bluuebunny/crossref_metadata_2025 huggingface dataset:
Stepwise Construction of Supramolecular A2B4‐Type Miktoarm Star Copolymers with a Cobalt Phthalocyanine Core
Authors: Zhong Xinhao , Cheng Hsu‐Tzu , Chueh Chu‐Chen , Takeuchi Masayuki , Aimi Junko
Published: November 2024

Supramolecular interactions between polymers play a crucial role in the construction of three‐dimensional polymer structures with unique physical and chemical properties. In this study, we have fabricated a novel supramolecular miktoarm star copolymer (μ‐star) with a cobalt(II) phthalocyanine (CoPc) core using metal‐ligand coordination. Axial coordination of the terminal pyridyl group of poly(methyl methacrylate) with the CoPc core of four‐armed star‐shaped polystyrene provided AB4‐ and A2B4‐type μ‐stars through stepwise complexation. The spin‐coated polymer films from mixed solutions of CoPcPS4 and pyPMMA in 1 : 1 or 1 : 2 mass ratios exhibited phase‐separated nanodomains with smooth surfaces. Supramolecular interactions in polymer systems provide a unique topology to polymers and affect their bulk morphology.
Selenocompounds as Potent Efflux Pump Inhibitors on Gram‐positive Bacteria
Authors: Kincses Annamária , Szemerédi Nikoletta , Benito‐Lama Miguel , Dózsai Dávid , Csonka Ákos , Domínguez‐Álvarez Enrique , Spengler Gabriella
Published: November 2024

In recent years, selenocompounds have gained increasing attention as potential anticancer and antibacterial agents. Several selenoderivatives have been confirmed to act as MDR efflux pump inhibitors, based on their in vitro results against the bacterial AcrAB‐TolC system and the cancer MDR efflux pump P‐glycoprotein. Efflux pumps can contribute directly or indirectly to the virulence of bacteria, as they can reduce the intracellular concentration of antibacterial substances by expelling them out of the cell. The present work aims to study the antibacterial and efflux pump inhibiting properties of four families of selenoesters, namely aspirin‐selenoesters, phenone‐selenoesters, hydroxy‐selenoesters, and benzyl‐selenoesters. The real‐time ethidium bromide accumulation assay confirmed that these derivatives inhibited the efflux systems of methicillin‐resistant Staphylococcus aureus (MRSA) without exerting any antibacterial effect. The relative expression of efflux pump gene of NorA transporter was also monitored in the presence of the most potent derivatives on reference S. aureus, finding that these derivatives could change the expression of the tested efflux pump gene. Regarding the anti‐biofilm activity, aspirin‐selenoesters, benzyl‐selenoesters, and hydroxy‐selenoesters could efficiently inhibit the biofilm production of the MRSA strain. It can be concluded that selenocompounds could act as efflux pump inhibitors, thus reducing the virulence of biofilm‐producing bacteria.
ChemPrice, a Python Package for Automated Chemical Price Search
Authors: Cihan Sorkun Murat , Saliou Baptiste , Er Süleyman
Published: November 2024

The open‐access movement in chemistry has led to a surge in publicly accessible data repositories such as PubChem and ChemSpider, housing more than 100 million chemical compounds. These repositories are invaluable for large‐scale virtual screening but lack crucial pricing information, a vital economic aspect influencing commercial decisions. Currently, these databases merely provide hyperlinks to vendor websites for pricing details, necessitating manual exploration due to the diverse structures of vendor websites, making automated data extraction impractical. To tackle this challenge, we introduce ChemPrice, a Python package that streamlines the collection of pricing data through the integration of ChemSpace, Mcule, and Molport platforms that provide up‐to‐date price information from over 100 suppliers. ChemPrice standardizes pricing units, offering consolidated and best‐pricing information for specified compounds. Its modular design facilitates integration into automated virtual screening workflows, and a user‐friendly web interface caters to those with limited coding skills, enabling easy compound list uploading and pricing data retrieval. This innovation addresses the complexity of collecting compound prices and enables integration into the virtual screening code workflows, providing a valuable resource for a wide community of users seeking comprehensive and up‐to‐date pricing information to enhance their decision‐making processes.
AI Based Resource Management for 5G Network Slicing: History, Use Cases, and Research Directions
Authors: Dubey Monika , Singh Ashutosh Kumar , Mishra Richa
Published: November 2024

