bluuebunny/crossref_metadata_2025 huggingface dataset:
Taguchi-TOPSIS based optimization of comfort in compression stockings for vascular disorders
Authors: Nadeem Muhammad , Jamshaid Hafsa , Mishra Rajesh , Ahmed Naseer , Chandan Vijay , Jirku Petr , Kolar Viktor , Muller Miroslav
Published: September 2023

Compression stockings/socks are one of the most essential materials to treat vascular disorders in veins. However, the comfort of wearing such stockings over prolonged period of time is a major problem. There is limited research in the area of comfort optimization while retaining the compressional performance. The current work is carried out with an aim to determine the optimum level of the input factors e.g., knitting structure, plaiting yarn linear density and main yarn linear density for achieving desired stretch recovery percentage and thermo-physiological comfort properties of compression socks used in treatment of vascular disorders. Their optimum combination was determined by using Taguchi based techniques for order of preference by similarity to ideal solution i.e., TOPIS. In this study, thickness, areal density, air permeability, thermal resistance, over all moisture management capacity (OMMC), stretch and recovery % were optimized simultaneously by using Taguchi-TOPSIS method. The results showed that linear density of plaiting and main yarn has significant influence on all the comfort related properties for compression stockings/socks. The optimum sample had linear density 20 denier for Lycra covered by 70 denier of nylon 66 in the plaiting yarn. It also suggested 120 denier nylon 66 in the main yarn knitted into a plain single jersey structure. The percentage contribution of the factors i.e., structure, plaiting yarn linear density and main yarn linear density was obtained by using ANOVA which are 7%, 31% and 42% respectively. It is worth mentioning that in case of compression stockings, the main yarn linear density has more significant effect on comfort properties as compared to other independent parameters. The results were verified by experiment, and the accuracy was relatively high (maximum error 8.533%). This study helped to select suitable knit structure with the change of linear densities of plaiting yarn and main yarn for comfortable compression stocking/sock and will fulfill the potential requirement for treatment of venous/vascular disorders. The novel methodology involving TOPSIS method helped in analyzing the cumulative contribution of the input parameters to achieve optimum compression as well as comfort performance. This modern approach is based on contemporary scientific principles and statistical approximations. This study may provide benchmark solutions to complex problems involving multiple interdependent criteria.
Node deployment optimization of underwater wireless sensor networks using intelligent optimization algorithm and robot collaboration
Authors: Zhang Yangmei , Liu Zhouzhou , Bi Yang
Published: September 2023

This study aims to optimize the node deployment of underwater wireless sensor networks (UWSNs) using intelligent optimization algorithms and robot collaboration technology to enhance network performance and coverage. The study employs the chemical reaction optimization (CRO) algorithm, which combines the advantages of genetic algorithms, simulated annealing algorithms, and ant colony algorithms. The CRO algorithm is enhanced through a structure correction function to determine the optimal node deployment scheme to achieve effective and optimal coverage control of the UWSN. Additionally, the flexibility and autonomy of robots are leveraged to improve the efficiency of node deployment and address the unique challenges posed by the underwater environment. Furthermore, the study conducts a comparative analysis of different intelligent optimization algorithms and demonstrates the effectiveness and advantages of the enhanced CRO algorithm in optimizing node deployment for UWSNs. The study findings reveal that the improved algorithm achieves an average coverage rate of 95.66%, significantly outperforming traditional intelligent optimization algorithms. The coverage of UWSNs can be significantly improved by utilizing the enhanced CRO algorithm and robot collaboration technology for node deployment optimization, which offers an effective approach for achieving optimal node deployment. Moreover, the rational deployment of nodes enhances the monitoring capability, resource utilization efficiency, and accuracy of environmental monitoring in underwater networks. The results of this study hold great practical significance for underwater environment monitoring, marine resource exploration, and marine scientific research.
Rapid, tunable, and multiplexed detection of RNA using convective array PCR
Authors: Sullivan Andrew T. , Rao Vibha , Rockwood Tyler , Gandhi Jahnavi , Gruzka Sarah , O’Connor Logan , Wang Bonnie , Ragan Katherine B. , Zhang David Yu , Khodakov Dmitriy
Published: September 2023

