bluuebunny/crossref_metadata_2025 huggingface dataset:
Separation method of semifixed variables together with integral bifurcation method for solving generalized time‐fractional thin‐film equations
Authors: Rui Weiguo , He Weijun
Published: April 2024

It is well known that investigation on exact solutions of nonlinear fractional partial differential equations (PDEs) is a very difficult work compared with integer‐order nonlinear PDEs. In this paper, based on the separation method of semifixed variables and integral bifurcation method, a combinational method is proposed. By using this new method, a class of generalized time‐fractional thin‐film equations are studied. Under two kinds of definitions of fractional derivatives, exact solutions of two generalized time‐fractional thin‐film equations are investigated respectively. Different kinds of exact solutions are obtained and their dynamic properties are discussed. Compared to the results in the existing references, the types of solutions obtained in this paper are abundant and very different from those in the existing references. Investigation shows that the solutions of the model defined by Riemann–Liouville differential operator converge faster than those defined by Caputo differential operator. It is also found that the profiles of some solutions are very similar to solitons, but they are not true soliton solutions. In order to visually show the dynamic properties of these solutions, the profiles of some representative exact solutions are illustrated by 3D graphs.
Debamestrocel multimodal effects on biomarker pathways in amyotrophic lateral sclerosis are linked to clinical outcomes
Authors: Lindborg Stacy R. , Goyal Namita A. , Katz Jonathan , Burford Matthew , Li Jenny , Kaspi Haggai , Abramov Natalie , Boulanger Bruno , Berry James D. , Nicholson Katharine , Mozaffar Tahseen , Miller Robert , Jenkins Liberty , Baloh Robert H. , Lewis Richard , Staff Nathan P. , Owegi Margaret Ayo , Dagher Bob , Blondheim‐Shraga Netta R. , Gothelf Yael , Levy Yossef S. , Kern Ralph , Aricha Revital , Windebank Anthony J. , Bowser Robert , Brown Robert H. , Cudkowicz Merit E.
Published: April 2024

Introduction/Aims

Biomarkers have shown promise in amyotrophic lateral sclerosis (ALS) research, but the quest for reliable biomarkers remains active. This study evaluates the effect of debamestrocel on cerebrospinal fluid (CSF) biomarkers, an exploratory endpoint.

Methods

A total of 196 participants randomly received debamestrocel or placebo. Seven CSF samples were to be collected from all participants. Forty‐five biomarkers were analyzed in the overall study and by two subgroups characterized by the ALS Functional Rating Scale‐Revised (ALSFRS‐R). A prespecified model was employed to predict clinical outcomes leveraging biomarkers and disease characteristics. Causal inference was used to analyze relationships between neurofilament light chain (NfL) and ALSFRS‐R.

Results

We observed significant changes with debamestrocel in 64% of the biomarkers studied, spanning pathways implicated in ALS pathology (63% neuroinflammation, 50% neurodegeneration, and 89% neuroprotection). Biomarker changes with debamestrocel show biological activity in trial participants, including those with advanced ALS. CSF biomarkers were predictive of clinical outcomes in debamestrocel‐treated participants (baseline NfL, baseline latency‐associated peptide/transforming growth factor beta1 [LAP/TGFβ1], change galectin‐1, all p < .01), with baseline NfL and LAP/TGFβ1 remaining (p < .05) when disease characteristics (p < .005) were incorporated. Change from baseline to the last measurement showed debamestrocel‐driven reductions in NfL were associated with less decline in ALSFRS‐R. Debamestrocel significantly reduced NfL from baseline compared with placebo (11% vs. 1.6%, p = .037).

Discussion

Following debamestrocel treatment, many biomarkers showed increases (anti‐inflammatory/neuroprotective) or decreases (inflammatory/neurodegenerative) suggesting a possible treatment effect. Neuroinflammatory and neuroprotective biomarkers were predictive of clinical response, suggesting a potential multimodal mechanism of action. These results offer preliminary insights that need to be confirmed.
Extension of the a posteriori finite element method (APFEM) to geometrical alterations and application to stochastic homogenisation
Authors: Ammouche Yanis , Jérusalem Antoine
Published: April 2024

We recently proposed an efficient method facilitating the parametric study of a finite element mechanical simulation as a postprocessing step, that is, without the need to run multiple simulations: the a posteriori finite element method (APFEM). APFEM only requires the knowledge of the vertices of the parameter space and is able to predict accurately how the degrees of freedom of a simulation, i.e., nodal displacements, and other outputs of interests, for example, element stress tensors, evolve when simulation parameters vary within their predefined ranges. In our previous work, these parameters were restricted to material properties and loading conditions. Here, we extend the APFEM to additionally account for changes in the original geometry. This is achieved by defining an intermediary reference frame whose mapping is defined stochastically in the weak form. Subsequent deformation is then reached by correcting for this stochastic variation in the reference frame through multiplicative decomposition of the deformation gradient tensor. The resulting framework is shown here to provide accurate mechanical predictions for relevant applications of increasing complexity: (i) quantifying the stress concentration factor of a plate under uniaxial loading with one and two elliptical holes of varying eccentricities, and (ii) performing the stochastic homogenisation of a composite plate with uncertain mechanical properties and geometry inclusion. This extension of APFEM completes our original approach to account parametrically for geometrical alterations, in addition to boundary conditions and material properties. The advantages of this approach in our original work in terms of stochastic prediction, uncertainty quantification, structural and material optimisation and Bayesian inferences are all naturally conserved.
Forecasting wind power using Optimized Recurrent Neural Network strategy with time‐series data
Authors: Kumar Krishan , Prabhakar Priti , Verma Avnesh
Published: April 2024

