bluuebunny/crossref_metadata_2025_split huggingface dataset:
Screening Therapeutic Effects of MSC‐EVs to Acute Lung Injury Model on A Chip
Authors: Chen Weiwei , Zhu Yujuan , Liu Rui , Kong Bin , Xia Nan , Zhao Yuanjin , Sun Lingyun 
Published: December 2023

AbstractAcute lung injury (ALI) is a lethal disease with high mortality rate, and its physiologically relevant models that could mimic human disease processes are urgently needed to study pathophysiology and predict drug efficacy. Here, this work presents a novel lipopolysaccharide (LPS) based ALI model on a microfluidic chip that reconstitutes an air–liquid interface lined by human alveolar epithelium and microvascular endothelium for screening the therapeutic effects of mesenchymal stem cells (MSC) derived extracellular vesicles (MSC‐EVs) to the biomimetic ALI. The air–liquid interface is established by coculture of alveolar epithelium and microvascular endothelium on the opposite sides of the porous membrane. The functionalized architecture is characterized by integrate cell layers and suitable permeability. Using this biomimetic microsystem, LPS based ALI model is established, which exhibits the disrupted alveolar‐capillary barrier, reduced transepithelial/transendothelial electrical resistance (TEER), and impaired expression of junction proteins. As a reliable disease model, this work examines the effects of MSC‐EVs, and the data indicate the therapeutic potential of EVs for severe ALI. MSC‐EVs can alleviate barrier disruption by restoring both the epithelial and endothelial barrier integrity. They hope this study can become a unique approach to study human pathophysiology of ALI and advance drug development.
Novel Ultra‐Stable 2D SbBi Alloy Structure with Precise Regulation Ratio Enables Long‐Stable Potassium/Lithium‐Ion Storage
Authors: Liu Xi , Wang Xinying , Zhou Yiru , Wang Bingchun , Zhao Ligong , Zheng He , Wang Jianbo , Liu Junhao , Liu Jun , Li Yunyong 
Published: December 2023

AbstractThe inferior cycling stabilities or low capacities of 2D Sb or Bi limit their applications in high‐capacity and long‐stability potassium/lithium‐ion batteries (PIBs/LIBs). Therefore, integrating the synergy of high‐capacity Sb and high‐stability Bi to fabricate 2D binary alloys is an intriguing and challenging endeavor. Herein, a series of novel 2D binary SbBi alloys with different atomic ratios are fabricated using a simple one‐step co‐replacement method. Among these fabricated alloys, the 2D‐Sb0.6Bi0.4 anode exhibits high‐capacity and ultra‐stable potassium and lithium storage performance. Particularly, the 2D‐Sb0.6Bi0.4 anode has a high‐stability capacity of 381.1 mAh g−1 after 500 cycles at 0.2 A g−1 (≈87.8% retention) and an ultra‐long‐cycling stability of 1000 cycles (0.037% decay per cycle) at 1.0 A g−1 in PIBs. Besides, the superior lithium and potassium storage mechanism is revealed by kinetic analysis, in‐situ/ex‐situ characterization techniques, and theoretical calculations. This mainly originates from the ultra‐stable structure and synergistic interaction within the 2D‐binary alloy, which significantly alleviates the volume expansion, enhances K+ adsorption energy, and decreases the K+ diffusion energy barrier compared to individual 2D‐Bi or 2D‐Sb. This study verifies a new scalable design strategy for creating 2D binary (even ternary) alloys, offering valuable insights into their fundamental mechanisms in rechargeable batteries.
Progress in Research and Application of Modified Silk Fibroin Fibers
Authors: Chai Shanshan , Wu Hong , Peng Xingjian , Tan Zifang , Cao Hanlin , Wei Liang , Mao Xue , Zhang Zhenfang , Zhou Fenglei , Zhang Qingling , Sun Runjun , Liu Chengkun 
Published: December 2023

