antioxidant and Anticancer Activities
Authors: Jeyaraj S. , Mary Saral A.
Published: June 2024

Primary objective of this research was to examine the biogenic production of TiO2NPs usingBrassica juncea (L.)Czern seed and investigate the prospective uses of thus synthesized nanoparticles in the area of biomedicine. The synthesized TiO2NPs were subjected to characterization using several analytical methods namely TEM, UV‐vis, XRD, FE‐SEM, FTIR and EDAX. The average particle size (TEM) is found to be 38 nm, exhibiting irregular shapes. The FT‐IR spectra indicated that the extract contains functional groups, such as polyphenolic, hydroxyl and carboxylic groups, which are likely responsible for formation of nanoparticles. The cytotoxicity studies of the synthesized TiO2NPs against breast cancer cells (MCF‐7) and lung cells (A549) are shown to be dosage dependent. The inhibitory doses (IC50) were determined to be 43.98 μg/mL and 74.50 μg/mL on MCF‐7 and A549 cells, respectively. Green synthesized TiO2NPs were assessed for antioxidant activity inhibition rate (DPPH 89.42 %). TiO2NPs exhibited a maximal zone of inhibition of Staphylococcus aureus 23±0.20 mm against and 20±0.30 against Klebsiella pneumoniae at a concentration of 100 μg/mL, indicating strong antibacterial activity. The findings suggestBrassica juncea (L.)Czern seed encapsulated TiO2NPs possesses excellent biological applications which can be explored for its application in pharmaceutical field.
Bioinspired Zwitterionic Nanowires with Simultaneous Biofouling Reduction and Release
Authors: Wang Jing , Macdonald Brian , Cho Tae H. , Repetto Taylor , Sun Kai , Tuteja Anish , Dasgupta Neil P.
Published: June 2024

Marine biofouling is a complex and dynamic process that significantly increases the carbon emissions from the maritime industry by increasing drag losses. However, there are no existing non‐toxic marine paints that can achieve both effective fouling reduction and efficient fouling release. Inspired by antifouling strategies in nature, herein, a superoleophobic zwitterionic nanowire coating with a nanostructured hydration layer is introduced, which exhibits simultaneous fouling reduction and release performance. The zwitterionic nanowires demonstrate >25% improvement in fouling reduction compared to state‐of‐the‐art antifouling nanostructures, and four times higher fouling‐release compared to conventional zwitterionic coatings. Fouling release is successfully achieved under a wall shear force that is four orders of magnitude lower than regular water jet cleaning. The mechanism of this simultaneous fouling reduction and release behavior is explored, and it is found that a combination of 1) a mechanical biocidal effect from the nanowire geometry, and 2) low interfacial adhesion resulting from the nanostructured hydration layer, are the major contributing factors. These findings provide insights into the design of nanostructured coatings with simultaneous fouling reduction and release. The newly established synthesis procedure for the zwitterionic nanowires opens new pathways for implementation as antifouling coatings in the maritime industry and biomedical devices.
Strong Metal‐Support Interaction Modulation between Pt Nanoclusters and Mn3O4 Nanosheets through Oxygen Vacancy Control to Achieve High Activities for Acidic Hydrogen Evolution
Authors: Hu Dongxiong , Wang Yongjie , Chen Weiheng , Jiang Zhongqing , Deng Binglu , Jiang Zhong‐Jie
Published: June 2024

The optimization of metal‐support interactions is used to fabricate noble metal‐based nanoclusters with high activity for hydrogen evolution reaction (HER) in acid media. Specifically, the oxygen‐defective Mn3O4 nanosheets supported Pt nanoclusters of ≈1.71 nm in diameter (Pt/V·‐Mn3O4 NSs) are synthesized through the controlled solvothermal reaction. The Pt/V·‐Mn3O4 NSs show a superior activity and excellent stability for the HER in the acidic media. They only require an overpotential of 19 mV to drive −10 mA cm−2 and show negligible activity loss at −10 and −250 mA cm−2 for >200 and >60 h, respectively. Their Pt mass activity is 12.4 times higher than that of the Pt/C and even higher than those of many single‐atom based Pt catalysts. DFT calculations show that their high HER activity arises mainly from the strong metal‐support interaction between Pt and Mn3O4. It can facilitate the charge transfer from Mn3O4 to Pt, optimizing the H adsorption on the catalyst surface and promoting the evolution of H2 through the Volmer–Tafel mechanism. The oxygen vacancies in the V·‐Mn3O4 NSs are found to be inconducive to the high activity of the Pt/V·‐Mn3O4 NSs, highlighting the great importance to reduce the vacancy levels in V·‐Mn3O4 NSs.
Influence of end restraint strength on the structural fire behavior and deterioration mechanism of RC frame beams
Authors: Lu Limin , Zhao Zixian , Xu Weihao , Wang Shouxing , Li Kang , Yuan Guanglin , Shu Qianjin , Yuan Yong , Taerwe Luc
Published: June 2024

