bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of Hybrid Dendrimers and Their Generations for Modulated Spatio‐Temporal Action
Authors: Kharangate Kalyani , Shende Pravin 
Published: February 2023

AbstractHybrid dendrimers constitute a unique class of well‐defined complex architecture featured with a central domain and bifurcated branches with two different dendritic sequences for their atomic configuration and functional groups at the periphery. This review article pioneers the field of new hybrid dendrimers using different generations by nanoconjugation with metals, carbohydrates, nucleotides, proteins/peptides, carbosilane, urea, silica, stem cells, guanidine, etc. The smart dendrimers contain desirable electrical, magnetic, optical, and biological attributes to increase surface area, monodisperse behavior, dose reduction, dissolution, permeability, long‐term stability, and significant decrement in nanotoxicity studies. The higher encapsulation of lipid soluble and insoluble moieties explores an excellent platform for the delivery of drugs (ibuprofen, indomethacin, etc.), nucleic acids (oligonucleotide, siRNA, and aptamer), genetic materials , and chemical diagnostic agents (gadolinium chelates and superparamagnetic iron oxide particles) for imaging. Owing to their flexibility in structural adaptability, different health conditions like glaucoma, inflammation, microbial infection, neurodegenerative problems (Alzheimer's disease and Parkinsonism), and cancer are benefited using such long‐lasting drug delivery. Advancements in molecular engineering techniques, 3D printing, artificial intelligence, robotic, green synthesis, and microwave‐assisted methods aid in the development of economically reliable and personalized pharmaceutical hybrid dendritic systems resembling antibodies, globular proteins, stem cells, enzymes, and genetic materials.
Variation in clinical practice guidelines for use of palivizumab in preventing severe respiratory syncytial viral (RSV) disease in high‐risk infants
Authors: Stiboy Eunice , Chan Mei , Islam Md Saiful , Saravanos Gemma L. , Lui Kei , Jaffe Adam , Homaira Nusrat 
Published: February 2023

AbstractBackgroundUniformity and compliance with clinical practice guidelines (CPGs) for use of palivizumab in preventing severe respiratory syncytial viral infection in Australian high‐risk infants remain unclear.MethodsAn online survey was conducted across the Australian and New Zealand Neonatal Network (ANZNN) to determine clinical practices around palivizumab. A literature search was also performed to identify and compare national and international guidelines.ResultsA total of 65 of 422 ANZNN members completed the survey. Respondents included 61 senior medical staff of consultants/staff specialists (78%) and four nursing staff (6%). According to the survey, infants most likely to be recommended palivizumab included preterm infants born <29 weeks gestational age (GA) (30%), children with chronic lung diseases (CLDs) born <32 weeks GA (40%), and with hemodynamically significant heart disease (35%). Many of the respondents (53%) stated that CPGs for palivizumab were developed locally.Literature search identified 20 guidelines (10 international and 10 domestic); 16 (80%) recommended palivizumab use in preterm infants, 16 (80%) recommended use in infants with CLD, 17 (85%) in congenital heart disease and 6 (30%) in bronchopulmonary dysplasia (BPD). Eight (40%) guidelines provided specific recommendations for immunocompromised infants. Canada, Western Australia, and American Academy of Paediatrics provided recommendations for Indigenous children. Frequency and dosage of palivizumab was universal across all CPGs. None of the international guidelines obtained were from low‐ or middle‐income countries.ConclusionsStandardization of CPGs may improve clinical decision making around use of palivizumab in high‐risk infants.
Improvements in body mass index of children with cystic fibrosis following implementation of a standardized nutritional algorithm: A quality improvement project
Authors: Gokdemir Yasemin , Eralp Ela Erdem , Ergenekon Almala Pinar , Yegit Cansu Yilmaz , Yanaz Muruvvet , Mursaloglu Hakan , Uzunoglu Burcu , Kocamaz Damla , Tastan Gamze , Filbrun Amy , Enochs Catherine , Bouma Sandra , Iwanicki Courtney , Karakoc Fazilet , Nasr Samya Z. , Karadag Bulent 
Published: February 2023