Fuel prices are rising, bringing attention to the utilization of alternative energy sources (RES). Even though load forecasting is more accurate at making predictions than wind power forecasting is. To address the operational challenges with the supply of electricity, wind energy forecasts remain essential. A certain kind of technology has recently been applied to forecast wind energy. On wind farms, a variety of wind power forecasting methods have been developed and used. The main idea underlying recurrent networks is parameter sharing across the multiple layers and neurons, which results in cycles in the network's graph sequence. Recurrent networks are designed to process sequential input. A novel hybrid optimization‐based RNN model for wind power forecasting is proposed in this research. Using the SpCro algorithm, a proposed optimization method, the RNN's weights are adjusted. The Crow Search Optimization (CSA) algorithm and the Sparrow search algorithm are combined to form the SpCro Algorithm (SSA). The suggested Algorithm was developed using the crow's memory traits and the sparrow's detecting traits. The proposed system is simulated in MATLAB, and the usefulness of the suggested approach is verified by comparison with other widely used approaches, such as CNN and DNN, in terms of error metrics. Accordingly, the MAE of the proposed method is 45%, 10.02%, 10.04%, 33.58%, 94.81%, and 10.01% higher than RNN, SOA+RNN, CSO+RNN, SSA+DELM, CFU‐COA, and GWO+RNN method.
Preference Phenotypes in Thyroid Nodule Management: A Patient Segmentation Approach
Authors: Naunheim Matthew R. , Wasserman Isaac , von Sneidern Manuela R. , Huston Molly N. , Randolph Gregory W. , Shrime Mark G.
Published: April 2024

Objective

Patient preferences regarding thyroid nodules are poorly understood. Our objective is to (1) employ a discrete choice experiment (DCE) to explore risk tradeoffs in thyroid nodule management, and (2) segment respondents into preference phenotypes.

Study Design

DCE.

Setting

Thyroid surgery clinic, online survey.

Methods

A DCE including 5 attributes (cancer risk, voice concerns, incision/scar, medication requirement, follow‐up frequency) was refined with qualitative patient and physician input. A final DCE including 8 choice tasks, demographics, history, and risk tolerance was administered to participants with and without thyroid disease. Analysis was performed with multinomial logit modeling and latent class analysis (LCA) for preference phenotyping.

Results

A total of 1026 respondents were included; 480 had thyroid disease. Risk aversion was associated with increasing age (P < .001), female gender (P < .001), and limited education (P = .038), but not previous thyroid disease. Cancer risk most significantly impacted decision‐making. Of the total possible utility change from thyroid nodule decision‐making, 47.8% was attributable to variations in cancer risk; 20.0% from medication management; 14.9% from voice changes; 12.7% from incision/scar; and 4.6% from follow‐up concerns. LCA demonstrated 3 classes with distinct preference phenotypes: the largest group (64.2%) made decisions primarily based on cancer risk; another group (18.2%) chose based on aversion to medication; the smallest group (17.7%) factored in medication and cancer risk evenly.

Conclusion

Cancer risk and the need to take medication after thyroid surgery factor into patient decision‐making most heavily when treating thyroid nodules. Distinct preference phenotypes were demonstrated, reinforcing the need for individual preference assessment before the treatment of thyroid disorders.
A multiscale scheme for homogenization to characterize the flexural performances of injection molded short glass fiber reinforced polyether ether ketone composites
Authors: Zhan Zhangjie , Wu Wanxia , Zhao Jian , Guo Yuting , Su Dongxiao , Ge Yuzhou
Published: April 2024

The characterization of the flexural performances of short glass fiber reinforced polyether‐ether‐ketone (SGFR‐PEEK) composites fabricated by injection molding is a crucial and challenging task due to the process‐induced fiber orientation at different locations, resulting layered shell‐core‐shell microstructures and exhibiting large variations in mechanical performances. This article proposes a method for predicting the bending performance of SGFR‐PEEK and indicates the influence of fiber orientation on its bending behavior. This article reports a new scheme that combines multiscale homogenization with periodic microstructures and presents an experimental investigation of the flexural properties of SGFR‐PEEK composites. The distributions of fiber orientation through the thickness extracted from the micro‐computed tomography (μCT) were analyzed and reproduced with a layered skin‐shell‐core structure along the thickness at meso‐scale finite element model within representative volume elements (RVEs) of the macroscopic composites. Then, the effective properties of the RVEs were predicted using the homogenization method with the periodic boundary condition. The elastic modulus of skin‐shell‐core layers in the direction of flow are 4260.51, 4541.27, 4628.52, and 4630.84 MPa, respectively. The classical laminate theory (CLT) and the second homogenization implementation were then utilized in conjunction with the obtained mechanical properties of RVEs to predict the effective macrostructural behavior. The flexural modulus of the composite material was determined to be 5448.7 MPa through a three‐point bending test. The results obtained through lamination plate reinforcement theory and finite element simulation were 5887.4 and 5785.9 MPa, respectively, showing good agreement with the experimental findings. It is shown that the proposed multiscale scheme yields satisfactory agreement with experimental measurements. In addition, the effect of layered skin‐shell‐core microstructures on the flexural behavior was discussed.

