bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nanoelectrospray based synthesis of large, transportable membranes with integrated membrane proteins
Authors: Wilm Matthias 
Published: October 2024

AbstractMembrane proteins tend to be difficult to study since they need to be integrated into a lipid bilayer membrane to function properly. This study presents a method to synthesize a macroscopically large and freely transportable membrane with integrated membrane proteins which is useful for studying membrane proteins and protein complexes in isolation. The method could serve as a blueprint for the production of larger quantities of functionalised membranes for integration into technical devices similar to the MinION DNA sequencer. It is possible to self-assemble larger biological membranes on solid surfaces. However, they cannot be removed from their solid support without destroying them. In transportable form, self-assembled membranes are limited to sizes of about 17 nm in nanodiscs. Here we electrospray a series of molecular layers onto the liquid surface of a buffer solution which creates a flat, liquid environment on the surface that directs the self-assembly of the membrane. This method enables us to experimentally control the membrane composition and to succeed in producing large membranes with integrated OmpG, a transmembrane pore protein. The technique is compatible with the assembly of membrane based protein complexes. Listeriolysin O and pneumolysin efficiently assemble into non-covalent membrane pore complexes of approximately 30 units or more within the surface layer.
A novel LRR receptor-like kinase BRAK reciprocally phosphorylates PSKR1 to enhance growth and defense in tomato
Authors: Ding Shuting , Feng Shuxian , Zhou Shibo , Zhao Zhengran , Liang Xiao , Wang Jiao , Fu Ruishuang , Deng Rui , Zhang Tao , Shao Shujun , Yu Jingquan , Foyer Christine H , Shi Kai 
Published: October 2024

AbstractPlants face constant threats from pathogens, leading to growth retardation and crop failure. Cell-surface leucine-rich repeat receptor-like kinases (LRR-RLKs) are crucial for plant growth and defense, but their specific functions, especially to necrotrophic fungal pathogens, are largely unknown. Here, we identified an LRR-RLK (Solyc06g069650) in tomato (Solanum lycopersicum) induced by the economically important necrotrophic pathogen Botrytis cinerea. Knocking out this LRR-RLK reduced plant growth and increased sensitivity to B. cinerea, while its overexpression led to enhanced growth, yield, and resistance. We named this LRR-RLK as BRAK (B. cinerea resistance-associated kinase). Yeast two-hybrid screen revealed BRAK interacted with phytosulfokine (PSK) receptor PSKR1. PSK-induced growth and defense responses were impaired in pskr1, brak single and double mutants, as well as in PSKR1-overexpressing plants with silenced BRAK. Moreover, BRAK and PSKR1 phosphorylated each other, promoting their interaction as detected by microscale thermophoresis. This reciprocal phosphorylation was crucial for growth and resistance. In summary, we identified BRAK as a novel regulator of seedling growth, fruit yield and defense, offering new possibilities for developing fungal disease-tolerant plants without compromising yield.
Histone modifications and Sp1 promote GPR160 expression in bone cancer pain within rodent models
Authors: Xu Chengfei , Wang Yahui , Ni Chaobo , Xu Miao , Yin Chengyu , He Qiuli , Ma Bing , Fu Jie , Zhao Baoxia , Chen Liping , Zhi Tong , Wei Shirong , Cheng Liang , Xu Hui , Xiao Jiajun , Yang Lei , Xu Qingqing , Kuang Jiao , Liu Boyi , Zhou Qinghe , Lin Xuewu , Yao Ming , Ni Huadong 
Published: October 2024

AbstractBone cancer pain (BCP) affects ~70% of patients in advanced stages, primarily due to bone metastasis, presenting a substantial therapeutic challenge. Here, we profile orphan G protein-coupled receptors in the dorsal root ganglia (DRG) following tumor infiltration, and observe a notable increase in GPR160 expression. Elevated Gpr160 mRNA and protein levels persist from postoperative day 6 for over 18 days in the affected DRG, predominantly in small-diameter C-fiber type neurons specific to the tibia. Targeted interventions, including DRG microinjection of siRNA or AAV delivery, mitigate mechanical allodynia, cold, and heat hyperalgesia induced by the tumor. Tumor infiltration increases DRG neuron excitability in wild-type mice, but not in Gpr160 gene knockout mice. Tumor infiltration results in reduced H3K27me3 and increased H3K27ac modifications, enhanced binding of the transcription activator Sp1 to the Gpr160 gene promoter region, and induction of GPR160 expression. Modulating histone-modifying enzymes effectively alleviated pain behavior. Our study delineates a novel mechanism wherein elevated Sp1 levels facilitate Gpr160 gene transcription in nociceptive DRG neurons during BCP in rodents.
Topological search and gradient descent boosted Runge–Kutta optimiser with application to engineering design and feature selection
Authors: Shi Jinge , Chen Yi , Heidari Ali Asghar , Cai Zhennao , Chen Huiling , Liang Guoxi 
Published: October 2024