AbstractBackgroundA collaboration between the University of Michigan (UM) Cystic Fibrosis Center (CFC) and Marmara University (MU) CFC was initiated in MU through conducting Quality Improvement projects (QIP). The global aim was to improve nutritional status of children with CF (cwCF), with a specific aim to increase the mean BMI percentile (BMIp) for cwCF by 10 percentile points in 12 months.MethodsBody mass index (BMI) percentiles of cwCF were categorized as: nutritionally adequate (BMIp ≥ 50%); at risk (BMIp 25%–49%); urgently at risk (BMIp 10%–25%); critically at risk (BMIp < 10%). Appropriate interventions were made according to BMIp category every three months. Forced expiratory volume in one‐second percent predicted (FEV1pp), and health‐related quality of life (HRQoL) were evaluated.ResultsOne hundred and eight‐two cwCF with a mean age of 9.1 ± 4.3 years were included in the project. Baseline BMIp increased from 25.6 to 37.2 at the 12th month (p < 0.001). In the critically at‐risk group BMIp increased from 3.6 to 20.5 (p < 0.001), in the urgently at risk group from 15.9 to 30.8 (p < 0.001), in the at risk group from 37.0 to 44.2 (p < 0.079) and in the nutritionally adequate group the increase was from 66.8 to 69.5 (p < 0.301). FEV1pp also improved significantly, from 81.3 ± 20.6 to 85.9 ± 20.8 (p < 0.001). Physical functioning, eating problems, and respiratory symptoms domains of the HRQoL evaluation improved (p < 0.05).ConclusionThis project has led to significant improvements in BMIp, FEV1pp and HRQoL of cwCF; similar projects could easily be implemented by centers in other developing countries.
Vibrational Spectra of HNIW and its Isotopologues: A Combined Experimental and Computational Study
Authors: Burton Mark A. , Steele Brad A. , Crowhurst Jonathan C. , Racoveanu Ana , Kuo I‐Feng W. , Shaw William L. , Gee Richard H. 
Published: February 2023

AbstractIncorporating isotopically labelled materials in degradation experiments could help unravel the mechanism(s) of decomposition through use of the kinetic isotope effect. Characterizing synthesized isotopologues however requires an understanding of what observable signals are affected by the isotopic substitution. As vibrational spectroscopy can distinguish between isotopologues, it is an ideal characterization technique to evaluate isotopic variants. To this end, the vibrational spectra of HNIW and its deuterated (2H), 13C, 15N (all), 15N (nitro), and 18O isotopologues have been computationally predicted in the gas phase using density functional theory. These results are compared to experimentally measured FTIR/ATR and Raman spectra of both unsubstituted HNIW and 15N‐labeled HNIW in which the six nitro groups were synthetically tagged with 15N atoms (15Nnitro−HNIW). The experimental isotopic frequency shift for the −NO2 asymmetric stretching frequencies agrees with that theoretically calculated (∼35.7 cm−1 vs. 36.5 cm−1, respectively). Furthermore, analysis of the theoretically predicted frequency shifts for all isotopologues suggest the −NO2 bending modes are lower in frequency than previously reported. This assignment is supported by the experimentally measured isotopic shift of ∼10.1 cm−1 for these features (consistent with the predicted shift of ∼13.1 cm−1). This work expands our current understanding of the vibrational modes in HNIW as well as provides a method for future work on similar systems.
Nanoformulations as a strategy to overcome the delivery limitations of cannabinoids
Authors: Reddy T. Srinivasa , Zomer Roby , Mantri Nitin 
Published: February 2023

AbstractMedical cannabis has received significant interest in recent years due to its promising benefits in the management of pain, anxiety, depression and neurological and movement disorders. Specifically, the major phytocannabinoids derived from the cannabis plant such as (−) trans‐Δ9‐tetrahydrocannabinol (THC) and cannabidiol (CBD), have been shown to be responsible for the pharmacological and therapeutic properties. Recently, these phytocannabinoids have also attracted special attention in cancer treatment due to their well‐known palliative benefits in chemotherapy‐induced nausea, vomiting, pain and loss of appetite along with their anticancer activities. Despite the enormous pharmacological benefits, the low aqueous solubility, high instability (susceptibility to extensive first pass metabolism) and poor systemic bioavailability restrict their utilization at clinical perspective. Therefore, drug delivery strategies based on nanotechnology are emerging to improve pharmacokinetic profile and bioavailability of cannabinoids as well as enhance their targeted delivery. Here, we critically review the nano‐formulation systems engineered for overcoming the delivery limitations of native phytocannabinoids including polymeric and lipid‐based nanoparticles (lipid nano capsules (LNCs), nanostructured lipid carriers (NLCs), nanoemulsions (NE) and self‐emulsifying drug delivery systems (SEDDS)), ethosomes and cyclodextrins as well as their therapeutic applications.
Overcoming Non‐Specific Interactions for Efficient Encapsulation of Doxorubicin in Ferritin Nanocages for Targeted Drug Delivery
Authors: Budiarta Made , Roy Sathi , Katenkamp Tobias , Feliu Neus , Beck Tobias 
Published: February 2023