The end restraint strength of the reinforced concrete (RC) beams under the fire conditions may greatly influence the inner force redistribution and the structural behavior of the beams, even the stability of the whole structure. The structural fire behavior of two full‐scale frame beams with different end restraint strength under load were studied based on experiment and simulation. The temperature field, reinforcement strain, beam deflection, end axial displacement, and rotation angle of the structure during the whole heating and cooling process were measured. The influence of end restraint strength on the structural behavior was analyzed. The results show that the vertical displacement, axial force, end bending moment, and angular displacement first increase rapidly, then decrease gradually and become stable in the whole process; the lateral displacement increases first and then stabilizes; the change of axial and rotational deformations appeared to be non‐proportional with the corresponding restraining forces, reflecting that the axial and the rotational restraint strength at the ends of the beams decreased with the rise of temperature. The restraining strength of beams that submitted to fire globally decreased faster, and leading to a severe fire response and an earlier failure of the structure. The analysis results and the conclusions will supply scientific basis for the fire‐resistance design and safety evaluation on complex structures.
A multi-omics approach to elucidate okadaic acid-induced changes in human HepaRG hepatocarcinoma cells
Authors: Wuerger Leonie T. D. , Sprenger Heike , Krasikova Ksenia , Templin Markus , Stahl Aaron , Herfurth Uta M. , Sieg Holger , Braeuning Albert
Published: June 2024

Okadaic acid (OA), a prevalent marine biotoxin found in shellfish, is known for causing acute gastrointestinal symptoms. Despite its potential to reach the bloodstream and the liver, the hepatic effects of OA are not well understood, highlighting a significant research gap. This study aims to comprehensively elucidate the impact of OA on the liver by examining the transcriptome, proteome, and phosphoproteome alterations in human HepaRG liver cells exposed to non-cytotoxic OA concentrations. We employed an integrative multi-omics approach, encompassing RNA sequencing, shotgun proteomics, phosphoproteomics, and targeted DigiWest analysis. This enabled a detailed exploration of gene and protein expression changes, alongside phosphorylation patterns under OA treatment. The study reveals concentration- and time-dependent deregulation in gene and protein expression, with a significant down-regulation of xenobiotic and lipid metabolism pathways. Up-regulated pathways include actin crosslink formation and a deregulation of apoptotic pathways. Notably, our results revealed that OA, as a potent phosphatase inhibitor, induces alterations in actin filament organization. Phosphoproteomics data highlighted the importance of phosphorylation in enzyme activity regulation, particularly affecting proteins involved in the regulation of the cytoskeleton. OA's inhibition of PP2A further leads to various downstream effects, including alterations in protein translation and energy metabolism. This research expands the understanding of OA's systemic impact, emphasizing its role in modulating the phosphorylation landscape, which influences crucial cellular processes. The results underscore OA's multifaceted effects on the liver, particularly through PP2A inhibition, impacting xenobiotic metabolism, cytoskeletal dynamics, and energy homeostasis. These insights enhance our comprehension of OA's biological significance and potential health risks.
Rocaglamide promotes infiltration and differentiation of T cells and coordinates with PD-1 inhibitor to overcome checkpoint resistance in multiple tumor models
Authors: Luo Jiaojiao , Ng Wanyi , Liu Yangli , Wang Lixin , Gong Chenyuan , Zhou Yufu , Fang Cheng , Zhu Shiguo , Yao Chao
Published: June 2024