Highlights

RVEs of layered shell‐core‐shell microstructures were generated with specified fiber orientations.

The homogenization scheme with the periodic boundary condition was adopted to accurately predict each layer mechanical properties.

The proposed multiscale scheme was compared with experimental results and yielded satisfactory predictions.

The effect of layered skin‐shell‐core microstructures on the flexural behavior was thoroughly studied by the multiscale analytical approach.
Proteasome‐dependent degradation of histone H1 subtypes is mediated by its C‐terminal domain
Authors: García‐Gomis D. , López J. , Calderón A. , Andrés M. , Ponte I. , Roque A.
Published: April 2024

Histone H1 is involved in chromatin compaction and dynamics. In human cells, the H1 complement is formed by different amounts of somatic H1 subtypes, H1.0‐H1.5 and H1X. The amount of each variant depends on the cell type, the cell cycle phase, and the time of development and can be altered in disease. However, the mechanisms regulating H1 protein levels have not been described. We have analyzed the contribution of the proteasome to the degradation of H1 subtypes in human cells using two different inhibitors: MG132 and bortezomib. H1 subtypes accumulate upon treatment with both drugs, indicating that the proteasome is involved in the regulation of H1 protein levels. Proteasome inhibition caused a global increase in cytoplasmatic H1, with slight changes in the composition of H1 bound to chromatin and chromatin accessibility and no alterations in the nucleosome repeat length. The analysis of the proteasome degradation pathway showed that H1 degradation is ubiquitin‐independent. The whole protein and its C‐terminal domain can be degraded directly by the 20S proteasome in vitro. Partial depletion of PA28γ revealed that this regulatory subunit contributes to H1 degradation within the cell. Our study shows that histone H1 protein levels are under tight regulation to prevent its accumulation in the nucleus. We revealed a new regulatory mechanism for histone H1 degradation, where the C‐terminal disordered domain is responsible for its targeting and degradation by the 20S proteasome, a process enhanced by the regulatory subunit PA28γ.
Diverse crystalline protein scaffolds through metal‐dependent polymorphism
Authors: Liutkus Mantas , Sasselli Ivan R. , Rojas Adriana L. , Cortajarena Aitziber L.
Published: April 2024

As protein crystals are increasingly finding diverse applications as scaffolds, controlled crystal polymorphism presents a facile strategy to form crystalline assemblies with controllable porosity with minimal to no protein engineering. Polymorphs of consensus tetratricopeptide repeat proteins with varying porosity were obtained through co‐crystallization with metal salts, exploiting the innate metal ion geometric requirements. A single structurally exposed negative amino acid cluster was responsible for metal coordination, despite the abundance of negatively charged residues. Density functional theory calculations showed that while most of the crystals were the most thermodynamically stable assemblies, some were kinetically trapped states. Thus, crystalline porosity diversity is achieved and controlled with metal coordination, opening a new scope in the application of proteins as biocompatible protein‐metal‐organic frameworks (POFs). In addition, metal‐dependent polymorphic crystals allow direct comparison of metal coordination preferences.
Computational and experimental identification of keystone interactions in Ebola virus matrix protein VP40 dimer formation
Authors: Narkhede Yogesh , Saxena Roopashi , Sharma Tej , Conarty Jacob P. , Ramirez Valentina Toro , Motsa Balindile B. , Amiar Souad , Li Sheng , Chapagain Prem P. , Wiest Olaf , Stahelin Robert V.
Published: April 2024

The Ebola virus (EBOV) is a lipid‐enveloped virus with a negative sense RNA genome that can cause severe and often fatal viral hemorrhagic fever. The assembly and budding of EBOV is regulated by the matrix protein, VP40, which is a peripheral protein that associates with anionic lipids at the inner leaflet of the plasma membrane. VP40 is sufficient to form virus‐like particles (VLPs) from cells, which are nearly indistinguishable from authentic virions. Due to the restrictions of studying EBOV in BSL‐4 facilities, VP40 has served as a surrogate in cellular studies to examine the EBOV assembly and budding process from the host cell plasma membrane. VP40 is a dimer where inhibition of dimer formation halts budding and formation of new VLPs as well as VP40 localization to the plasma membrane inner leaflet. To better understand VP40 dimer stability and critical amino acids to VP40 dimer formation, we integrated computational approaches with experimental validation. Site saturation/alanine scanning calculation, combined with molecular mechanics‐based generalized Born with Poisson‐Boltzmann surface area (MM‐GB/PBSA) method and molecular dynamics simulations were used to predict the energetic contribution of amino acids to VP40 dimer stability and the hydrogen bonding network across the dimer interface. These studies revealed several previously unknown interactions and critical residues predicted to impact VP40 dimer formation. In vitro and cellular studies were then pursued for a subset of VP40 mutations demonstrating reduction in dimer formation (in vitro) or plasma membrane localization (in cells). Together, the computational and experimental approaches revealed critical residues for VP40 dimer stability in an alpha‐helical interface (between residues 106–117) as well as in a loop region (between residues 52–61) below this alpha‐helical region. This study sheds light on the structural origins of VP40 dimer formation and may inform the design of a small molecule that can disrupt VP40 dimer stability.
Optimal maintenance policy considering imperfect switching for a multi‐state warm standby system
Authors: Qi Fa‐Qun , Wang Yun‐Ke , Huang Hong‐Zhong
Published: April 2024