5G, 6G, and beyond networks promise to support vertical industrial services with strict QoS parameters, but the hardware‐based "one‐size‐fits‐all" model of legacy networks lacks the flexibility needed for diverse services. The foundation of 5G networks lies in softwarization, with network slicing, Software Defined Networking (SDN), and Network Function Virtualisation (NFV) serving as its core components. The network‐slicing‐based shared network environment necessitates an intelligent and flexible resource management approach. In this case, traditional approaches are no longer suitable for dealing with a dynamic network environment. With recent advancements, AI‐based approaches have the potential to manage resources autonomously. This paradigm shift underscores the need for deep and extensive investigation. However, existing literature on this subject is fragmented and lacks a cohesive overview of network slicing. To address these gaps, our review paper aims to provide a comprehensive scope of network slicing in a unified manner. In this sequence at first, this paper presented a conceptual overview of network slicing and enabling technologies, including SDN, NFV, and edge computing. Secondly, this paper identifies the relevant phases of resource management and presents AI‐based resource management for network traffic classification, admission, allocation, and scheduling. Finally, it also discusses the deployment of network slicing‐enabled key use cases and their practical deployment, the research gap, and open research challenges. To the best of our knowledge, this is the first attempt to critically analyze and present a consolidated review of the state of the art in network slicing resource management modules and network slicing‐enabled key industrial use cases. This paper aims to guide researchers in developing innovative solutions and assist network players in the practical deployment of network slices for industrial applications.
17O NMR Spectroscopy Reveals CO2 Speciation and Dynamics in Hydroxide‐Based Carbon Capture Materials
Authors: Rhodes Benjamin J. , Schaaf Lars L. , Zick Mary E. , Pugh Suzi M. , Hilliard Jordon S. , Sharma Shivani , Wade Casey R. , Milner Phillip J. , Csányi Gábor , Forse Alexander C.
Published: November 2024

Carbon dioxide capture technologies are set to play a vital role in mitigating the current climate crisis. Solid‐state 17O NMR spectroscopy can provide key mechanistic insights that are crucial to effective sorbent development. In this work, we present the fundamental aspects and complexities for the study of hydroxide‐based CO2 capture systems by 17O NMR. We perform static density functional theory (DFT) NMR calculations to assign peaks for general hydroxide CO2 capture products, finding that 17O NMR can readily distinguish bicarbonate, carbonate and water species. However, in application to CO2 binding in two test case hydroxide‐functionalised metal‐organic frameworks (MOFs) – MFU‐4l and KHCO3‐cyclodextrin‐MOF, we find that a dynamic treatment is necessary to obtain agreement between computational and experimental spectra. We therefore introduce a workflow that leverages machine‐learning force fields to capture dynamics across multiple chemical exchange regimes, providing a significant improvement on static DFT predictions. In MFU‐4l, we parameterise a two‐component dynamic motion of the bicarbonate motif involving a rapid carbonyl seesaw motion and intermediate hydroxyl proton hopping. For KHCO3‐CD‐MOF, we combined experimental and modelling approaches to propose a new mixed carbonate‐bicarbonate binding mechanism and thus, we open new avenues for the study and modelling of hydroxide‐based CO2 capture materials by 17O NMR.
Two‐Photon Absorption Switches Based on Protonation of Pyrimidine Derivatives
Authors: Sdralias Lampros , Katsidas Alexandros , Polyzos Ioannis , Bonnaud Thibault , Noirbent Guillaume , Achelle Sylvain , Fakis Mihalis
Published: November 2024

The photophysical and two‐photon absorption (TPA) properties of five push‐pull pyrimidine derivatives were studied upon protonation with trifluoroacetic acid (TFA). The pyrimidine heterocycles have been used as the protonation sites and electron acceptors while methoxy groups were employed as electron donors. Steady state and fluorescence time‐resolved spectroscopy from femtoseconds to nanoseconds have been used together with the two‐photon excited fluorescence method. Protonation with TFA resulted in red‐shifted absorption and fluorescence spectra as well as to an acceleration of the excited state dynamics. The TPA properties showed a remarkable enhancement upon protonation with a ten‐times increase of the TPA cross sections due to an increased intramolecular charge transfer. Our results demonstrate the potential of pyrimidine chromophores to be used as protonation tunable non‐linear optical chromophores.
Incorporating stressor interactions into spatially explicit cumulative impact assessments
Authors: Stockbridge Jackson , Jones Alice R. , Brown Christopher J. , Doubell Mark J. , Gillanders Bronwyn M.
Published: November 2024

Human‐induced stressors are impacting the oceans and reducing the biodiversity of marine ecosystems. The many stressors affecting marine environments do not act in isolation. However, their cumulative impact is difficult to predict. Most of the available methods for quantifying cumulative impacts on marine ecosystems sum the impact of individual stressors to estimate cumulative impact. We demonstrate how experimental evidence from interacting stressors can be accounted for in cumulative impact assessments. We adapted a widely used additive model to incorporate nonadditive stressor interactions into a marine spatially explicit cumulative impact assessment for seagrasses. We combined experimental data on the impact of multiple stressors with spatial data on stressor intensity to test whether stressor interactions impact seagrasses in a case study region in South Australia. We also assessed how uncertainty about cumulative impacts changes when uncertainty in stressor interactions is included in the impact mapping. The results from an additive spatial cumulative impact assessment model were compared with results from the model incorporating interactions. Cumulative effects from the interaction model were more variable than those produced by the additive model. Five of the 15 stressor interactions that we tested produced impacts that significantly deviated from those predicted by an additive model. Areas of our study region that showed the largest discrepancies between the additive and interactive outputs were also associated with higher uncertainty. Our study demonstrates that the inclusion of stressor interactions changes the pattern and intensity of modeled spatial cumulative impact. Additive models have the potential to misrepresent cumulative impact intensity and do not provide the opportunity for targeted mitigation measures when managing the interactive effects of stressors. Appropriate inclusion of interacting stressor data may have implications for the identification of key stressors and the subsequent spatial planning and management of marine ecosystems and biodiversity.
California's College of the Redwoods: Meeting students where they are
Authors: D’Orio Wayne
Published: November 2024