AbstractThe Runge–Kutta optimiser (RUN) algorithm, renowned for its powerful optimisation capabilities, faces challenges in dealing with increasing complexity in real‐world problems. Specifically, it shows deficiencies in terms of limited local exploration capabilities and less precise solutions. Therefore, this research aims to integrate the topological search (TS) mechanism with the gradient search rule (GSR) into the framework of RUN, introducing an enhanced algorithm called TGRUN to improve the performance of the original algorithm. The TS mechanism employs a circular topological scheme to conduct a thorough exploration of solution regions surrounding each solution, enabling a careful examination of valuable solution areas and enhancing the algorithm’s effectiveness in local exploration. To prevent the algorithm from becoming trapped in local optima, the GSR also integrates gradient descent principles to direct the algorithm in a wider investigation of the global solution space. This study conducted a serious of experiments on the IEEE CEC2017 comprehensive benchmark function to assess the enhanced effectiveness of TGRUN. Additionally, the evaluation includes real‐world engineering design and feature selection problems serving as an additional test for assessing the optimisation capabilities of the algorithm. The validation outcomes indicate a significant improvement in the optimisation capabilities and solution accuracy of TGRUN.
Design of miniaturized and highly selective frequency selective rasorber based on compact spiral resonator
Authors: Xu Yixuan , Wu Weiwei , Shi Qingzhan , Shi Tongtong , Wang Shaozhi 
Published: October 2024

AbstractA miniaturized, high‐selectivity, wideband A‐T‐A frequency selective rasorber (FSR) based on compact spiral resonators (CSR) is proposed here. The lossy layer of the FSR consists of the CSR and a Jerusalem cross, with four resistors soldered onto the surface. The underlying layer is a bandpass frequency selective surface (FSS) with an extremely narrow slit. The dimensions of the FSR unit are only 0.079 λL × 0.079 λL × 0.078 λL. The extremely narrow‐slitted FSS and CSR together provide a narrowband frequency response, enhancing the selectivity of the FSR. Additionally, a prototype of an FSR was fabricated and tested, achieving results highly consistent with simulations.
Patienten mit Diabetes mellitus und komorbider psychischer Störung –
besteht eine psychotherapeutische Unterversorgung? – Ergebnisse der
DiMPS-Studie
Authors: Röhrig Bonnie , Petrak Frank , Bartel Alina , Hagena Verena , Dieris-Hirche Jan , Meier Juris M. , Herpertz Stephan 
Published: October 2024