A novel maintenance policy for a two‐component warm standby system with multiple standby states is presented in this paper. Two standby states, that is, cold and warm standby, for components in the system are considered. Components can realize the transition from the cold standby to the warm standby state by periodic switching, intended to shorten recovery time and save system operating costs. Preventive maintenance (PM) and preventive switching (PS) of components are considered. In the PS strategy, the standby component can switch before the operating component fails. In addition, additional standby failure modes based on idle time are studied. Derive the long‐term average cost of the system through the semi‐regenerative process. A numerical example eventually verifies the feasibility of this paper's proposed maintenance and switching strategy.
Monitoring covariance in multivariate time series: Comparing machine learning and statistical approaches
Authors: Weix Derek , Cath Tzahi Y. , Hering Amanda S.
Published: April 2024

In complex systems with multiple variables monitored at high‐frequency, variables are not only temporally autocorrelated, but they may also be nonlinearly related or exhibit nonstationarity as the inputs or operation changes. One approach to handling such variables is to detrend them prior to monitoring and then apply control charts that assume independence and stationarity to the residuals. Monitoring controlled systems is even more challenging because the control strategy seeks to maintain variables at prespecified mean levels, and to compensate, correlations among variables may change, making monitoring the covariance essential. In this paper, a vector autoregressive model (VAR) is compared with a multivariate random forest (MRF) and a neural network (NN) for detrending multivariate time series prior to monitoring the covariance of the residuals using a multivariate exponentially weighted moving average (MEWMA) control chart. Machine learning models have an advantage when the data's structure is unknown or may change. We design a novel simulation study with nonlinear, nonstationary, and autocorrelated data to compare the different detrending models and subsequent covariance monitoring. The machine learning models have superior performance for nonlinear and strongly autocorrelated data and similar performance for linear data. An illustration with data from a reverse osmosis process is given.
Procedures from samples to sulfur isotopic data: A review
Authors: Zhao Changqiu , Guo Qingjun , Zhang Tonggang , Han Xiaokun , Usman Dawuda
Published: April 2024

Rationale

Sulfur isotopes have been widely used to solve some key scientific questions, especially in the last two decades with advanced instruments and analytical schemes. Different sulfur speciation and multiple isotopes analyzed in laboratories worldwide and in situ microanalysis have also been reported in many articles. However, methods of sampling to measurements are multifarious, and occasionally some inaccuracies are present in published papers. Vague methods may mislead newcomers to the field, puzzle readers, or lead to incorrect data‐based correlations.

Methods

We have reviewed multiple methods on sulfur isotopic analyses from the perspectives of sampling, laboratory work, and instrumental analysis in order to help reduce operational inhomogeneity and ensure the fidelity of sulfur isotopic data. We do not deem our proposed solutions as the ultimate standard methods but as a lead‐in to the overall introduction and summary of the current methods used.

Results

It has been shown that external contamination and transformation of different sulfur species should be avoided during the sampling, pretreatment, storage, and chemical treatment processes. Conversion rates and sulfur isotopic fractionations during sulfur extraction, purification, and conversion processes must be verified by researchers using standard or known samples. The unification of absence of isotopic fractionation is needed during all steps, and long‐term monitoring of standard samples is recommended.

Conclusion

This review compiles more details on different methods in sampling, laboratory operation, and measurement of sulfur isotopes, which is beneficial for researchers' better practice in laboratories. Microanalyses and molecular studies are the frontier techniques that compare the bulk sample with the elemental analysis/continuous flow–gas source stable isotope ratio mass spectrometry method, but the latter is widely used. The development of sulfur isotopic measurements will lead to the innovation in scientific issues with sulfur proxies.
Analytical method development, identification, and characterization of stress degradation products of idelalisib by ultrahigh‐performance liquid chromatography with photodiode array and ultrahigh‐performance liquid chromatography with electrospray ionization quadrupole time‐of‐flight mass spectrometry studies
Authors: Mahesh Marella , Bali Alka , Gupta Tanvi
Published: April 2024

Rationale

As per International Council for Harmonization (ICH) drug stability test guideline Q1A(R2), inherent stability characteristics of a drug should be studied. This work was designed to investigate inherent degradation characteristics of the drug idelalisib under ICH prescribed stress conditions, identify its degradation products, and postulate their corresponding degradation pathways.

Methods

Idelalisib was subjected to the ICH prescribed conditions of hydrolytic (neutral, acidic, and alkaline), photolytic, oxidative, and thermal stress according to ICH guideline Q1A(R2). An ultrahigh‐performance liquid chromatography with photodiode array (UHPLC‐PDA) method was developed to adequately resolve the drug from its degradation products, validated as per the ICH guidelines, and subsequently extended to UHPLC with electrospray ionization quadrupole time‐of‐flight mass spectrometry (ESI‐QTOFMS) studies to identify the degradation products.

Results

Significant degradation was noted under conditions of acidic/alkaline hydrolysis, acid photolysis, and oxidative stress. The UHPLC/ESI‐QTOFMS studies revealed the generation of four degradation products (I–IV), which were satisfactorily resolved from the drug by UHPLC on a Kinetex® C18 (100 × 4.6 mm; 2.6 μm) column by the developed isocratic elution method. Detection wavelength was selected as 270 nm. All the degradation products (I–IV) could be identified and characterized from their mass spectral data. The degradation pathways for the generation of various products from the drug were postulated.