CRESCENT CITY, Calif. — Tory Eagles was a financial aid administrator at College of the Redwoods in 2016 when she helped the school set up a program at Pelican Bay State Prison, California's max security facility.
Leveraging technology to simplify administrative tasks
Authors: Arnett Autumn A.
Published: November 2024

“Hello, I’m a university professor. My job is to answer email and complete mandatory online training courses,” said a post on X from Fernanda Ferreira, a professor of psycholinguistics at the University of California–Davis earlier this year.
Hybridization of Stirling Heat Engine with Solid Oxide Electrolysis Cell: Performance Prediction and Regulation Mechanism
Authors: Lang Shaocheng , Yuan Jinliang
Published: November 2024

Solid oxide electrolysis cell (SOEC) is an advanced green energy storage technology for achieving high‐efficiency hydrogen production. However, SOEC generates redundant waste heat in exothermic mode. To improve system exergy efficiency and ensure stable and reliable operation of the SOEC, a novel hybrid system is proposed to mainly comprise an SOEC and a Stirling heat engine (SHE). Mathematical formulas for the exergy efficiency of the SOEC‐SHE hybrid system are obtained and applied for this system, and it is found that the exergy efficiency is 69.90%, which is 13.77% higher than that of a single SOEC system when the operating current density is 30 000 A m−2. A mixed orthogonal experiment method is further implemented to analyze the comprehensive effects of various parameters on the exergy efficiency of the SOEC‐SHE hybrid system. Operated on the optimal combination of the investigated parameters, the exergy efficiency of the SOEC‐SHE hybrid system reaches 82.35%, which is further improved by 17.81%. The results provide valuable theoretical insights for the design and operation of the SOEC‐SHE hybrid system.
Purification and Characterization of Pinto Bean Protein Using Membrane Technology
Authors: Aliabbasi Neda , Diosady Levente L. , Emam‐Djomeh Zahra
Published: November 2024

Pinto beans, an underutilized legume, are abundant in protein content and contain a variety of beneficial phytonutrients. However, the commonly used protein extraction method, alkaline extraction, is associated with several drawbacks. These drawbacks include low extraction yield and purity as well as the production of large amounts of wastewater that can lead to environmental hazards. In this regard, membrane technology has gained considerable recognition as a superior method for extracting proteins. A combined processing scheme was developed, which included alkaline extraction at pH 10.5, ultrafiltration with a concentration factor of 5.5, diafiltration with a diavolume of 4, and isoelectric precipitation at pH 4.5 followed by freeze drying. The specific functional characteristics (nitrogen solubility index, water and oil holding capacity, and emulsifying and foaming properties) of the protein concentrates were assessed and compared with those of a commercially available soybean protein isolate. Based on pinto bean flour containing 23.9% protein, 85.5% of the protein was recovered in the products of this process: precipitated protein concentrate (PPC) with 86.4% protein, acid‐soluble protein concentrate (ASP‐C) with 56.3% protein, and meal residue with 6.1% protein. The mass yields were 17.3% in PPC, 3.9% in ASP‐C, and 54% in the meal residue. The precipitated protein showed higher emulsifying activity, and the acid‐soluble protein showed a high nitrogen solubility index (NSI) and oil‐holding capacity. Both proteins had comparable foaming properties to commercial soy protein isolate. The project demonstrated the feasibility of protein production from pinto beans and highlighted the proteins' useful food functionality and good potential for commercialization.
Affordances in the Home Environment for Motor Development for Turkish Children: Cultural Adaptation, Validity and Reliability Analysis
Authors: Ergün Başak , Önal Gözde , Zengin Yazıcı Gülşah , Akyürek Gökçen
Published: November 2024