Zusammenfassung
Ziel der Studie Diabetes mellitus ist mit einer erhöhten Prävalenz
psychischer Störungen, insbesondere Depressionen, assoziiert. Trotz einer häufig
postulierten psychotherapeutischen Unterversorgung wurde der tatsächliche
Psychotherapiebedarf dieser Patientengruppe bislang kaum untersucht. In dieser
Studie soll die Versorgungslage von Diabetes-Patienten mit psychischen
Komorbiditäten in Deutschland analysiert werden.
Methodik In einem diabetologischen Tertiärzentrum wurden 240 konsekutiv
behandelte Patienten mit Typ-1- oder Typ-2-Diabetes quer- und längsschnittlich
untersucht. Nach einer Screening- und Diagnostikuntersuchung wurden 94 Patienten
mit einer psychischen Komorbidität in die Studie eingeschlossen. Anschließend
trafen die Patienten im Rahmen einer standardisierten partizipativen
Entscheidungsfindung eine Behandlungsentscheidung hinsichtlich einer Behandlung
ihrer psychischen Störung. In der 6-Monats-Katamnese gaben 77 der 94 Patienten
(81,9%) Auskunft über die Umsetzung ihrer Behandlungsentscheidung sowie der
damit verbundenen Hürden.
Ergebnisse 39,2% der untersuchten Patienten mit Diabetes wiesen eine
psychische Störung auf. Von diesen befanden sich bereits 44,2% in medikamentöser
oder psychotherapeutischer Behandlung. Nach Ablauf der sechs Monate konnten
46,8% der Patienten ihre Therapieentscheidungen umsetzen. Nur 7,1% erhielten
trotz ihrer Bemühungen keine Behandlung. Die 6-Monats-Katamnese zeigte eine
signifikante Verringerung der diabetesbezogenen Belastung (PAID; p<0,05) und
ein gesteigertes psychisches Wohlbefinden in allen Untergruppen – unabhängig von
der Initiierung einer Therapie (WHO-5; p<0,05).
Diskussion Entgegen der weitverbreiteten Vorstellung einer
psychotherapeutischen Unterversorgung von psychisch erkrankten Patienten mit
Diabetes, konnte diese Annahme in dieser Untersuchung nicht bestätigt werden.
Schlussfolgerung: Die Gleichsetzung der Häufigkeit psychischer Störungen mit
einem Bedarf an psychotherapeutischer und/oder psychopharmakologischer
Behandlung, ohne die spezifischen Behandlungsbedürfnisse der Patienten zu
berücksichtigen, kann eine Überschätzung des Versorgungsbedarfs zur Folge
haben.
Medicinal Plant Microbiomes: Factors Affecting Bacterial and Fungal Community Composition
Authors: Zagal Daniel , Graham James G. , Bisson Jonathan , Green Stefan J. , Pauli Guido F. 
Published: October 2024

AbstractThis exploratory study was designed to identify factors implicating microbial influence on medicinal plant metabolomes. Utilizing a whole-microbiome approach, amplicon sequencing was used to identify the makeup of fungal and bacterial assemblages from endophytic (interior) and epiphytic (external) environments in two different sets of congeneric host-plant pairs, with collection of multiple samples of two medicinal plant species (Actaea racemosa, Rhodiola rosea) and two generic analogs (Actaea rubra, Rhodiola integrifolia). Diversity analysis of microbial assemblages revealed the influence of three primary factors driving variance in microbial community composition: host-plant taxonomy, the compartmentalization of microbial communities within discrete plant parts, and the scale of distance (microhabitat heterogeneity) between sampling locations. These three factors accounted for ~ 60% of variance within and between investigated microbiomes. Across all our
collections, bacterial populations were more diverse than fungi (per compartment), and microbial density in epiphytic compartments (aerial parts, rhizosphere) were higher than those of endophytes (leaf and root). These comparative data point to key loci associated with variation between congeneric pairs and plant genera, providing insight into the complex and contrasting relationships found within this multi-kingdom coevolutionary relationship. Although reflective of only a limited set of botanical source materials, these data document the richness of a relatively unexplored component of the plant world and highlight the relevance of a whole-microbiome ecology-driven approach to botanical research and directed natural product investigations.
A novel endoscopic artificial intelligence system to assist in the diagnosis of autoimmune gastritis: a multicenter study
Authors: Chen Shurong , Xu Louzhe , Li Ting , Chen Yi , Yan Lingling , Zhang Jie , Zhou Xuefeng , Wang Jiayi , Yan Tianlian , Wang Jinghua , He Xinjue , Ma Han , Zhang Xuequn , Zhu Shenghua , Zhang Yizhen , Xu Chengfu , Gao Jianguo , Ji Xia , Bai Dezhi , Chen Yuan , Chen Hongda , Ke Yini , Li Lan , Yu Chaohui , Mao Xinli 
Published: October 2024