Conclusions

A UHPLC‐PDA method was developed and validated for idelalisib. Four degradation products of idelalisib were revealed through UHPLC/ESI‐QTOFMS studies, and corresponding degradation pathways were postulated for the same.
Competitive segregation to grain boundaries between Cr and Co in FeNiCrCo alloy
Authors: Zhang Weiwei , Huang Li , Liang Jing , Li Yanchao , Bai Wei , Jiao Benqi , Kan Dongxiao , Li Jianfeng , Zhang Wen
Published: April 2024

Alloying elements segregating to grain boundaries (GBs) is vital in determining structural stability and mechanical properties of alloys, especially in high‐entropy alloys (HEAs) that consist of multiple elements. However, some details remain unclear, such as the process of varied atoms (Cr and Co) cosegregation to GBs in FeNiCrCo alloy. Therefore, the competition and cooperation between Fe, Ni, Cr, and Co atoms segregating to GBs of FeNiCrCo alloy were investigated via molecular dynamic (MD) simulation. Five [110] symmetric tilt GBs of FeNiCrCo were applied to study the relation between the tendency of atomic segregation especially Cr and Co and GB characters including GB energy and GB excess free volume (GB excess volume). A competitive segregation phenomenon between Cr and Co atoms was discovered, which could be dominated by GB excess volume and different atomic radii among components.
Nanochannel Stability of Chemically Converted Graphene Oxide Membranes
Authors: Zhou Siyu , Guan Kecheng , Li Zhan , Xu Ping , Fang Shang , Zhang Aiwen , Wang Zheng , He Shengnan , Nakagawa Keizo , Matsuyama Hideto
Published: April 2024

Chemically converted graphene oxide laminate membranes, which exhibit stable interlayered nanochannels in aqueous environments, are receiving increasing attention owing to their potential for selective water and ion permeation. However, how the molecular properties of conversion agents influence the stabilization of nanochannels and how effectively nanochannels are stabilized have rarely been studied. In this study, mono‐, di‐, and tri‐saccharide molecules of glucose (Glu), maltose (Glu2), and maltotriose (Glu3) are utilized, respectively, to chemically modify graphene oxide (GO). The aim is to create nanochannels with different levels of stability and investigate how these functional conversion agents affect the separation performance. The effects of the property differences between different conversion agents on nanochannel stabilization are demonstrated. An agent with efficient chemical reduction of GO and limited intercalation in the resulting nanochannel ensures satisfactory nanochannel stability during desalination. The stabilized membrane nanochannel exhibits a permeance of 0.69 L m−2 h−1 bar−1 and excellent Na2SO4 rejection of 96.42%. Furthermore, this optimized membrane nanochannel demonstrates enhanced stability under varying external conditions compared to the original GO. This study provides useful information for the design of chemical conversion agents for GO nanochannel stabilization and the development of nanochannel membranes for precise separation.
Separation of Mono‐/Divalent Ions via Controlled Dynamic Adsorption/Desorption at Polythiophene Coated Carbon Surface with Flow‐Electrode Capacitive Deionization
Authors: Xiong Jingjing , Ye Wenkai , Mu Liwen , Lu Xiaohua , Zhu Jiahua
Published: April 2024

Capacitive deionization for selective separation of ions is rarely reported since it relies on the electrostatic attraction of oppositely charged ions with no capability to distinguish ions of different valent states. Using molecular dynamic simulation, a screening process identified a hybrid material known as AC/PTh, which consists of activated carbon with a thin layer of polythiophene (PTh) coating. By utilizing AC/PTh as electrode material implementing the short‐circuit cycle (SCC) mode in flow‐electrode capacitive deionization (FCDI), selective separation of mono‐/divalent ions can be realized via precise control of dynamic adsorption and desorption of mono‐/divalent ions at a particular surface. Specifically, AC/PTh shows strong interaction with divalent ions but weak interaction with monovalent ions, the distribution of divalent ions can be enriched in the electric double layer after a couple of adsorption–desorption cycles. At Cu2+/Na+ molar ratio of 1:40, selectivity toward divalent ions can reach up to 110.3 in FCDI SCC mode at 1.0 V. This work presents a promising strategy for separating ions of different valence states in a continuously operated FCDI device.
CuO (111) Microcrystalline Evoked Indium–Organic Framework for Efficient Electroreduction of CO2 to Formate
Authors: Huang Honghao , Yue Kaihang , Liu Chaofan , Zhan Ke , Dong Hongliang , Yan Ya
Published: April 2024

Electrochemical reduction of carbon dioxide (CO2RR) to formate is economically beneficial but suffers from poor selectivity and high overpotential. Herein, enriched microcrystalline copper oxide is introduced on the surface of indium‐based metal–organic frameworks. Benefiting from the CuO (111) microcrystalline shell and formed catalytic active In–Cu interfaces, the obtained MIL‐68(In)/CuO heterostructure display excellent CO2RR to formate with a Faradaic efficiency (FE) as high as 89.7% at low potential of only −0.7 V vs. RHE in a flow cell. Significantly, the membrane electrode assembly (MEA) cell based on MIL‐68(In)/CuO exhibit a remarkable current density of 640.3 mA cm−2 at 3.1 V and can be stably operated for 180 h at 2.7 V with a current density of 200 mA cm−2. The ex/in situ electrochemical investigations reveal that the introduction of CuO increases the formation rate of the carbon dioxide reduction intermediate *HCOO− and inhibits the competitive hydrogen evolution reaction. This work not only provides an in‐depth study of the mechanism of the CO2RR pathways on In/Cu composite catalyst but also offers an effective strategy for the interface design of electrocatalytic carbon dioxide reduction reaction.
Nucleation‐Inhibited Emulsion Interfacial Assembled Polydopamine Microvesicles as Artificial Antigen‐Presenting Cells
Authors: Dong Lingkai , Liu Minchao , Fang Meng , Lu Qianqian , Li Xingjin , Ma Yanming , Zhao Tiancong
Published: April 2024