Detection of RNA targets is typically achieved through RT-qPCR or RNAseq. RT-qPCR is rapid but limited in number and complexity of targets detected, while RNAseq is high-throughput but takes multiple days. We demonstrate simultaneous amplification and detection of 28 distinct RNA targets from a single unsplit purified RNA sample in under 40 minutes using our convective array PCR (caPCR) technology. We integrate tunable strand displacement probes into caPCR to allow detection of RNA species with programmable sequence selectivity for either a single, perfectly matched target sequence or for targets with up to 2 single-nucleotide variants within the probe-binding regions. Tunable probes allow for robust detection of desired RNA species against high homology background sequences and robust detection of RNA species with significant sequence diversity due to community-acquired mutations. As a proof-of-concept, we experimentally demonstrated detection of 7 human coronaviruses and 7 key variants of concern of SARS-CoV-2 in a single assay.
Repurposing of Ibrutinib and Quizartinib as potent inhibitors of necroptosis
Authors: Huang Fangmin , Liang Jiankun , Lin Yingying , Chen Yushi , Hu Fen , Feng Jianting , Zeng Qiang , Han Zeteng , Lin Qiaofa , Li Yan , Li Jingyi , Wu Lanqin , Li Lisheng
Published: September 2023

Necroptosis is a form of regulated cell death that has been implicated in multiple diseases. TNF-induced necroptosis is regulated by necrosomes, complexes consisting of RIPK1, RIPK3 and MLKL. In this study, by screening of a small-compound library, we identified dozens of compounds that inhibited TNF-induced necroptosis. According to the mechanisms by which they inhibited necroptosis, these compounds were classified into different groups. We then identified Ibrutinib as an inhibitor of RIPK3 and found that Quizartinib protected against the TNF-induced systemic inflammatory response syndrome in mice by inhibiting the activation of RIPK1. Altogether, our work revealed dozens of necroptosis inhibitors, suggesting new potential approaches for treating necroptosis-related diseases.
Oncometabolite D-2-hydroxyglutarate—dependent metabolic reprogramming induces skeletal muscle atrophy during cancer cachexia
Authors: Zhu Xinting , Hao Juan , Zhang Hong , Chi Mengyi , Wang Yaxian , Huang Jinlu , Xu Rong , Xincai Zhao , Xin Bo , Sun Xipeng , Zhang Jianping , Zhou Shumin , Cheng Dongdong , Yuan Ting , Ding Jun , Zheng Shuier , Guo Cheng , Yang Quanjun
Published: September 2023

Cancer cachexia is characterized by weight loss and skeletal muscle wasting. Based on the up-regulation of catabolism and down-regulation of anabolism, here we showed genetic mutation-mediated metabolic reprogramming in the progression of cancer cachexia by screening for metabolites and investigating their direct effect on muscle atrophy. Treatment with 93 μM D-2-hydroxyglutarate (D2HG) resulted in reduced myotube width and increased expression of E3 ubiquitin ligases. Isocitrate Dehydrogenase 1 (IDH1) mutant patients had higher D2HG than non-mutant patients. In the in vivo murine cancer cachexia model, mutant IDH1 in CT26 cancer cells accelerated cachexia progression and worsened overall survival. Transcriptomics and metabolomics revealed a distinct D2HG-induced metabolic imbalance. Treatment with the IDH1 inhibitor ivosidenib delayed the progression of cancer cachexia in murine GL261 glioma model and CT26 colorectal carcinoma models. These data demonstrate the contribution of IDH1 mutation mediated D2HG accumulation to the progression of cancer cachexia and highlight the individualized treatment of IDH1 mutation associated cancer cachexia.
Anomaly detection speed-up by quantum restricted Boltzmann machines
Authors: Moro Lorenzo , Prati Enrico
Published: September 2023

Quantum machine learning promises to revolutionize traditional machine learning by efficiently addressing hard tasks for classical computation. While claims of quantum speed-up have been announced for gate-based quantum computers and photon-based boson samplers, demonstration of an advantage by adiabatic quantum annealers (AQAs) is open. Here we quantify the computational cost and the performance of restricted Boltzmann machines (RBMs), a widely investigated machine learning model, by classical and quantum annealing. Despite the lower computational complexity of the quantum RBM being lost due to physical implementation overheads, a quantum speed-up may arise as a reduction by orders of magnitude of the computational time. By employing real-world cybersecurity datasets, we observe that the negative phase on sufficiently challenging tasks is computed up to 64 times faster by AQAs during the exploitation phase. Therefore, although a quantum speed-up highly depends on the problem’s characteristics, it emerges in existing hardware on real-world data.
300-Gbps optical interconnection using neural-network based silicon microring modulator
Authors: Hu Fangchen , Zhang Yuguang , Zhang Hongguang , Li Zhongya , Xing Sizhe , Shi Jianyang , Zhang Junwen , Xiao Xi , Chi Nan , He Zhixue , Yu Shaohua
Published: September 2023