Tumor-infiltrating lymphocyte (TIL) deficiency is the most conspicuous obstacle to limit the cancer immunotherapy. Immune checkpoint inhibitors (ICIs), such as anti-PD-1 antibody, have achieved great success in clinical practice. However, due to the limitation of response rates of ICIs, some patients fail to benefit from monotherapy. Thus, novel combination therapy that could improve the response rates emerges as new strategies for cancer treatment. Here, we reported that the natural product rocaglamide (RocA) increased tumor-infiltrating T cells and promoted Th17 differentiation of CD4+ TILs. Despite RocA monotherapy upregulated PD-1 expression of TILs, which was considered as the consequence of T cell activation, combining RocA with anti-PD-1 antibody significantly downregulated the expression of PD-1 and promoted proliferation of TILs. Taken together, these findings demonstrated that RocA could fuel the T cell anti-tumor immunity and revealed the remarkable potential of RocA as a therapeutic candidate when combining with the ICIs.
The biological roles of CD47 in ovarian cancer progression
Authors: Xing Linan , Wang Zhao , Feng Yue , Luo Haixia , Dai Guijiang , Sang Lin , Zhang Chunlong , Qian Jianhua
Published: June 2024

Ovarian cancer is one of the most lethal malignant tumors, characterized by high incidence and poor prognosis. Patients relapse occurred in 65–80% after initial treatment. To date, no effective treatment has been established for these patients. Recently, CD47 has been considered as a promising immunotherapy target. In this paper, we reviewed the biological roles of CD47 in ovarian cancer and summarized the related mechanisms. For most types of cancers, the CD47/Sirpα immune checkpoint has attracted the most attention in immunotherapy. Notably, CD47 monoclonal antibodies and related molecules are promising in the immunotherapy of ovarian cancer, and further research is needed. In the future, new immunotherapy regimens targeting CD47 can be applied to the clinical treatment of ovarian cancer patients.
Enhanced abscopal anti-tumor response via a triple combination of thermal ablation, IL-21, and PD-1 inhibition therapy
Authors: Wu Shaoxian , Jiang Hongwei , Fang Zhang , Wu You , Jiao Jing , Fang Weiwei , Wu Yue , Lang Yanyan , Chen Ning , Zhong Ziyang , Chen Lujun , Zheng Xiao , Lu Binfeng , Jiang Jingting
Published: June 2024

Despite the success of immune checkpoint inhibitors (ICIs) in treating solid tumors, lots of patients remain unresponsive to this therapy. Microwave ablation (MWA) stimulates systemic adaptive immunity against tumor cells by releasing tumor antigens. Additionally, IL-21 has demonstrated importance in stimulating T-cell effector function. The combination of these three therapies—MWA, IL-21, and anti-PD-1 monoclonal antibodies (mAbs)—has yet to be explored in the context of cancer treatment.

In this study, we explored the impact of thermal ablation on IL-21R expression in tumor-infiltrating lymphocytes (TILs). Subsequently, we assessed alterations in the tumor microenvironment (TME) and peripheral lymphoid organs. Additionally, we conducted a thorough examination of tumor-infiltrating CD45+ immune cells across various treatment groups using single-cell RNA sequencing (scRNA-seq). Moreover, we determined the potential anti-tumor effects of the triple combination involving MWA, IL-21, and anti-PD-1 mAbs.

Our findings revealed that MWA upregulated the expression of IL-21R on various immune cells in the untreated tumors. The combination of MWA with IL-21 exhibited a robust abscopal anti-tumor effect, enhancing the effector function of CD8+ T cells and facilitating dendritic cells' maturation and antigen presentation in the untreated tumor. Notably, the observed abscopal anti-tumor effect resulting from the combination is contingent upon T-cell recirculation, indicating the reliance of systemic adaptive immunity for this treatment regimen. Additionally, the combination of MWA, IL-21, and PD-1 mAbs demonstrated profound abscopal anti-tumor efficacy. Our findings provide support for further clinical investigation into a triple combination therapy involving MWA, IL-21, and ICIs for the treatment of metastatic cancer.
Combined use of tyrosine kinase inhibitors with PD-(L)1 blockade increased the risk of thyroid dysfunction in PD-(L)1 blockade: a prospective study
Authors: Kobayashi Tomoko , Iwama Shintaro , Yamagami Ayana , Izuchi Tetsushi , Suzuki Koji , Otake Koki , Yasuda Yoshinori , Ando Masahiko , Onoue Takeshi , Miyata Takashi , Sugiyama Mariko , Hagiwara Daisuke , Suga Hidetaka , Banno Ryoichi , Hase Tetsunari , Nishio Naoki , Mori Shoichiro , Shimokata Tomoya , Sano Tomoyasu , Niimi Kaoru , Yoshikawa Nobuhisa , Akamatsu Shusuke , Ando Yuichi , Akiyama Masashi , Sone Michihiko , Ishii Makoto , Arima Hiroshi
Published: June 2024

Background

Anti-programmed cell death-1 (ligand-1) antibody [PD-(L)1-Ab] can cause destructive thyroiditis and/or hypothyroidism. In addition, tyrosine kinase inhibitors (TKIs) frequently induce hypothyroidism. The aim of this prospective study is to examine the incidence and clinical characteristics of thyroid dysfunction induced by combination therapy of a PD-(L)1-Ab and TKI [PD-(L)1-Ab/TKI].