AbstractSilk fibroin (SF) is a biodegradable protein and possesses superior skin‐friendliness, biocompatibility, low immunogenicity, and non‐toxicity. However, SF has a series of drawbacks. For example, the application of SF in water filtration is limited by its inadequate ability to adsorb heavy metal ions. It is not inherently antibacterial, making SF ineffective as a filter to eliminate airborne bacteria. SF without conductivity is not suitable for use in sensors and triboelectric nanogenerators. In tissue engineering, deficient mechanical and anti‐inflammatory properties also have an influence on the rate of wound recovery. While physical and chemical modifications will improve its application properties as well as broaden its application areas. This review describes the modification of SF by filling, blending, structural adjustment, post treatment, crosslinking, grafting, and in situ polymerization to provide it with other functional properties. Modified SF fibers prepared by various methods (e.g., wet/dry/microfluidic spinning, electrospinning) are discussed, and they can be used in water/air filtration, chemical/pressure/strain sensors, triboelectric nanogenerators, artificial skin, wound dressings, and tissue scaffolds. Finally, the development trend of the modified SF fibers is prospected. This review has a reference significance on how to use modified SF fibers to improve filtration efficiency, sensor performance, and wound recovery.
Strongly Luminescent Tetradentate Palladium(II)‐TADF Emitters. Blue TADF And TADF‐Sensitized OLEDs with External Quantum Efficiencies Over 23%
Authors: Sit Man‐Ki , Tong Glenna So Ming , Lam Tsz‐Lung , Cheng Gang , Hung Faan‐Fung , So Kwok‐Ming , Du Lili , Choy Kin‐On , Low Kam‐Hung , Che Chi‐Ming 
Published: December 2023

AbstractDue to the low‐lying Pd(4d)‐orbitals, luminescent palladium(II) complexes usually show 3IL phosphorescence (IL = intraligand) with excited state lifetimes in the range of hundreds of microseconds, which limits their application in blue organic light‐emitting diodes (OLEDs). Here, a molecular design strategy for the development of strongly luminescent Pd(II)‐based thermally activated delayed fluorescence (TADF) emitters with fast radiative decay rate constants and reverse intersystem crossing rate (kRISC) constants is presented. The synthesized tetradentate [Pd(N*C*C^N)] TADF emitters show sky‐blue to yellow (λmax = 484–565 nm) emission with excited state lifetimes in the range of 0.9−8.7 µs and high photoluminescence quantum yield of up to 77% in CH2Cl2 solution. In 5 wt.% 2,8‐bis(diphenylphosphoryl)dibenzo[b,d]furan (PPF) thin films, these [Pd(N*C*C^N)] TADF complexes display blue to sky‐blue (476−496 nm) emission with quantum yields close to unity. Variable‐temperature emission lifetime measurements, femtosecond time‐resolved spectroscopy, and density functional theory (DFT) and time‐dependent DFT (TDDFT) calculations together reveal ultrafast kRISC rate constants of these [Pd(N*C*C^N)] TADF emitters. Using these Pd(II)‐TADF emitters as dopants, sky‐blue TADF and blue TADF‐sensitized OLEDs with small efficiency roll‐offs achieved high maximum external quantum efficiencies (EQEs) of 24.8% and 23.1%, respectively.
Quantum Sensing and Light Guiding with Fluorescent Nanodiamond‐Doped PVA Fibers
Authors: Styles Roy , Candini Andrea , Guarino Vincenzo , Robertson Islay , Singh Priya , Cruz‐Maya Iriczalli , Benfenati Valentina , Abraham Amanda N. , Abe Hiroshi , Ohshima Takeshi , Broadway David A. , Greentree Andrew D. , Gibson Brant C. , Ambrosio Luigi , Tetienne Jean‐Philippe , Reineck Philipp 
Published: December 2023

AbstractFluorescent nanodiamonds (FNDs) containing quantum defects enable the optical measurement of electromagnetic fields and temperature and are among the most developed nanoscale quantum sensors today. Yet, for many applications in biomedicine and beyond, FNDs must be integrated into biocompatible substrates that preserve FND sensitivity and bring FNDs within nanoscale distance of their sensing target. At the same time, the high excitation light intensity required for most quantum sensing protocols remains a major challenge for applications in biomedicine. Here, it is shown that FNDs embedded in polyvinyl‐alcohol (PVA) fibers are a powerful 3D platform for nanoscale quantum sensing via light guiding. First, it is demonstrated that biocompatible PVA fibers can guide light to excite FNDs >10 µm from the excitation beam. Using this light‐guiding‐enabled excitation, optically detected magnetic resonance (ODMR) and T1 spin relaxometry measurements are performed using the nitrogen‐vacancy (NV) center in FNDs. Through ODMR thermometry, it is shown that light‐guiding‐enabled excitation mitigates light‐induced heating. Finally, the quantum sensing capability of the platform is established by detecting paramagnetic gadolinium in a dry and aqueous environment using T1 relaxometry of the NV center in FNDs. These results pave the way for light‐guiding‐enabled optical quantum sensing in biomedicine using nanodiamond‐doped biosubstrates.
AR‐Enabled Persistent Human–Machine Interfaces via a Scalable Soft Electrode Array
Authors: Kim Hodam , Cha Ho‐Seung , Kim Minseon , Lee Yoon Jae , Yi Hoon , Lee Sung Hoon , Ira Soltis , Kim Hojoong , Im Chang‐Hwan , Yeo Woon‐Hong 
Published: December 2023