The home environment is a significant factor that greatly influences the motor development of children. This study aims to examine the cultural adaptation validity and reliability of the Affordances in the Home Environment for Motor Development (AHEMD‐SR) for Turkish children aged 18–42 months. The study included 103 Turkish children (mean age = 29.3 ± 7.4 months; 57.3% female, 42.6% male). The majority of participants were from middle‐income families. The AHEMD‐SR was administered to parents, and test–retest reliability was evaluated with a subsample of 30 families. The Cronbach's alpha coefficient and Intraclass Correlation Coefficient (ICC) were calculated to assess reliability, while correlations with the Denver Developmental Screening Tool 2 (DDST‐2) were examined for convergent validity. The Cronbach's alpha coefficient of the AHEMD‐SR was 0.815, and the ICC for test–retest reliability was 0.889. The AHEMD‐SR total score correlated with DDST‐2's social development (r = 0.32), fine motor development (r = 0.33) and gross motor development (r = 0.33) domains (all p < 0.05). The Turkish version of the AHEMD‐SR was found to be a valid and reliable tool for assessing the home environment's impact on motor development in children aged 18–42 months. This questionnaire can provide valuable insights into how to enhance home environments to better support children's motor development in Turkey.
Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization
Authors: Talebpour Mahdad , Bou‐Zeid Elie , Welty Claire , Li Dan , Zaitchik Benjamin
Published: November 2024

Urban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.
Raman Spectroscopy Reveals Microparticles in Synovial Fluids of Patients With Suspected Implant‐Related Complications
Authors: Niessink Tom , Schoenmakers Jorrit W. A. , Janssen Matthijs , Wouthuyzen‐Bakker Marjan , Piersma Sjouke , van Oosten Marleen , van Dijl Jan Maarten , Otto Cees , Jansen Tim L.
Published: November 2024

Prosthetic implant‐associated inflammation and failure can be caused by bacterial infections and mechanical wear of the prosthesis. Currently, there is no diagnostic modality that allows simultaneous identification of both causes of implant failure. Here, we present a proof‐of‐principle study to assess whether Raman spectroscopy can be applied to diagnose implant failure. Synovial fluids from 10 patients with a clinical suspicion of implant‐related complications were previously collected and cultured to determine the presence of bacteria. The presence of microparticles in these synovial fluids was assessed by Raman spectroscopy and verified by scanning electron microscopy combined with energy‐dispersive X‐ray spectroscopy (SEM‐EDX). For control, the possibility to detect in vitro‐cultured Staphylococcus aureus by Raman spectroscopy was investigated. Raman spectroscopy revealed that all 10 synovial fluid samples contained microparticles: eight contained microplastics (polyethylene, polypropylene, and polystyrene), and nine contained titanium dioxide nanoparticles (anatase and rutile) as verified by SEM‐EDX. There was no clear difference in the microparticle content of synovial fluids with or without bacteria. Raman signals relating to individual bacteria and clusters of bacteria were detectable in in vitro cultures of S. aureus, but it was not possible to demonstrate the presence of bacteria in synovial fluids by Raman spectroscopy. Raman spectroscopy is a potential tool for characterizing microparticles in synovial fluids from patients with implant‐related complications. This is of clinical relevance as these microparticles can cause joint inflammation. The identification of bacteria by Raman spectroscopy is feasible, but further research is needed before clinical implementation.
The Use of Near‐Infrared Indocyanine Green Fluorescence Imaging to Differentiate Benign Versus Malignant Adrenal Tumors
Authors: Berber Beren , Krishnamurthy Vikram , Siperstein Allan
Published: November 2024

Introduction

Despite advances in imaging modalities, a significant number of adrenal tumors are considered indeterminate and removed surgically. Currently, there is no intraoperative tool available to provide further information about the nature of indeterminate adrenal tumors. The aim of this study was to investigate whether near‐infrared indocyanine green (ICG) imaging can be used in this regard.

Methods

This was an institutional review board‐approved study. Within 9 years, 197 patients underwent robotic adrenalectomy with ICG imaging. Adrenal tumors were characterized prospectively as fluorescent or nonfluorescent intraoperatively. ICG was administered as a 2.5 mg dose, one to three times a procedure. No patient developed an allergic reaction. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

Results

Robotic transabdominal lateral adrenalectomy was performed in 155 patients and posterior retroperitoneal adrenalectomy in 42 patients. One hundred and eighty‐four patients had benign adrenal tumors, 10 patients had malignant tumors, and three patients had tumors of uncertain malignant potential. Sensitivity, specificity, PPV, and NPV to predict a benign tumor were 87%, 38.5%, 95.2%, and 17.2%.

Conclusions

To our knowledge, this is the largest study on ICG imaging of adrenal tumors. High PPV to detect benign tumors suggests a utility of ICG to provide the surgeon with further information about the benign vs malignant nature of indeterminate adrenal tumors taken to surgery.
Sustained Drug Release from Dual‐Responsive Hydrogels for Local Cancer Chemo–Photothermal Therapy
Authors: Liu Zhixiang , Koseki Yoshitaka , Suzuki Ryuju , Dao Anh Thi Ngoc , Kasai Hitoshi
Published: November 2024