Methods

A total of 757 patients treated with PD-(L)1-Ab or PD-(L)1-Ab/TKI were evaluated for anti-thyroid antibodies (ATAs) at baseline and for thyroid function for 48 weeks after treatment initiation and then observed until the last visit.

Results

The cumulative incidences of destructive thyroiditis [4/23 (17.4%) vs. 45/734 (6.1%) patients, p < 0.001], isolated hypothyroidism [10/23 (43.5%) vs. 29/734 (4.0%) patients, p < 0.001], and all thyroid dysfunction [14/23 (60.9%) vs. 74/734 (10.1%) patients, p < 0.001] were significantly higher in the PD-(L)1-Ab/TKI group than PD-(L)1-Ab group, respectively. All patients positive for ATAs at baseline developed thyroid dysfunction after PD-(L)1-Ab/TKI treatment, a significantly higher incidence than that in those negative for ATAs at baseline [4/4 (100%) vs. 10/19 (52.6%) patients, p = 0.026].

Conclusions

The addition of TKIs increased the risk of thyroid dysfunction induced by PD-(L)1-Ab, with the risk being higher in patients positive for baseline ATAs.
Deep learning-based image segmentation for instantaneous flame front extraction
Authors: Strässle Ruben M. , Faldella Filippo , Doll Ulrich
Published: June 2024

This paper delves into the methodology employed in examining lean premixed turbulent flame fronts extracted from Planar Laser Induced Fluorescence (PLIF) images at elevated pressures. In such flow regimes, the PLIF signal suffers from significant collisional quenching, typically resulting in image data with low signal-to-noise ratio (SNR). This poses severe difficulties for conventional flame front extraction algorithms based on intensity gradients and requires intense user intervention to yield acceptable results. In this work, we propose Convolutional Neural Network (CNN)-based Deep Learning (DL) models as an alternative to problem specific conventional methods. The pretrained DL models were fine-tuned, employing data augmentation, on a small annotated dataset including a variety of conditions between SNR $$\approx$$
≈
1.6 to 2.6 and subsequently evaluated. All DL models significantly outperformed the best-scoring conventional implementation both quantitatively and visually, while having similar inference times. IoU-scores and Recall values were found to be up to a factor $$\approx$$
≈
1.2 and $$\approx$$
≈
2.5 higher, respectively, with $$\approx$$
≈
1.15 times improved Precision. Small-scale structures were captured much better with fewer erroneous predictions, becoming particularly pronounced for the lower SNR data investigated. Moreover, by applying artificially modeled noise, it was shown that the range of image conditions in terms of SNR that can be reliably processed extends well beyond the images included in the training data, and satisfactory segmentation performances were found for SNR as low as $$\approx$$
≈
1.1. The presented DL-based flame front detection algorithm marks a methodology with significantly increased detection performance, while a similar computational effort for inference is achieved and the need for user-based parameter tuning is eliminated. It enables a very accurate extraction of instantaneous flame fronts in large image datasets where supervised processing is infeasible, unlocking unprecedented possibilities for the study of flame dynamics and instability mechanisms at industry-relevant conditions.
Recommendations for defining giant cell arteritis fast-track clinics. English version
Authors: Schmidt Wolfgang A. , Czihal Michael , Gernert Michael , Hartung Wolfgang , Hellmich Bernhard , Ohrndorf Sarah , Riemekasten Gabriela , Schäfer Valentin S. , Strunk Johannes , Venhoff Nils
Published: June 2024

A German expert committee recommends defining fast-track clinics (FTC) for the acute diagnosis of giant cell arteritis (GCA) as follows: easy and prompt reachability at least on weekdays, scheduling appointments ideally within 24 h, examination by a specialist with GCA expertise, ≥ 2 experts per FTC, ≥ 50 patients with suspected GCA per year, sonologists with ≥ 300 (≥ 50) temporal and axillary artery examinations, adherence to standard operating procedures, availability of an ≥ 18 (≥ 15) MHz and a lower frequency linear ultrasound probe, and collaboration with partners for neurology and ophthalmology consultations, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT, possibly CT), and for temporal artery biopsy.