AbstractAugmented reality (AR) is a computer graphics technique that creates a seamless interface between the real and virtual worlds. AR usage rapidly spreads across diverse areas, such as healthcare, education, and entertainment. Despite its immense potential, AR interface controls rely on an external joystick, a smartphone, or a fixed camera system susceptible to lighting. Here, an AR‐integrated soft wearable electronic system that detects the gestures of a subject for more intuitive, accurate, and direct control of external systems is introduced. Specifically, a soft, all‐in‐one wearable device includes a scalable electrode array and integrated wireless system to measure electromyograms for real‐time continuous recognition of hand gestures. An advanced machine learning algorithm embedded in the system enables the classification of ten different classes with an accuracy of 96.08%. Compared to the conventional rigid wearables, the multi‐channel soft wearable system offers an enhanced signal‐to‐noise ratio and consistency over multiple uses due to skin conformality. The demonstration of the AR‐integrated soft wearable system for drone control captures the potential of the platform technology to offer numerous human–machine interface opportunities for users to interact remotely with external hardware and software.
Low Onset‐Potential Z‐Scheme Ta3N5‐based Photoanode with Enhanced Light Harvesting and Charge Transport
Authors: Kwon Hee Ryeong , Yang Jin Wook , Choi Sungkyun , Cheon Woo Seok , Im In Hyuk , Kim Younhwa , Park Jungwon , Lee Gwan‐Hyoung , Jang Ho Won 
Published: December 2023

AbstractSimultaneous enhancement of light harvesting and charge transport in photoelectrochemical (PEC) systems is a major challenge to achieving high solar‐to‐hydrogen efficiency. Here, a Ta3N5‐Si Z‐scheme system is constructed to facilitate charge transport pathways from generation to catalysis, taking advantage of the exquisite bandgap and band position of Ta3N5. The tailored Ta3N5‐Si junction with an NbNx electron mediator effectively establishes a Z‐scheme charge transport and enhances the driving force for water oxidation, reducing the onset potential by an increment in photovoltage. Moreover, the nitrogen‐doped CoFeOx co‐catalyst boosts hole dynamics and kinetics at the surface level, resulting in improved hole extraction for water oxidation catalysis. The synergy between the above strategies cooperatively expedites the charge separation and transport in a Ta3N5 photoanode, which decreases the photocurrent onset potential from 0.69 to 0.27 V versus the reversible hydrogen electrode, a reduction of 420 mV. This result represents one of the lowest onset potentials observed for Ta3N5‐based photoanodes. A systematic approach to enhancing photovoltage and photocurrent expands the design concept of metal nitride‐based PEC devices.
Towards bespoke optimizations of energy efficiency in HPC environments
Authors: Tracey Robert , Elisseev Vadim , Smyrnakis Michalis , Hoang Lan , Fellows Mark , Ackers Michael , Laughton Andrew , Hill Stephen , Folkes Phillip , Whittle John 
Published: December 2023

AbstractWe present bespoke energy efficiency optimizations in high performance computing (HPC) environments using holistic approach to data collection, analysis and proactive management of resources and workloads. Our solution has three major components: (i) platform for collecting, storing and processing data from multiple sources across hardware and software stacks, (ii) collections of regression machine learning (ML) algorithms for making workloads classifications and energy usage predictions, (iii) agent‐based decision‐making framework for delivering control decisions to middle‐ware and infrastructure thus supporting real time or near real energy efficiency optimizations. We will provide some concrete examples of using our proposed approach in HPC environment.
Age at cardiovascular disease onset, dementia risk, and the role of lifestyle factors
Authors: van Gennip April C. E. , van Sloten Thomas T. , Fayosse Aurore , Sabia Séverine , Singh‐Manoux Archana 
Published: December 2023