As an exceptional carrier for localized drug delivery to tumors, hydrogels can achieve prolonged drug release through careful design and adjustments, effectively targeting cancer cells and minimizing side effects. This study investigates a novel dual‐responsive hydrogel system designed for the delivery of nanomedicines, focusing on drug release and the local antitumor efficacy of SN‐38‐cholesterol nanoparticles (SN‐38‐chol NPs) and polydopamine NPs (PDA NPs)/poly(n‐isopropylacrylamide) (pNIPAM) hydrogels. By combining the thermosensitive properties of pNIPAM with the near‐infrared (NIR) responsiveness of PDA NPs, the hydrogel aims to enhance on‐demand drug release. SN‐38‐chol NPs, known for their stability and small size, are incorporated into the hydrogel to improve drug release dynamics. The investigation reveals a drug release cycle of over three weeks, maintaining sensitivity to both temperature and NIR light for controlled drug release. In vivo studies demonstrate the high tumor growth inhibition performance of the system after photothermal treatment induced by 808 nm NIR light. These results suggest that the drug‐carrying hydrogel system holds promise for diverse applications in chemical and physical therapies, including the treatment of malignant wounds, post‐surgery wound healing, and direct tumor treatment. This study establishes the potential of SN‐38‐chol NPs and PDA NPs/pNIPAM hydrogels as effective platforms for chemo‐phototherapy.
Electroplating on Electrically Conductive Filaments for Additive Manufacturing
Authors: Eßbach Claudia , Förster Wolfgang , Fischer Dirk , Dietrich Dagmar , Neumann Peter , Nickel Daniela
Published: November 2024

Materials for additive manufacturing by material extrusion are thermoplastic polymers that can be processed by the impact of heating. Reinforcement of established base materials expands potential applications by increasing the variety of properties. Introducing electroconductivity enables the process of direct electroplating, and reduces the process steps and the use of toxic reagents. Therefore, the development of electroconductive materials is a promising research field. In this work, a composite material based on polylactic acid (PLA) is examined that allows direct electroplating by adding carbon products as electroconductive filler. In agreement with the literature, a total amount of 10 wt.% of carbon materials (graphite and carbon black) is sufficient to achieve the desired electroconductivity and still allows processing. Electroplating on the extruded filaments is enhanced by mechanical roughening and provides promising results for further investigations.
Well‐posedness and inviscid limits for the Keller–Segel–Navier–Stokes system of the parabolic–elliptic type
Authors: Takeuchi Taiki
Published: November 2024

We show the local well‐posedness of the Keller–Segel system of the parabolic–elliptic type coupled with the Navier–Stokes system for arbitrary initial data with Sobolev regularities, where the solution is uniformly bounded with respect to the viscosity. We also show the continuous dependence of the solutions with respect to the initial data. As a result of the uniform boundedness of the solutions, we obtain inviscid limits of the system. The proof is mainly based on a priori estimates in the Sobolev spaces.
Supramolecular Janus Nanocylinders: Controlling Their Characteristics by the Self‐Assembly Process
Authors: Kalem Sandra , Siefker David , Ji Mingsheng , Guigner Jean‐Michel , Schweins Ralf , Pensec Sandrine , Rieger Jutta , Bouteiller Laurent , Nicol Erwan , Colombani Olivier
Published: November 2024

Janus NanoRods (JNR) are anisotropic and non‐symmetrical colloids with two faces of different chemical composition. They are difficult to prepare because of their nanometric dimensions and strong anisotropy. Recently, a versatile strategy was developed, allowing the formation of JNR relying on the self‐assembly in aqueous medium of two polymers end‐functionalized with non‐symmetrical and complementary hydrogen bonding stickers. However, the supramolecular JNR prepared following this strategy are out‐of‐equilibrium (frozen) and therefore their characteristics depend on the self‐assembly process. The present study elucidates the formation mechanism of the JNR and the parameters of the self‐assembly process influencing their characteristics. The polymers are initially dissolved as unimers in DMSO. Dropwise addition of water triggers the rapid assembly of more and more unimers into long nanocylinders that are unable to grow anymore once formed. Consequently, increasing the dropwise addition rate of water hardly impacts the process, whereas lowering the initial polymer concentration in DMSO reduces both the length and proportion of nanocylinders. Increasing temperature during water addition weakens hydrogen bonds, triggering the formation of a mixture of spheres and nanocylinders. Many supramolecular polymer assemblies are frozen in solution and these findings should help understanding how to control their characteristics, allowing to adapt them to a target application.
Patient Perspectives on Upper‐Limb Daily Function in Parkinson's Disease
Authors: Cohen Noa , Kizony Rachel
Published: November 2024

Background

Dexterity impairments are common among people with Parkinson's disease (PWP), yet little is understood about the effect of upper‐limb (UL) dysfunction on daily activity performance.

Objectives

The aims were to (1) map the dexterity activities most affected and meaningful to PWP; (2) explore the associations between perceived dexterity function and disease severity, cognitive and motor UL impairments, dexterity ability, self‐reported activities of daily living (ADL) function, and quality of life (QOL); (3) investigate variables explaining perceived dexterity function; and (4) examine the differences in perceived dexterity function based on dominance affectedness.