Albeit microemulsion systems have emerged as efficient platforms for fabricating tunable nano/microstructures, lack of understanding on the emulsion‐interfacial assembly hindered the control of fabrication. Herein, a nucleation‐inhibited microemulsion interfacial assembly method is proposed, which deviates from conventional interfacial nucleation approaches, for the synthesis of polydopamine microvesicles (PDA MVs). These PDA MVs exhibit an approximate diameter of 1 µm, showcasing a pliable structure reminiscent of cellular morphology. Through modifications of antibodies on the surface of PDA MVs, their capacity as artificial antigen presentation cells is evaluated. In comparison to solid nanoparticles, PDA MVs with cell‐like structures show enhanced T‐cell activation, resulting in a 1.5‐fold increase in CD25 expression after 1 day and a threefold surge in PD‐1 positivity after 7 days. In summary, the research elucidates the influence of nucleation and interfacial assembly in microemulsion polymerization systems, providing a direct synthesis method for MVs and substantiating their effectiveness as artificial antigen‐presenting cells.
Efficient Lead Removal by Assembly of Bio‐Derived Ellagate Framework, Which Enables Electrocatalytic Reduction of CO2 to Formate
Authors: Chen Song , Chung Lai‐Hon , Chen Shaoru , Jiang Zhixin , Li Ning , Hu Jieying , Liao Wei‐Ming , He Jun
Published: April 2024

Lead (Pb) poisoning and CO2‐induced global warming represent two exemplary environmental and energy issues threatening humanity. Various biomass‐derived materials are reported to take up Pb and convert CO2 electrochemically into low‐valent carbon species, but these works address the problems separately rather than settle the issues simultaneously. In this work, cheap, natural ellagic acid (EA) extracted from common plants is adopted to assemble a stable metal–organic framework (MOF), EA‐Pb, by effective capture of Pb2+ ions in an aqueous medium (removal rate close to 99%). EA‐Pb represents the first structurally well‐defined Pb‐based MOF showing selective electrocatalytic CO2‐to‐HCOO− conversion with Faradaic efficiency (FE) of 95.37% at −1.08 V versus RHE. The catalytic mechanism is studied by 13CO2 labeling, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and theoretical calculation. The use of EA‐Pb as an electrocatalyst for CO2 reduction represents a 2‐in‐1 solution of converting detrimental wastes (Pb2+) as well as natural resources (EA) into wealth (electrocatalytic EA‐Pb) for addressing the global warming issue.
Anisotropic Te/PdSe2 Van Der Waals Heterojunction for Self‐Powered Broadband and Polarization‐Sensitive Photodetection
Authors: Wang Pu , Li Zhao , Xia Xue , Zhang Jingni , Lan Yingying , Zhu Lu , Ke Qingqing , Mu Haoran , Lin Shenghuang
Published: April 2024

Polarization‐sensitive broadband optoelectronic detection is crucial for future sensing, imaging, and communication technologies. Narrow bandgap 2D materials, such as Te and PdSe2, show promise for these applications, yet their polarization performance is limited by inherent structural anisotropies. In this work, a self‐powered, broadband photodetector utilizing a Te/PdSe2 van der Waals (vdWs) heterojunction, with orientations meticulously tailored is introduced through polarized Raman optical spectra and tensor calculations to enhance linear polarization sensitivity. The device exhibits anisotropy ratios of 1.48 at 405 nm, 3.56 at 1550 nm, and 1.62 at 4 µm, surpassing previously‐reported photodetectors based on pristine Te and PdSe2. Additionally, it exhibits high responsivity (617 mA W−1 at 1550 nm), specific detectivity (5.27 × 1010 Jones), fast response (≈4.5 µs), and an extended spectral range beyond 4 µm. The findings highlight the significance of orientation‐engineered heterostructures in enhancing polarization‐sensitive photodetectors and advancing optoelectronic technology.
Use of Interfacial Interactions and Complexation of Carbon Dots to Construct Ultra‐Robust and Efficient Photothermal Film From Micro‐Carbonized Polysaccharides
Authors: Ding Yingying , Liu Shouxin , Yang Long , Du Guanben , Wan Jianyong , Chen Zhijun , Li Shujun
Published: April 2024