Background Autoimmune gastritis (AIG), distinct from Helicobacter pylori-associated atrophic gastritis (HpAG), is underdiagnosed due to limited awareness. This multicenter study aimed to develop a novel endoscopic artificial intelligence (AI) system for assisting in AIG diagnosis.
Methods Patients diagnosed with AIG, HpAG, or nonatrophic gastritis (NAG), were retrospectively enrolled from six centers. Endoscopic images with relevant demographic and medical data were collected for development of the AI-assisted system based on a multi-site feature fusion model. The diagnostic performance of the AI model was evaluated in internal and external datasets. Endoscopists’ performance with and without AI support was tested and compared using Mann–Whitney U test. Heatmap analysis was performed to interpret AI model outputs.
Results 18 828 endoscopy images from 1070 patients (294 AIG, 386 HpAG, 390 NAG) were collected. On testing datasets, AI identified AIG with 96.9 % sensitivity, 92.2 % specificity, and area under the receiver operating characteristic curve (AUROC) of 0.990 (internal), and 90.3 % sensitivity, 93.1 % specificity, and AUROC of 0.973 (external). The performance of AI (sensitivity 91.3 %) was comparable to that of experts (87.3 %) and significantly outperformed nonexperts (70.0 %; P = 0.01). With AI support, the overall performance of endoscopists was improved (sensitivity 90.3 % [95 %CI 86.0 %–93.2 %] vs. 78.7 % [95 %CI 73.6 %–83.2 %]; P = 0.008). Heatmap analysis revealed consistent focus of AI on atrophic areas.
Conclusions This novel AI system demonstrated expert-level performance in identifying AIG and enhanced the diagnostic ability of endoscopists. Its application could be useful in guiding biopsy sampling and improving early detection of AIG.
Effectiveness of Eupatorium Perfoliatum 30C in Preventing Dengue Fever—A Prospective, Community-Based, Open Label, Parallel Cohort Study in Delhi, India
Authors: Nayak Debadatta , Kaur Lovepreet , Bhalerao Rupali , Nahar Karanpreet , Ram Hanuman , Sharma Pawan , Gupta Ankit , Singh Smita , Khurana Anil , Manchanda Raj Kumar 
Published: October 2024

Abstract
Objective The study was undertaken to evaluate the protective effect of Eupatorium perfoliatum (EP) 30C on the incidence of dengue fever.
Design This study was designed as a prospective, open label, parallel cohort study.
Interventions Participants were enrolled in two medicine cohort (MC) communities and one control cohort (CC) community. Participants in MC who were more than 5 years of age received four medicated globules and those aged between 1 and 5 years received two medicated globules of EP 30C once a week for 10 weeks. Participants in CC received no medical intervention. Both cohorts received information and educational material regarding dengue.
Outcome Measures The primary outcome was incidence of dengue cases based on laboratory confirmation or the clinical definition of dengue as per the case definition notified by the National Vector-Borne Disease Control Program, Government of India, during the 14 weeks of intervention and observation.
Results The analysis included 20,607 participants residing in three slums of Delhi, of which MC and CC included 15,298 and 5,309 participants respectively. The overall protective effect of EP 30C in MC against probable/laboratory-confirmed dengue was 59.59% (95% confidence interval [CI], 50.74 to 66.85, p = 0.0001). The overall protective effect of EP 30C against laboratory-confirmed dengue was 72.78% (95% CI, 54.45 to 83.74, p = 0.0001): 26 cases per 15,298 (0.13 per 1,000 person-weeks) in MC versus 33 cases per 5,309 (0.46 per 1,000 person-weeks) in CC.
Conclusion The use of EP 30C was associated with some protection against probable and laboratory-confirmed dengue.
Impact of Antiphospholipid Syndrome on Reproductive Outcomes: Current Insights and Management Approaches
Authors: He Lauren , Sims Catherine 
Published: October 2024

AbstractAntiphospholipid syndrome (APS) is a disease characterized by the presence of antiphospholipid (aPL) antibodies, thrombosis, and obstetric complications. While patients with APS can have successful pregnancies, many important considerations exist. APS can also cooccur with other systemic autoimmune diseases which can affect pregnancy, particularly systemic lupus erythematosus. This article reviews specific considerations for pregnancy and reproductive health in patients with APS. Similar to other autoimmune diseases, stable or quiescent disease and planning with a rheumatologist and obstetrician prior to conception are vital components of a successful pregnancy. Pregnancy management for patients with aPL antibodies or diagnosis of APS with aspirin and/or anticoagulation depending on disease profile is discussed, as well as the effects of physiologic changes during pregnancy in maternal and fetal outcomes for this population. Given the reproductive span lasts beyond conception through delivery, we include discussions on safe contraception options, the use of assistive reproductive technology, pregnancy termination, menopause, and male fertility. While APS is a relatively rare condition, the effects this disease can have on maternal and fetal outcomes even with available therapies demonstrates the need for more high-quality, evidence-based research.
An increased accuracy laser-induced transient grating spectroscopy analysis method for probing near surface thermal diffusivity with gigahertz frequency instrumentation
Authors: Simmonds M. J. , Založnik A. , Patino M. I. , Baldwin M. J. , Boechler N. 
Published: October 2024