Methods

A total of 43 PWP (mean age = 70.00 years, standard deviation [SD] = 6.75) were assessed for perceived dexterity function (36‐item Dexterity Questionnaire [DextQ‐36]), dexterity ability (Coin Rotation Task), disease severity (modified Hoen and Yahr Scale), self‐reported ADL function and motor UL impairments (Movement Disorder Society‐Unified Parkinson's Disease Rating Scale), cognition (Montreal Cognitive Assessment), and QOL (Parkinson's Disease Questionnaire‐39).

Results

The leading dexterity activities participants reported as difficult and meaningful included using a touchscreen, pulling on socks, and dialing a phone. Perceived dexterity significantly correlated with self‐reported ADL function (r = 0.716), QOL (r = 0.691), disease severity (r = 0.470), and dominant‐hand dexterity (r = 0.432). Dexterity ability and disease severity explained 30% of perceived dexterity variance. No differences in perceived dexterity function based on dominance affectedness were found.

Conclusions

PWP encounter challenges in complex dexterity tasks that impact their independence. Before interventions focused on UL function are initiated, assessments of PWP should include inquiries about the meaningfulness of challenging dexterity activities.
‘Dirty dose’‐based proton variable RBE models ‐ performance assessment on in vitro data
Authors: Kalholm Fredrik , Toma‐Dasu Iuliana , Traneus Erik
Published: November 2024

Background

In clinical proton radiotherapy, a constant relative biological effectiveness (RBE) of 1.1 is typically applied. Due to abundant evidence of variable RBE effects from in vitro data, multiple variable RBE models have been suggested, typically by describing the and parameters in the linear quadratic (LQ) model as a function of dose averaged linear energy transfer ().

Purpose

This work introduces a new variable RBE model based on the dirty dose concept, where dose deposited in voxels with a corresponding LET exceeding a specific threshold is considered “dirty” in the sense that it has a biological effect above the one predicted by a constant RBE of 1.1. As only one LET level, corresponding to a specific energy for a given particle in a given medium, needs to be monitored, this offers several advantages, such as simplified calculations by removing the need for intricate end of range LET calculations and averaging procedures, as well as opening up for more efficient experimental assessment of the cell specific model parameters.

Methods

Previously published in vitro data were utilized, where surviving fraction (SF), dose and were reported for a pristine proton beam with varying physical PMMA thicknesses placed upstream of the cells. The setup was re‐simulated to extract dirty dose metrics for the corresponding reported ‐values. Models were created by setting the parameter of the LQ model as a function of the fraction of dirty dose and subsequently benchmarked against models based on other radiation quality metrics by comparing the root‐mean‐square‐error (RMSE) of the predicted and actual cell surviving fraction.

Results

Variable RBE models based on dirty dose perform on par with conventional radiation quality metrics with a RMSE of 0.38 for a dirty dose‐based model with a threshold of 7 , compared to 0.42 and 0.36 for a ‐based and ‐based model, respectively. Higher chosen LET thresholds typically performed better and lower performed worse.

Conclusion

The results indicate that models based on dirty dose metrics perform equally well as conventional radiation quality metrics. Due to the simplified calculations involved and the potential for more efficient measurement techniques for data generation, dirty dose‐based models might be the most conservative and practical approach for creating future proton variable RBE models.
Commercialism and Inter‐Industry Pay Differentials in the US Nonprofit Sector
Authors: Cui Tracy Shicun
Published: November 2024

While the wage dispersion across industries persists for long, it has yet to be adequately explained. Focusing on the nonprofit sector, this study examines the effect of commercialism on pay at the industry level with nationally representative data from the perspective of institutional theory and management. I first constructed a factor to measure commercialism at the industry level with data from IRS Form 990. Then I modeled the net effect of commercialism on pay by using cross‐classified multilevel modeling to control effects at occupation, state, and individual levels. The findings show that commercialism increases pay at the industry level and widens pay gaps between managers and nonmanagerial staff. With multilevel modeling, the study closes the gap of the micro–macro divide in pay studies, provides an additional interpretation of compensating wage theory, and supplements empirical evidence to the debate about the impact of nonprofit commercialism.
A dominant negative Kcnd3 F227del mutation in mice causes spinocerebellar ataxia type 22 (SCA22) by impairing ER and Golgi functioning
Authors: Hung Hao‐Chih , Lin Jia‐Han , Teng Yuan‐Chi , Kao Cheng‐Heng , Wang Pei‐Yu , Soong Bing‐Wen , Tsai Ting‐Fen
Published: November 2024