AbstractDue to its beneficial pharmacological properties, ferritin (Ftn) is considered as an interesting drug delivery vehicle to alleviate the cardiotoxicity of doxorubicin (DOX) in chemotherapy. However, the encapsulation of DOX in Ftn suffers from heavy precipitation and low protein recovery yield which limits its full potential. Here, a new DOX encapsulation strategy by cysteine‐maleimide conjugation is proposed. In order to demonstrate that this strategy is more efficient compared to the other approaches, DOX is encapsulated in Ftn variants carrying different surface charges. Furthermore, in contrast to the common belief, this data show that DOX molecules are also found to bind non‐specifically to the surface of Ftn. This can be circumvented by the use of Tris(2‐carboxyethyl)phosphine (TCEP) during encapsulation or by washing with acidic buffer. The biocompatibility studies of the resulting DOX Ftn variants in MCF‐7 and MHS cancer cells shows a complex relationship between the cytotoxicity, the DOX loading and the different surface charges of Ftn. Further investigation on the cell uptake mechanism provides reasonable explanations for the cytotoxicity results and reveals that surface charging of Ftn hinders its transferrin receptor 1 (TfR‐1) mediated cellular uptake in MCF‐7 cells.
Congo Red‐Derived Carbon Dots: Simultaneously as Fluorescence Probe for Protein Aggregates, Inhibitor for Protein Aggregation, and Scavenger of Free Radicals
Authors: Li Qin‐ying , Yu Xu , Li Xi , Bao Li‐na , Zhang Yu , Wang Shi‐lin , Jiang Ming , Huang Kun , Xu Li 
Published: February 2023

AbstractThe pathological aggregation of some proteins is claimed to be highly related to several human diseases, such as β‐amyloid 1–42 (Aβ42) to Alzheimer's disease (AD), islet amyloid polypeptide, and insulin to type 2 diabetes mellitus. Therefore, it is in desperate need to develop effective methods for detection of protein aggregates and inhibition of abnormal aggregation. Herein, to construct all‐in‐one probe with both diagnosis and treatment potentials for protein aggregation diseases, Congo red (CR), a classical staining reagent with red fluorescence signal output for protein aggregates, is deliberately adopted to react with three different reductive carbon sources and ammonium persulfate to generate three CR‐derived carbon dots (CDs). The obtained CDs exhibit the capabilities of turn‐on red fluorescence imaging of protein aggregates, and/or inhibition of protein aggregation as well as scavenging of free radicals. Among them, CA‐CDs, using citric acid as the reductive carbon source, demonstrate the superiority to the other two studied CDs in integrating all of these functions, and particularly exert excellent cytoprotection effect against toxic Aβ42 species, possessing tremendous potential in diagnosis and treatment of AD for future study. The present study paves a new way to develop all‐in‐one CDs for the protein disease research.
Ultra‐High Interfacial Thermal Conductance via Double hBN Encapsulation for Efficient Thermal Management of 2D Electronics
Authors: Ye Fan , Liu Qingchang , Xu Baoxing , Feng Philip X.‐L. , Zhang Xian 
Published: February 2023