Silicon microring modulators (Si-MRM) are critical components for high-performance electro-optical (E-O) signal conversion at optical interconnections due to their ultrawide bandwidth. However, the current transmission speed at the interconnections is still limited to 240 Gbps because of the low spectral-efficiency, as a result of the inherent modulation nonlinearity of Si-MRMs. Here, we theoretically analyse the modulation nonlinearity of a depletion-mode Si-MRM. Based on the analytical results, we further propose a physics-inspired neural network, named as bidirectional gate recurrent unit (Bi-GRU) to mitigate the signal distortion in Si-MRMs. Bi-GRU matches the analytical E-O modulation dynamics within Si-MRMs, thus can accurately capture the impairment features and accelerate the data transmission speed. We then fabricate a Si-MRM with −3dB E-O bandwidth of 42.5 GHz, achieving an ultrahigh speed optical interconnection with a data rate of 302 Gbps. The maximum spectral-efficiency of modulated signals is improved to 5.20 bit/s/Hz. The results provide insights to develop ultrahigh-speed Si-MRM using emerging AI techniques.
Preparation and application of carbon quantum dot fluorescent probes combined with rare earth ions
Authors: Xu Xiaoyi , Min Hua , Li Ying
Published: September 2023

Synthesis Strategies of fluorescent probes based on RE-CQDs.
Aurivillius-layered Bi2WO6 nanoplates with CoOx cocatalyst as high-performance piezocatalyst for hydrogen evolution
Authors: Tan Lining , Sun Xinran , Zhang Jintao , Jin Chengchao , Wang Fei , Liu Daiming
Published: September 2023

In water with methanol (MeOH) as hole scavenger, the loading of CoOx cocatalysts can facilitate the transfer of holes from Bi2WO6 (BWO) to CoOx, which are then quickly consumed by MeOH, resulting in the boosted piezocatalytic HER efficiency.
Effects of proton tunneling distance on CO2 reduction by Mn terpyridine species
Authors: Qing Yuhang , Wu Qianqian , He Shuanglin , Zhang Ping , Xiong Ying , Zhang Yaping , Huang Fang , Li Fei , Chen Lin
Published: September 2023

The shorter proton tunneling distance from the pendent amide to the carboxylate (Mn-CO2) in 1 is more beneficial for the pre-equilibrium kinetics of CO2 binding and the cleavage of the CO bond, leading to higher rate of CO2-to-CO conversion than 2.
Development of high methanol-tolerance Pichia pastoris based on iterative adaptive laboratory evolution
Authors: Wang Shuai , Wang Yuanyuan , Yuan Qingyan , Yang Liu , Zhao Fengguang , Lin Ying , Han Shuangyan
Published: September 2023

High methanol-tolerant strains were obtained using iterative adaptive laboratory evolution (microbial microdroplet culture (MMC) and shake flask culture (SFC)).
The importance of second sphere interactions on single molecule magnet performance
Authors: Matheson Brodie E. , Dais Tyson N. , Donaldson Marryllyn E. , Rowlands Gareth J. , Plieger Paul G.
Published: September 2023

Secondary interactions occur beyond the primary coordination sphere and can influence the performance of single molecule magnets (SMMs). This article highlights the role that secondary interactions play in the synthesis and performance of SMMs.
Transition metal ion-doped cesium lead halide perovskite nanocrystals: doping strategies and luminescence design
Authors: Zhang Yunqin , Tu Datao , Wang Luping , Li Chenliang , Liu Yuhan , Chen Xueyuan
Published: September 2023

We herein briefly review the recent advances in transition metal ion-doped cesium lead halide perovskite nanocrystals including the typical strategies for effective doping and optical properties manipulation.
Transport phenomena in solid phase synthesis supported by cross-linked polymer beads
Authors: Pinzón-López Sebastián , Kraume Mathias , Danglad-Flores José , Seeberger Peter H.
Published: September 2023

Transport phenomena in solid phase synthesis.
Cleaning steel by devulcanizing rubber from used automotive tires
Authors: Chen Yang , Ibrahim Saleh , Zheng Sijia , Wittenberg Liam , Chapple Spencer , LaChapelle Griffin , Iao Cheok Hang , Bourke Adam , Brook Michael A.
Published: September 2023