Spinocerebellar ataxia type 22 (SCA22) caused by KCND3 mutations is an autosomal dominant disorder. We established a mouse model carrying the Kcnd3 F227del mutation to study the molecular pathogenesis. Four findings were pinpointed. First, the heterozygous mice exhibited an early onset of defects in motor coordination and balance which mirror those of SCA22 patients. The degeneration and a minor loss of Purkinje cells, together with the concurrent presence of neuroinflammation, as well as the previous finding on electrophysiological changes, may all contribute to the development of the SCA22 ataxia phenotype in mice carrying the Kcnd3 F227del mutant protein. Second, the mutant protein is retained by the endoplasmic reticulum and Golgi, leading to activation of the unfolded protein response and a severe trafficking defect that affects its membrane destination. Intriguingly, profound damage of the Golgi is the earliest manifestation. Third, analysis of the transcriptome revealed that the Kcnd3 F227del mutation down‐regulates a panel of genes involved in the functioning of synapses and neurogenesis which are tightly linked to the functioning of Purkinje cells. Finally, no ataxia phenotypes were detectable in knockout mice carrying a loss‐of‐function Kcnd3 mutation. Thus, Kcnd3 F227del is a dominant‐negative mutation. This mouse model may serve as a preclinical model for exploring therapeutic strategies to treat patients. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
A theoretical systems chronopharmacology approach for COVID‐19: Modeling circadian regulation of lung infection and potential precision therapies
Authors: Tseng Yu‐Yao
Published: November 2024

The COVID‐19 pandemic, caused by SARS‐CoV‐2, has underscored the urgent need for innovative therapeutic approaches. Recent studies have revealed a complex interplay between the circadian clock and SARS‐CoV‐2 infection in lung cells, opening new avenues for targeted interventions. This systems pharmacology study investigates this intricate relationship, focusing on the circadian protein BMAL1. BMAL1 plays a dual role in viral dynamics, driving the expression of the viral entry receptor ACE2 while suppressing interferon‐stimulated antiviral genes. Its critical position at the host‐pathogen interface suggests potential as a therapeutic target, albeit requiring a nuanced approach to avoid disrupting essential circadian regulation. To enable precise tuning of potential interventions, we constructed a computational model integrating the lung cellular clock with viral infection components. We validated this model against literature data to establish a platform for drug administration simulation studies using the REV‐ERB agonist SR9009. Our simulations of optimized SR9009 dosing reveal circadian‐based strategies that potentially suppress viral infection while minimizing clock disruption. This quantitative framework offers insights into the viral‐circadian interface, aiming to guide the development of chronotherapy‐based antivirals. More broadly, it underscores the importance of understanding the connections between circadian timing, respiratory viral infections, and therapeutic responses for advancing precision medicine. Such approaches are vital for responding effectively to the rapid spread of coronaviruses like SARS‐CoV‐2.
Statistical Procedure for Panel Block Assembly in Shipbuilding
Authors: Otero Deborah , Cao Ricardo , Blasco Vicente , Brage Álvaro , Tarrío‐Saavedra Javier , Naya Salvador
Published: November 2024

A statistical procedure to estimate the probability of successful sliding of transverse elements through the longitudinals in shipbuilding panel block assembly is proposed. It consists of developing a custom statistical solution to control the quality of shipbuilding block assembly process, which helps to meet the requirements of production time, cost, and resources consumption. This proposal addresses a critical shipbuilding challenge: the panel block assembly process, which involves inserting transverse pieces through panels containing longitudinal components. This statistical procedure estimates the probability of successful block assembly before the process starts, taking into account inputs such as panel dimensions, panel structure, and transverse stiffener. A comprehensive simulation study has been performed to evaluate the statistical procedure performance. In addition, an actual database obtained from Navantia shipyards has been used to obtain information about the mean values and dispersion of the block assembly parameters. Finally, a sensitivity analysis is applied in order to obtain information about the most critical inputs for process improvement. This statistical tool proposes an alternative to evaluate the proficiency of shipyards to perform panel block assembly process during the vessel construction. The identification of those critical variables in the panel assembly process and the quantification of their influence in the studied process are goals that have been also achieved.
A Q‐Learning and Fuzzy Logic Control of Hybrid Energy Storage System Using Two Stage Low‐Pass Filter to Smooth Power Fluctuations in Microgrid
Authors: Rajabinezhad Mohamadamin , Mirafzal Behrooz , Fateh Fariba , Zuo Shan
Published: November 2024

The intermittent and fluctuating nature of wind turbine output power is increasingly being recognized as a significant issue adversely impacting the power quality and stability of electrical grids. With the increasing integration of wind power, this challenge cannot be underestimated. However, a potential solution for mitigating the adverse effects of such fluctuations lies in the Hybrid Energy Storage System (HESS), which encompasses battery energy storage systems (BESS) and supercapacitors (SC). The HESS is equipped with flexible operational modes for charging and discharging, thus enabling grid‐connected microgrids to possess the ability to counteract these oscillations. In this article, a control strategy based on the combination of Q‐learning and fuzzy logic control approaches is presented for tuning the parameters of a utilized two‐stage variable time constant low‐pass filter (LPF) in a grid‐connected microgrid. The proposed strategy adaptively tunes the time constants of LPFs to mitigate wind power fluctuations. Furthermore, practical constraints for the energy storage systems and their interfaced converters, such as preventing overcharge/discharge, ramp rate requirements, and certain maximum power conversion ranges, have been taken into account. Numerical simulation results verify the effectiveness of the proposed two‐stage variable time constant LPF for output wind power fluctuation reduction considering practical constraints of HESS.
Immersions of Directed Graphs in Tournaments
Authors: Girão António , Hancock Robert
Published: November 2024