Solar energy conversion technologies, particularly solar‐driven photothermal conversion, are both clean and manageable. Although much progress has been made in designing solar‐driven photothermal materials, significant challenges remain, not least the photobleaching of organic dyes. To tackle these issues, micro‐carbonized polysaccharide chains, with carbon dots (CDs) suspended from the chains, are conceived, just like grapes or tomatoes hanging from a vine. Carbonization of sodium carboxymethyl cellulose (CMC) produces just such a structure (termed CMC‐g‐CDs), which is used to produce an ultra‐stable, robust, and efficient solar‐thermal film by interfacial interactions within the CMC‐g‐CDs. The introduction of the CDs into the matrix of the photothermal material effectively avoided the problem of photobleaching. Manipulating the interfacial interactions (such as electrostatic interactions, van der Waals interactions, π–π stacking, and hydrogen bonding) between the CDs and the polymer chains markedly enhances the mechanical properties of the photothermal film. The CMC‐g‐CDs are complexed with Fe3+ to eliminate leakage of the photothermal reagent from the matrix and to solve the problem of poor water resistance. The resulting film (CMC‐g‐CDs‐Fe) has excellent prospects for practical application as a photothermal film.
Highly Durable Silicone‐Based Elastomers Achieved Through the Synergy of Bi‐Incompatible Soft Segments and Multi‐Scale Hydrogen Bonds
Authors: Zheng Wei , Zhang Chengshu , Han Yangjiao , Wang Wenpin , Li Zhibo
Published: April 2024

Developing a silicone elastomer with high strength, exceptional toughness, good crack tolerance, healability, and recyclability, poses significant challenges due to the inherent trade‐offs between these properties. Herein, the design of silicone‐based elastomers with a nanoscopic microphase separation structure and comprehensive mechanical properties is achieved by combining bi‐incompatible soft segments and multi‐scale hydrogen bonds. The formation of multi‐scale hydrogen bonds involving urethane, urea, and 2‐ureido‐4[1H]‐pyrimidinone (UPy) facilitates efficient reversible crosslinking of the synthesized polymer containing thermodynamically incompatible poly(dimethylsiloxane) (PDMS) and poly(propylene glycol) (PPG). The dynamic dissociation and recombination of hydrogen bonds, coupled with the forced compatibility and spontaneous separation of bi‐incompatible soft segments, can effectively dissipate energy, particularly in the crack region during the stretching process. The obtained silicone‐based elastomer exhibits a high break strength of 8.0 MPa, good elongation at break of 1910%, ultrahigh toughness of 67.8 MJ m−3, and unprecedented fracture energy of 31.8 kJ m−2 while maintaining their thermal stability, hydrophobicity, healability, and recyclability. This resilient and long‐lasting silicone‐based elastomer exhibits significant potential for use in flexible electronic devices.
Research on the toxicological prognostic significance of age‐related genes in endometrial cancer unveiling key factors in patient prognosis
Authors: Yin Yongchao , Niu Qian , Wei Zhiqiang , Wang Yefei , Li Gang , Zhang Weican , Guo Kai , Yao Xinyu
Published: April 2024

This study investigates the influence of aging‐related genes on endometrial cancer, a prominent gynecological malignancy with rising incidence and mortality. By analyzing gene expression differences between cancerous and normal endometrial tissues, 42 aging‐related genes were identified as differentially expressed. Utilizing the TCGA‐UCEC sample, consensus clustering divided the samples into two molecular subgroups, Aging low and Aging high, based on their expression profiles. These subgroups showed distinct prognoses and survival rates, with the Aging high group associated with DNA repair and cell cycle pathways, and the Aging low group showing suppressed metabolic pathways and increased immune cell infiltration, suggesting a potential for better immunotherapy outcomes. Mutation analysis did not find significant differences in mutation frequencies between the groups, but a high Tumor Mutation Burden (TMB) correlated with better prognosis. A risk score model was also developed, showcasing significant prognostic power. Further analysis of the SIX1 gene revealed its overexpression in cancer cells. Drug sensitivity tests indicated that the low‐risk group might respond better to chemotherapy. This research underscores the significance of aging‐related genes in endometrial cancer, offering insights into their prognostic value and therapeutic potential, which could lead to personalized treatment approaches and enhanced patient management.
RETRACTED: Zinc finger Protein207 orchestrates glioma migration through regulation of epithelial‐mesenchymal transition
Authors: Zhao Chao , Guo Yuduo , Chen Yujia , Shang Guanjie , Song Dixiang , Wang Jun , Yang Jingjing , Zhang Hongwei
Published: April 2024

Background

Glioma represents the predominant primary malignant brain tumor. For several years, molecular profiling has been instrumental in the management and therapeutic stratification of glioma, providing a deeper understanding of its biological complexity. Accumulating evidence unveils the putative involvement of zinc finger proteins (ZNFs) in cancer. This study aimed to elucidate the role and significance of ZNF207 in glioma.

Methods

Utilizing online data such as The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), the Genotype‐Tissue Expression (GTEx) project, the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA) databases, in conjunction with bioinformatics methodologies including GO, KEGG, GSEA, CIBERSORT immune cell infiltration estimation, and protein–protein interaction (PPI) analysis, enabled a comprehensive exploration of ZNF207's involvement in gliomagenesis. Immunohistochemistry and RT‐PCR techniques were employed to validate the expression level of ZNF207 in glioma samples. Subsequently, the biological effects of ZNF207 on glioma cells were explored through in vitro assays.

Results

Our results demonstrate elevated expression of ZNF207 in gliomas, correlating with unfavorable patient outcomes. Stratification analyses were used to delineate the prognostic efficacy of ZNF207 in glioma with different clinicopathological characteristics. Immunocorrelation analysis revealed a significant association between ZNF207 expression and the infiltration levels of T helper cells, macrophages, and natural killer (NK) cells. Utilizing ZNF207 expression and clinical features, we constructed an OS prediction model and displayed well discrimination with a C‐index of 0.861. Moreover, the strategic silencing of ZNF207 attenuated glioma cell advancement, evidenced by diminished cellular proliferation, weakened cell tumorigenesis, augmented apoptotic activity, and curtailed migratory capacity alongside the inhibition of the epithelial‐mesenchymal transition (EMT) pathway.