AbstractHeat dissipation is a major limitation of high‐performance electronics. This is especially important in emerging nanoelectronic devices consisting of ultra‐thin layers, heterostructures, and interfaces, where enhancement in thermal transport is highly desired. Here, ultra‐high interfacial thermal conductance in encapsulated van der Waals (vdW) heterostructures with single‐layer transition metal dichalcogenides MX2 (MoS2, WSe2, WS2) sandwiched between two hexagonal boron nitride (hBN) layers is reported. Through Raman spectroscopic measurements of suspended and substrate‐supported hBN/MX2/hBN heterostructures with varying laser power and temperature, the out‐of‐plane interfacial thermal conductance in the vertical stack is calibrated. The measured interfacial thermal conductance between MX2 and hBN reaches 74 ± 25 MW m−2 K−1, which is at least ten times higher than the interfacial thermal conductance of MX2 in non‐encapsulation structures. Molecular dynamics (MD) calculations verify and explain the experimental results, suggesting a full encapsulation by hBN layers is accounting for the high interfacial conductance. This ultra‐high interfacial thermal conductance is attributed to the double heat transfer pathways and the clean and tight vdW interface between two crystalline 2D materials. The findings in this study reveal new thermal transport mechanisms in hBN/MX2/hBN structures and shed light on building novel hBN‐encapsulated nanoelectronic devices with enhanced thermal management.
Biofilm Potentiates Cancer‐Promoting Effects of Tumor‐Associated Macrophages in a 3D Multi‐Faceted Tumor Model
Authors: Deng Yanlin , Fu Yatian , Chua Song Lin , Khoo Bee Luan 
Published: February 2023

AbstractComponents of the tumor microenvironment (TME), such as tumor‐associated macrophages (TAMs), influence tumor progression. The specific polarization and phenotypic transition of TAMs in the tumor microenvironment lead to two‐pronged impacts that can promote or hinder cancer development and treatment. Here, a novel microfluidic multi‐faceted bladder tumor model (TAMPIEB) is developed incorporating TAMs and cancer cells to evaluate the impact of bacterial distribution on immunomodulation within the tumor microenvironment in vivo. It is demonstrated for the first time that biofilm‐induced inflammatory conditions within tumors promote the transition of macrophages from a pro‐inflammatory M1‐like to an anti‐inflammatory/pro‐tumor M2‐like state. Consequently, multiple roles and mechanisms by which biofilms promote cancer by inducing pro‐tumor phenotypic switch of TAMs are identified, including cancer hallmarks such as reducing susceptibility to apoptosis, enhancing cell viability, and promoting epithelial‐mesenchymal transition and metastasis. Furthermore, biofilms formed by extratumoral bacteria can shield tumors from immune attack by TAMs, which can be visualized through various imaging assays in situ. The study sheds light on the underlying mechanism of biofilm‐mediated inflammation on tumor progression and provides new insights into combined anti‐biofilm therapy and immunotherapy strategies in clinical trials.
Superior Energy Storage Properties and Optical Transparency in K0.5Na0.5NbO3‐Based Dielectric Ceramics via Multiple Synergistic Strategies
Authors: Chai Qizhen , Zhang Fudong , Zhou Qiyuan , Peng Zhanhui , Wu Di , Liang Pengfei , Wei Lingling , Chao Xiaolian , Yang Zupei 
Published: February 2023

AbstractEco‐friendly transparent dielectric ceramics with superior energy storage properties are highly desirable in various transparent energy‐storage electronic devices, ranging from advanced transparent pulse capacitors to electro‐optical multifunctional devices. However, the collaborative improvement of energy storage properties and optical transparency in KNN‐based ceramics still remains challenging. To address this issue, multiple synergistic strategies are proposed, such as refining the grain size, introducing polar nanoregions, and inducing a high‐symmetry phase structure. Accordingly, outstanding energy storage density (Wtotal ≈7.5 J cm−3, Wrec ≈5.3 J cm−3) and optical transmittance (≈76% at 1600 nm, ≈62% at 780 nm) are simultaneously realized in the 0.94(K0.5Na0.5)NbO3‐0.06Sr0.7La0.2ZrO3 ceramic, together with satisfactory charge‐discharge performances (discharge energy density: ≈2.7 J cm−3, power density: ≈243 MW cm−3, discharge rate: ≈76 ns), surpassing previously reported KNN‐based transparent ceramics. Piezoresponse force microscopy and transmission electron microscopy revealed that this excellent performance can be attributed to the nanoscale domain and submicron‐scale grain size. The significant improvement in the optical transparency and energy storage properties of the materials resulted in the widening of the application prospects of the materials.
The update of self‐identity: Importance of assessing autobiographical memory in major depressive disorder
Authors: Bulteau Samuel , Malo Roman , Holland Zoé , Laurin Andrew , Sauvaget Anne 
Published: February 2023