Recently, Draganić, Munhá Correia, Sudakov and Yuster (2022) showed that every tournament on vertices contains a 1‐subdivision of a transitive tournament on vertices, which is tight up to a constant factor. We prove a counterpart of their result for immersions. Let be the smallest integer such that any tournament on at least vertices must contain a 1‐immersion of a transitive tournament on vertices. We show that , which is clearly tight up to a multiplicative factor. If one insists on finding an immersion of a complete directed graph on vertices, then an extra condition on the tournament is necessary. Indeed, we show that every tournament with minimum out‐degree at least must contain a 2‐immersion of a complete digraph on vertices. This is again tight up to the value of and tight on the order of the paths in the immersion.
Statistical Inference for Counting Processes Under Shape Heterogeneity
Authors: Sheng Ying , Sun Yifei
Published: November 2024

Proportional rate models are among the most popular methods for analyzing recurrent event data. Although providing a straightforward rate‐ratio interpretation of covariate effects, the proportional rate assumption implies that covariates do not modify the shape of the rate function. When the proportionality assumption fails to hold, we propose to characterize covariate effects on the rate function through two types of parameters: the shape parameters and the size parameters. The former allows the covariates to flexibly affect the shape of the rate function, and the latter retains the interpretability of covariate effects on the magnitude of the rate function. To overcome the challenges in simultaneously estimating the two sets of parameters, we propose a conditional pseudolikelihood approach to eliminate the size parameters in shape estimation, followed by an event count projection approach for size estimation. The proposed estimators are asymptotically normal with a root‐ convergence rate. Simulation studies and an analysis of recurrent hospitalizations using SEER‐Medicare data are conducted to illustrate the proposed methods.
A Computational Approach: Predicting iNOS Inhibition of Compounds for Alzheimer's Disease Treatment Through QSAR Modeling
Authors: Mariwan Ahmed Shkar , Tugcu Gulcin , Köksal Meric
Published: November 2024

This article presents the development of a quantitative structure‐activity relationship (QSAR) model for predicting the inhibitory activity of inducible nitric oxide synthase (iNOS) by specific compounds used in Alzheimer's disease treatment. iNOS is a vital enzyme involved in nitric oxide (NO) production, contributing to neuroinflammation and neuronal damage in Alzheimer's disease. The QSAR model was developed using a dataset of 90 compounds with known iNOS inhibition activity. Molecular descriptors representing the compounds’ structural and physicochemical properties were calculated and employed as input variables. Five descriptors (MATS6p, Chi1_EA(dm), Mor17 s, NsssCH, and SHED_AL) were selected as optimal for developing the classification model. The Random Forest algorithm was chosen as the classifier, implemented using WEKA software. The model underwent rigorous internal and external validation to assess its performance. The resulting QSAR model exhibited outstanding predictive capabilities with an overall accuracy of 88.8 %, a high correlation coefficient, and minimal prediction errors. It effectively forecasts iNOS inhibition activity of the chosen compounds, offering valuable insights for potential Alzheimer's disease treatments. This model significantly contributes to drug discovery, providing a rapid and cost‐effective means of screening and prioritizing compounds with iNOS inhibitory potential.
Investigating the Tyrosinase Inhibitory Activity of 4‐Bromobenzoic Acid Hydrazone‐Schiff Bases: In Vitro, Molecular Structure and Docking Studies
Authors: Alam Faima , Ismail Muhammad , Kamal Masroor , Ur Rahman Fayaz , Alam Aftab , AlAsmari Abdullah F. , Alasmari Fawaz , Khan Momin
Published: November 2024

Fourteen hydrazone‐Schiff base derivatives bearing 4‐bromobenzoic acid have been successfully synthesized, characterized by means of 1H‐NMR and EI‐MS spectrometry and finally evaluated for in vitro tyrosinase inhibitory activity. Among the series, five compounds 2 g, 2 k, 2 d, 2 c, and 2 n attributed potent tyrosinase inhibitors with IC50 values ranging from (IC50=6.07±0.40 μM) to (IC50=13.15±0.09 μM) surpassing the standard drug kojic acid (IC50=16.9±1.30 μM). Furthermore, the remaining compounds demonstrated significant to less inhibition. The density functional theory (DFT) study was performed to investigate various electronic properties such as geometry optimization, global reactivity parameter, frontier molecular orbitals (FMOs), molecular electrostatic potential map (MEPM), theoretical 1H‐NMR chemical shift, and nonlinear optical properties (NLO). Theoretical study shows good agreement with experimental study and NLO analysis suggest that the targeted compounds are good candidates with nonlinear optics. Furthermore, the docking studies were executed on the synthesized derivatives in order to explain the binding interface of compounds with the active sites of tyrosinase enzyme. The potent compounds observed in the current work may lead them promising candidates for future drug development.