Steel from used automobile tires can be rendered suitable for recycling by stripping rubber contamination using reductive silylation with silicones.
Voltage rise rate‐related generalised probabilistic lifetime model of turn‐to‐turn insulation in inverter‐fed motors
Authors: Yang Yan , Bai Xueyang , Lei Yuxing , Liu Kai , Wu Guangning
Published: September 2023

The lifetime model of turn‐to‐turn insulation in inverter‐fed motors is studied. A lifetime model has been built by considering the effect of inverter‐generated high voltage rise rate (dv/dt up to 20 V/ns). This model is followed by the generalised probabilistic model, in which the lifetime is proportional to the nth power of the voltage rise rate. Moreover, by investigating the effect of voltage rise rate on the partial discharge characteristics, it is found that the effect of voltage rise rate on the charge transport process in a voltage cycle is similar to that of the voltage amplitude. The enhanced partial discharge activity and induced charges are responsible for accelerated ageing and thus determine the final lifetime of turn‐to‐turn insulation. In this case, the generalised probabilistic electric lifetime model is applicable to the voltage rise rate as well as the voltage amplitude.
Exploring the Red Supergiant wind kink
Authors: Vink Jorick S. , Sabhahit Gautham N.
Published: September 2023

Red supergiants (RSG) are key objects in studying the evolution of massive stars and their endpoints, but uncertainties related to their underlying mass-loss mechanism have stood in the way of an appropriate framework for massive star evolution thus far. In this work, we analyse a recently uncovered empirical mass-loss “kink” feature and we highlight its similarity to hot star radiation-driven wind models and observations at the optically thin-to-thick transition point. We motivate a new RSG mass-loss prescription that depends on the Eddington factor, Γ, (including both a steep luminosity, L, dependence and an inverse steep mass, Mcur, dependence). We subsequently implement this new RSG mass-loss prescription in the stellar evolution code MESA. We find that our physically motivated mass-loss behaviour naturally reproduces the Humphreys-Davidson limit without the need for any ad hoc tweaks. It also resolves the RSG supernova “problem”. We argue that a universal behaviour that is seen for radiation-driven winds across the HR diagram, independent of the exact source of opacity, is a key feature of the evolution of the most massive stars.
General theory of data, artificial intelligence and governance
Authors: de Pedraza Pablo , Vollbracht Ian
Published: September 2023

Big Data (BD) and Artificial Intelligence (AI) play a fundamental role in today’s economy that traditional economic models fail to capture. This paper presents a theoretical conceptualisation of the data economy and derives implications for digital governance and data policies. It defines a hypothetical data-intensive economy where data are the main input of AI and in which the amount of knowledge generated is below the socially desired amount. Intervention could consist of favouring the creation of additional knowledge via data sharing. We show that the framework suggested describes many features of today’s data-intensive economy and provides a tool to assist academic, policy and governance discussions. Our conclusions support data sharing as a way of increasing knowledge production on societal challenges and dilemmas of data capitalism and transparency in AI.
Cloud cover and expected oil returns
Authors: Hao Xianfeng , Wang Yudong
Published: September 2023

Satellites can “sense” oil inventory, but cloud cover prevents observation, which reduces the flow of information into the oil market and creates uncertainty about information availability. The effects of the availability of such information on oil prices need to be thoroughly explored. Therefore, using time-series prediction, this paper examines the effects of the availability of satellite-based information on oil returns. The cloud cover above the floating roof tanks in major oil storage areas is measured to predict oil returns through regression approaches. The empirical results indicate that higher cloudiness in a week leads to lower oil returns in the following week. The predictive ability of cloudiness is significant from both in-sample and out-of-sample perspectives. The ability of cloudiness measures to predict oil returns can be explained by information uncertainty and information flow channels. The findings have important implications for asset pricing and risk management using big data.
Effects of rapid cold-hardening and cold acclimation on egg survival and cryoprotectant contents in Ceracris kiangsu (Orthoptera: Arcypteridae)
Authors: Zhao Qian , Zhu Dao-Hong
Published: September 2023