An updated analysis method for laser-induced transient grating spectroscopy measurements of near-surface thermal diffusivity using gigahertz frequency instrumentation is presented. Considering the particular application of characterizing materials with heavy ion damage, prior analysis methods typically assume a very short excitation pulse relative to the relaxation time of the response signal. For longer pulse durations, this can be an increasingly poor assumption with decreasing probing depth. This work presents the application of convolution to update the previous analysis method. As a case study, a 400 ps excitation laser pulse on tungsten with transient grating wavelengths of 1.33–20.0 μm, corresponding to characteristic decay times of 0.633–143 ns, is analyzed. Transient grating response curves from numerical simulations and experimental transient grating spectroscopy data are fit using each analysis method, with and without convolution, and compared. Considerations with regard to the data collection instruments are also detailed.
Dynamics of paramagnetic permanent chains and self-assembled clusters under a rapidly rotating magnetic field
Authors: Hamid Abdelkerim Hassan , Gonzalez-Rodriguez David , Xu Hong , Bécu Lydiane 
Published: October 2024

We study experimentally and theoretically the dynamics of permanent paramagnetic chains and mixed clusters formed by permanent paramagnetic chains and paramagnetic particles under the influence of a time-varying magnetic field. First, we examine the dynamics of permanent chains at high frequencies (∼50 to 1000 Hz). These permanent chains exhibit continuous rotational motion with a frequency several orders of magnitude lower than that of the magnetic field. We develop a theoretical model that accurately describes the dependence of the rotational dynamics of chains on their length, as well as the amplitude and frequency of the external magnetic field in this high frequency regime. Next, we examine how cluster dynamics are affected by the presence of permanent chains. We show that the rotation of clusters composed of a high proportion of permanent chains is slowed down but remains qualitatively well described by the theoretical model we developed for homogeneous clusters of isotropic particles. We propose that the decrease in angular velocity for mixed clusters is due to the hardening of the cluster’s 2D elastic modulus caused by the increase of the steric interaction parameter stemming from the presence of chemical links between particles in the chains.
Mechanical vibration-induced suppression of transverse acoustic phonons in silicon due to Akhiezer damping
Authors: Jin Jae Sik 
Published: October 2024

Thermoelectric modules that utilize waste heat from machinery are inevitably exposed to mechanical vibrations. Here, we investigated the effects of mechanically induced phonon anharmonicity on Akhiezer damping with three different vibrational modes: Lamé, square extensional, and width extensional modes. We showed complete suppression of the transverse acoustic phonons at 300 K or above for the Lamé mode resonator, which is the reason why the mode has a high quality factor. Our results provide a new fundamental understanding of mechanically induced phonon scattering and rationally enable the design of thermoelectric modules to achieve high performance via mechanical vibrations when they are exposed to mechanical motion. Moreover, this should pave the way for studies of oscillatory motion in short-time-scale vibrational resonators.
A multi-scale temporal convolutional capsule network with parameter-free attention module-dynamic routing for intelligent diagnosis of rolling bearing
Authors: Jin Yulin , Hao Liang , He Xinghua , Liu Zhiwen 
Published: October 2024

Abstract
We proposed a multi-scale temporal convolutional capsule network model coupled with a parameter-free attention module and dynamic routing mechanism to analyze complex vibration signals for diagnosing the health of bearings. The proposed method utilizes a capsule network as the fundamental architecture. Instead of a convolutional neural network, a temporal convolutional network is employed. Additionally, a multi-scale feature fusion module is integrated into the capsule network structure to dynamically extract various layers of features from fault samples, enhancing the discriminatory capability of abnormal data. Subsequently, the parameter-free attention module and dynamic routing mechanism are employed to construct digital capsules. This allows the smallest unit capsule in a single layer to carry more information, enhance the similarity between the instance primary capsule and the fault capsule, reduce the interference of irrelevant features to the model, and improve the accuracy of fault type recognition. Finally, a multi-scale temporal convolutional capsule network model that integrates feature extraction and pattern recognition is established to perform end-to-end diagnosis of the bearing. Experimental findings suggest that the proposed method outperforms other deep learning methods in terms of accuracy and robustness. It can provide a theoretical basis and implementation path for the detection and diagnosis of train wheelset bearing time series abnormal data.