AbstractINTRODUCTIONWe first examined the role of age at cardiovascular disease (CVD) onset for incident dementia, and then examined whether lifestyle factors at guideline‐recommended levels in individuals with CVD mitigates dementia risk.METHODSWe used population‐based data (Whitehall II: n = 10,308/baseline 1985–1988/examinations every 4–5 years). Lifestyle factors (non‐smoking, body mass index [BMI], physical activity, diet) were extracted post‐CVD.RESULTSOver a median of 31.6 years, 3275 (32.1%) developed CVD. At age 70, risk of dementia was higher in individuals with CVD onset before (hazard ratio [HR] of incident dementia for participants with CVD before age 60, using participants without CVD at age 70 as the reference: 1.56, 95% confidence interal [CI] 1.18–2.08) but not after 60 years. In participants with CVD, a greater number of lifestyle factors at recommended levels post‐CVD was associated with a lower dementia risk (per lifestyle factor at recommended level HR: 0.73, 95% CI 0.59–0.92).DISCUSSIONOur results suggest that early onset CVD is associated with a higher dementia risk at older ages. In those with CVD, the dementia risk was lower if lifestyle factors are at recommended levels following CVD diagnosis.Highlights
CVD in midlife but not in late life is associated with a higher risk of dementia.
Dementia risk in CVD patients is lower if their lifestyle factors are at recommended levels.
These findings provide evidence to promote CVD prevention in midlife or earlier.
Study findings also show the importance of a healthy lifestyle in those with CVD.
Predicting clinical progression trajectories of early Alzheimer's disease patients
Authors: Devanarayan Viswanath , Ye Yuanqing , Charil Arnaud , Andreozzi Erica , Sachdev Pallavi , Llano Daniel A. , Tian Lu , Zhu Liang , Hampel Harald , Kramer Lynn , Dhadda Shobha , Irizarry Michael ,   for the Alzheimer's Disease Neuroimaging Initiative (ADNI)
Published: December 2023

AbstractBACKGROUNDModels for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring.METHODSPrediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures.RESULTSThe model using clinical features achieved R2 of 0.21 and 0.31 for predicting 2‐year cognitive decline in VC 1 and VC 2, respectively. Adding MRI features improved the R2 to 0.29 in VC 1, which employed the same preprocessing pipeline as the TC. Utilizing these model‐based predictions for clinical trial enrichment reduced the required sample size by 20% to 49%.DISCUSSIONOur validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.
Direct Decarboxylation of Trifluoroacetates Enabled by Iron Photocatalysis**
Authors: Fernández‐García Sara , Chantzakou Veronika O. , Juliá‐Hernández Francisco 
Published: December 2023

AbstractTrifluoroacetates are the most abundant and accessible sources of trifluoromethyl groups, which are key components in pharmaceuticals and agrochemicals. The generation of trifluoromethyl reactive radicals from trifluoroacetates requires their decarboxylation, which is hampered by their high oxidation potential. This constitutes a major challenge for redox‐based methods, because of the need to pair the redox potentials with trifluoroacetate. Here we report a strategy based on iron photocatalysis to promote the direct photodecarboxylation of trifluoroacetates that displays reactivity features that escape from redox limitations. Our synthetic design has enabled the use of trifluoroacetates for the trifluoromethylation of more easily oxidizable organic substrates, offering new opportunities for late‐stage derivatization campaigns using chemical feedstocks, Earth‐abundant catalysts, and visible‐light.
Chemical Engineering of Artificial Transcription Factors by Orthogonal Palladium(II)‐Mediated S‐Arylation Reactions
Authors: Lin Xiaoxi , Harel Omer , Jbara Muhammad 
Published: December 2023

AbstractSite‐selective functionalization strategies are in high demand to prepare well‐defined homogeneous proteins for basic research and biomedical applications. In this regard, cysteine‐based reactions have enabled a broad set of transformations to produce modified proteins for various applications. However, these approaches were mainly employed to modify a single reactive site with a specific transformation. Achieving site selectivity or multiple transformations, essential for preparing complex biomolecules, remains challenging. Herein we demonstrate the power of combining palladium(II)‐mediated C−S bond formation and C−S bond cleavage reactions to selectively edit desired cysteine sites in complex and uniquely modified proteins. We developed an orthogonal palladium(II) strategy for rapid and effective diversification of multiple cysteine sites (3–6 residues) with various transformations. Importantly, we employed our approach to prepare 10 complex analogues, including modified, stapled, and multimeric proteins on a milligram scale. Furthermore, we also synthesized a focused library of stabilized artificial transcription factors that displayed enhanced stability and potent DNA binding activity. Our approach enables rapid and effective protein editing and opens new avenues to engineer new biomolecules for fundamental research and therapeutic applications.
Quantitative Construction of Boronic‐Ester Linkages in Covalent Organic Frameworks for the Carbon Dioxide Reduction
Authors: Yang Xiubei , Li Xuewen , Liu Minghao , Yang Shuai , Xu Qing , Zeng Gaofeng 
Published: December 2023