AbstractMajor depressive disorder is a leading global cause of disability. There is a growing interest for memory in mood disorders since it might constitute an original tool for prevention, diagnosis, and treatment. MDD is associated with impaired autobiographical memory characterized by a tendency to overgeneral memory, rather than vivid episodic self‐defining memory, which is mandatory for problem‐solving and projection in the future. This memory bias is maintained by three mechanisms: ruminations, avoidance, and impaired executive control. If we adopt a broader and comprehensive perspective, we can hypothesize that all those alterations have the potential to impair self‐identity updating. We posit that this update requires a double referencing process: (1) to internalized self‐representation and (2) to an externalized framework dealing with the representation of the consequence of actions. Diagnostic and therapeutic implications are discussed in the light of this model and the importance of assessing autobiographical memory in MDD is highlighted.This article is categorized under:
Psychology > Memory
Psychology > Brain Function and Dysfunction
Neuroscience > Clinical
Multicriticality in Yang-Lee edge singularity
Authors: Lencsés Máté , Miscioscia Alessio , Mussardo Giuseppe , Takács Gábor 
Published: February 2023

Abstract
In this paper we study the non-unitary deformations of the two-dimensional Tricritical Ising Model obtained by coupling its two spin ℤ2 odd operators to imaginary magnetic fields. Varying the strengths of these imaginary magnetic fields and adjusting correspondingly the coupling constants of the two spin ℤ2 even fields, we establish the presence of two universality classes of infrared fixed points on the critical surface. The first class corresponds to the familiar Yang-Lee edge singularity, while the second class to its tricritical version. We argue that these two universality classes are controlled by the conformal non-unitary minimal models $$ \mathcal{M} $$
M
(2, 5) and $$ \mathcal{M} $$
M
(2, 7) respectively, which is supported by considerations based on PT symmetry and the corresponding extension of Zamolodchikov’s c-theorem, and also verified numerically using the truncated conformal space approach. Our results are in agreement with a previous numerical study of the lattice version of the Tricritical Ising Model [1]. We also conjecture the classes of universality corresponding to higher non-unitary multicritical points obtained by perturbing the conformal unitary models with imaginary coupling magnetic fields.
QFT approach to dressed particle processes in preheating and non-perturbative mechanism in kinematically-forbidden regime
Authors: Taya Hidetoshi , Yamada Yusuke 
Published: February 2023

Abstract
We provide a quantum-field theoretic formulation of dressed particle dynamics that systematically includes particle production and scattering/decay processes in the preheating era. Our approach is based on the so-called perturbation theory in the Furry picture, in which coherent background fields (i.e., inflaton and the expanding Universe) are treated non-perturbatively whereas interactions between dressed particles are taken into account perturbatively. As an application, we consider the instant preheating mechanism and compute the number of produced particles explicitly. We find a novel non-perturbative particle-production mechanism, which is kinematically forbidden within the conventional perturbative calculation and gives the dominant contribution in certain parameter regimes, e.g., light daughter particles.
Novel black holes in higher derivative gravity
Authors: Huang Yang , Liu Dao-Jun , Zhang Hongsheng 
Published: February 2023

Abstract
We find a class of novel black holes in higher derivative theory. The novel black holes follow behavior of Schwarzschild ones at large mass limit, while dramatically differentiate from Schwarzschild ones for little holes because of the effects which may root in quantum gravity. The temperature of the hole takes maximum for a specific mass, which is related to the new sale introduced in the higher derivative theory, and goes to zero at little mass limit. This property leads to a significant observation that the novel black hole may be a candidate for dark matters evading constraint from γ-ray burst.
Discriminative feature learning through feature distance loss
Authors: Schlagenhauf Tobias , Lin Yiwen , Noack Benjamin 
Published: February 2023

AbstractEnsembles of convolutional neural networks have shown remarkable results in learning discriminative semantic features for image classification tasks. However, the models in the ensemble often concentrate on similar regions in images. This work proposes a novel method that forces a set of base models to learn different features for a classification task. These models are combined in an ensemble to make a collective classification. The key finding is that by forcing the models to concentrate on different features, the classification accuracy is increased. To learn different feature concepts, a so-called feature distance loss is implemented on the feature maps. The experiments on benchmark convolutional neural networks (VGG16, ResNet, AlexNet), popular datasets (Cifar10, Cifar100, miniImageNet, NEU, BSD, TEX), and different training samples (3, 5, 10, 20, 50, 100 per class) show the effectiveness of the proposed feature loss. The proposed method outperforms classical ensemble versions of the base models. The Class Activation Maps explicitly prove the ability to learn different feature concepts. The code is available at: https://github.com/2Obe/Feature-Distance-Loss.git.