Conclusions

ZNF207 may identify as a prospective biomarker and therapeutic candidate for glioma prevention, providing valuable insights into understanding glioma pathogenesis and treatment strategies.
An artificial intelligence‐driven scoring system to measure histological disease activity in ulcerative colitis
Authors: Peyrin‐Biroulet Laurent , Adsul Shashi , Stancati Andrea , Dehmeshki Jamshid , Kubassova Olga
Published: April 2024

Background and Aims

Assessment and scoring of histological images in Ulcerative colitis (UC) is prone to inter‐ and intra‐observer variability. This study aimed to investigate whether an artificial intelligence (AI) system developed using image processing and machine learning algorithms could measure histological disease activity based on the Nancy index.

Methods

A total of 200 histological images of patients with UC were used in this study. A novel AI algorithm was developed using state‐of‐the‐art image processing and machine learning algorithms based on deep learning and feature extraction. The cell regions of each image, followed by the Nancy index, were manually annotated and measured independently by four histopathologists. Manual and AI‐automated measurements of the Nancy index score were conducted and assessed using the intraclass correlation coefficient (ICC).

Results

The 200‐image dataset was divided into two groups (80% was used for training and 20% for testing). Intraclass correlation coefficient statistical analyses were performed to evaluate the AI tool and used as a reference to calculate the accuracy. The average ICC among the histopathologists was 89.3 and the average ICC between histopathologists and the AI tool was 87.2. The AI tool was found to be highly correlated with histopathologists.

Conclusions

The high correlation of performance of the AI method suggests promising potential for inflammatory bowel disease clinical applications. A standardized automated histological AI‐driven scoring system can potentially be used in daily inflammatory bowel disease practice to reduce training needs and resource use, eliminate the subjectivity of the pathologists, and assess disease severity for treatment decisions.
Compounds from aerial parts of Isodon lophanthoides and their effects of cytotoxicity and LPS‐induced IL‐1β and IL‐10 production in RAW 264.7 macrophages
Authors: Khoa Nguyen Manh , Thu Nguyen Thi , Hien Tran Thi , Diep Vu Thi , Trang Ha Thuy , Manh Do Hong , Tuan Nguyen Hoang , Ha Do Thi
Published: April 2024

The bioassay‐guided isolation of compounds from the aerial parts of Isodon lophanthoides (IL) resulted in the identification of five compounds (1–5). The chemical structures of 1–5 were determined through spectral analyses and compared to those identified in the literature to be 4‐hydroxybenzoic acid (1), protocatechuic acid (2), rosmarinic acid (3), coetsoidin B (4), and coetsoidin A (5). Compounds 1, 4, and 5 were found for the first time in the aerial parts of IL. Compounds 1 and 2 displayed potent cytotoxic activity against A549, MCF‐7, HepG2, and HL60 cancer cell lines, with IC50 values ranging from 13.93 to 18.69 µm and from 11.97 to 18.30 µm, respectively. Compounds 1‒5 significantly inhibited LPS‐induced IL‐1β production in RAW 264.7 macrophages compared to the LPS 5 ng/mL control group, resulting in IL‐1β concentrations ranging from 34.92 to 46.91 pg/mL. Additionally, compounds 1‒5 exhibited notable stimulation of IL‐10 production, with IL‐10 levels ranging from 358.77 to 478.23 pg/mL, compared to the LPS 5 ng/mL control group. These findings highlight the potential of compounds 1‒5 and the IL extracts for the cytotoxic effects on cancer cell lines and on LPS‐induced IL‐1β and IL‐10 production in RAW 264.7 macrophages.
Thunderstorms coming up against the wind on 11 June 2023 – the development of a mesoscale convective system over southern England
Authors: Pike W. S. , Smart D. J.
Published: April 2024

On 11 June 2023, a mesoscale convective system (MCS) developed over the southern UK producing heavy rainfall and numerous lightning strikes. The MCS formed from clusters of relatively small‐scale thundery showers south and west of the London area. These showers then merged together and grew upscale to form an organised convective system of the leading‐line trailing stratiform type with a large quasi‐circular cloud shield. Both surface‐based and elevated convection appears to have been involved. Heavy rainfall caused localised surface water flooding with a number of stations in southern England reporting event totals in excess of 1 inch (25.4mm).
A new insight into the surface adsorption in the solution phase: A modification of the Langmuir isotherm
Authors: Ezzati Rohollah
Published: April 2024

The Langmuir isotherm, originally developed to study the adsorption of gases, has been modified in this research to investigate the adsorption of solutes in the solution phase. The modification considers the adsorption of solvent molecules and the interactions between adsorbed particles and the species in the solution. Three equations have been obtained to calculate the contribution of these additional effects on the Gibbs free energy, enthalpy, and entropy of solute adsorption based on the new isotherm. The study evaluated the efficiency of the new isotherm in the adsorption of some metal ions in an aqueous solution and found that it is more accurate than the Langmuir isotherm and provides a deeper insight into the adsorption process in the solution phase.

Practitioner Points

Modification of the Langmuir isotherm for adsorption in solution.

Comparison of the efficiency of the Langmuir and modified Langmuir isotherms.

Accurate determination of and for Pb(II), Cd(II), and Ni(II) adsorption.