AbstractCovalent organic frameworks (COFs) have been utilized for catalyzing the reduction of carbon dioxide (CO2RR) due to their atomic metal centers and controllable pore channels, which are facilitated by different covalent bonds. However, the exploration of boron‐based linkages in these catalytic COFs has been limited owing to potential instability. Herein, we present the construction of boronic ester‐linked COFs through nucleophilic substitution reactions in order to catalyze the CO2RR. The inclusion of abundant fluorine atoms within the frameworks enhances their hydrophobicity and subsequently improves water tolerance and chemical stability of COFs. The content of boron atoms in the COF linkages was carefully controlled, with COFs featuring a higher density of boron atoms exhibiting increased electronic conductivity, enhanced reductive ability, and stronger binding affinity towards CO2. Consequently, these COFs demonstrate improved activity and selectivity. The optimized COFs achieve the highest activity, achieving a turnover frequency of 1695.3 h−1 and a CO selectivity of 95.0 % at −0.9 V. Operando synchrotron radiation measurements confirm the stability of Co (II) atoms as catalytically active sites. By successfully constructing boronic ester‐linked COFs, we not only address potential instability concerns but also achieve exceptional catalytic performance for CO2RR.
Li6E5Li6: Tetrel Sandwich Complexes with 10‐π‐Electrons
Authors: Inostroza Diego , Leyva‐Parra Luis , Pino‐Rios Ricardo , Solar‐Encinas José , Vásquez‐Espinal Alejandro , Pan Sudip , Merino Gabriel , Yañez Osvaldo , Tiznado William 
Published: December 2023

AbstractWhen (4n +2) π‐electrons are located in single planar ring, it conventionally qualifies as aromatic. According Hückel's rule, systems possessing ten π‐electrons should be aromatic. Herein we report a series of D5h Li6E5Li6 sandwich structures, representing the first global minima featuring ten π‐electrons E510− ring (E=Si−Pb). However, these π‐electrons localize as five π‐lone‐pairs rather than delocalized orbitals. The high symmetry structure achieved is a direct consequence of σ‐aromaticity, particularly favored in elements from Si to Pb, resulting in a pronounced diatropic ring current flow that contributes to the enhanced stability of these systems.
Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes**
Authors: Orsi Markus , Shing Loh Boon , Weng Cheng , Ang Wee Han , Frei Angelo 
Published: December 2023

AbstractRising antimicrobial resistance (AMR) and lack of innovation in the antibiotic pipeline necessitate novel approaches to discovering new drugs. Metal complexes have proven to be promising antimicrobial compounds, but the number of studied compounds is still low compared to the millions of organic molecules investigated so far. Lately, machine learning (ML) has emerged as a valuable tool for guiding the design of small organic molecules, potentially even in low‐data scenarios. For the first time, we extend the application of ML to the discovery of metal‐based medicines. Utilising 288 modularly synthesized ruthenium arene Schiff‐base complexes and their antibacterial properties, a series of ML models were trained. The models perform well and are used to predict the activity of 54 new compounds. These displayed a 5.7x higher hit‐rate (53.7 %) against methicillin‐resistant Staphylococcus aureus (MRSA) compared to the original library (9.4 %), demonstrating that ML can be applied to improve the success‐rates in the search of new metalloantibiotics. This work paves the way for more ambitious applications of ML in the field of metal‐based drug discovery.
Confinement of p‐Xylene in the Pores of a Bilanthanide Metal–Organic Framework for Highly Selective Recognition
Authors: Wang Mengmeng , Han Zongsu , Wang Kunyu , Zhao Bin , Sun Tiankai , Wu Yuewei , Cheng Peng , Shi Wei 
Published: December 2023

AbstractThe rapid and accurate sensing of p‐xylene, an essential raw material with a multi‐billion‐dollar market, in xylene mixture is of great significance in industry; however, the highly similar molecular structures, energy levels, and spectral characteristics of xylene isomers make the selective recognition extremely challenging. Metal–organic frameworks (MOFs) exhibiting tailorable pores and potential binding sites provide prospects for xylene sensing but a comprehensive understanding of the pore effect is still elusive, primarily due to the intricacies involved in the sensing process. Herein, we reported a robust bilanthanide MOF NKU‐999‐EuTb with precisely engineered pores to accommodate p‐xylene, of which the binding sites were confirmed by single crystal X‐ray diffraction and dynamic magnetic susceptibilities. NKU‐999‐EuTb exhibits high‐performance in selective recognition for p‐xylene towards its isomers. Through a systematical study, it was revealed that absorbing p‐xylene into the pores governs the sensing performance. This work provides insights for developing advanced sensing materials for complex isomers.