The bamboo grasshopper, Ceracris kiangsu Tsai, is a serious pest of bamboo in China and Southeast Asia, and it overwinters as eggs for a period of up to 9 mo. Despite its importance, cold tolerance has not been thoroughly examined in this species. Thus, the present study investigated the low-temperature tolerance of overwintering eggs collected in the field, particularly the effects of rapid cold-hardening (RCH) and cold acclimation (ACC) on egg survival, and changes in the cryoprotectant contents. The supercooling point of overwintering eggs collected from the field was −23.9 °C, and their survival rate after exposure to −22 °C for 6 h was 26.6%, thereby suggesting that the cold tolerance strategy employed by C. kiangsu is freeze avoidance. After exposure to 0 and 4 °C for 12 and 24 h, or 0, 4, and 8 °C for 5 days, the survival rate of eggs subjected to −22 °C increased to approximately 50%, with significant effects of RCH and ACC. The glycerol levels in RCH and ACC treated eggs were also significantly higher than those in the control group, but the protein and trehalose contents were either reduced or not significantly altered. These results indicate that glycerol functions as a low molecular weight cryoprotectant in C. kiangsu eggs, and that RCH and ACC treatment facilitate its accumulation, thereby enhancing cold tolerance. Furthermore, the correlation between RCH and ACC was investigated.
The effectiveness of community-based palliative care programme components: a systematic review
Authors: Hughes M Courtney , Vernon Erin , Hainstock Allison
Published: September 2023

Background

There is evidence that community-based palliative care programmes can improve patient outcomes and caregiver experiences cost-effectively. However, little is known about which specific components within these programmes contribute to improving the outcomes.

Aim

To systematically review research that evaluates the effectiveness of community-based palliative care components.

Design

A systematic mixed studies review synthesising quantitative, qualitative and mixed-methods study findings using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PROSPERO: ID # CRD42022302305.

Data sources

Four databases were searched in August 2021 (CINAHL, Web of Science, ProQuest Federated and PubMed including MEDLINE) and a close review of included article references. Inclusion criteria required articles to evaluate a single, specific component of a community-based palliative care programme either within an individual programme or across several programmes.

Results

Overall, a total of 1,674 articles were identified, with 57 meeting the inclusion criteria. Of the included studies, 21 were qualitative, 25 were quantitative and 11 had mixed methods. Outcome measures consistently examined included patient/caregiver satisfaction, hospital utilisation and home deaths. The components of standardised sessions (interdisciplinary meetings about patients), volunteer engagement and early intervention contributed to the success of community-based palliative care programmes.

Conclusions

Certain components of community-based palliative care programmes are effective. Such components should be implemented and tested more in low- and middle-income countries and key and vulnerable populations such as lower-income and marginalised racial or ethnic groups. In addition, more research is needed on the cost-effectiveness of individual programme components.
Interventions for reducing anticholinergic medication burden in older adults—a systematic review and meta-analysis
Authors: Braithwaite Eve , Todd Oliver M , Atkin Abigail , Hulatt Rachel , Tadrous Ragy , Alldred David P , Pirmohamed Munir , Walker Lauren , Lawton Rebecca , Clegg Andrew
Published: September 2023

Introduction

Anticholinergic medications block the neurotransmitter acetylcholine in the brain and peripheral nervous system. Many medications have anticholinergic properties, and the cumulative effect of these medications is termed anticholinergic burden. Increased anticholinergic burden can have short-term side effects such as dry mouth, blurred vision and urinary retention as well as long-term effects including dementia, worsening physical function and falls.

Methods

We carried out a systematic review (SR) with meta-analysis (MA) looking at randomised controlled trials addressing interventions to reduce anticholinergic burden in older adults.

Results

We identified seven papers suitable for inclusion in our SR and MA. Interventions included multi-disciplinary involvement in medication reviews and deprescribing of AC medications. Pooled data revealed no significant difference in outcomes between control and intervention group for falls (OR = 0.76, 95% CI: 0.52–1.11, n = 647), cognition (mean difference = 1.54, 95% CI: −0.04 to 3.13, n = 405), anticholinergic burden (mean difference = 0.04, 95% CI: −0.11 to 0.18, n = 710) or quality of life (mean difference = 0.04, 95% CI: −0.04 to 0.12, n = 461).

Discussion

Overall, there was no significant difference with interventions to reduce anticholinergic burden. As we did not see a significant change in anticholinergic burden scores following interventions, it is likely other outcomes would not change. Short follow-up time and lack of training and support surrounding successful deprescribing may have contributed.
‘Auspicious liaisons’—evaluating the impact of a liaison geriatrician initiative on older adults psychiatric wards
Authors: Swann Peter , Tolley Abraham , Paschalis Theodoros , Zahedi Daniel , Wong Heng C , Kirthisingha Viveca , Ruiz-Mendoza Eladia , Rubinsztein Judy
Published: September 2023

Background

Although liaison services in acute hospitals are now the norm, the reverse is not usually available for patients in mental health trusts. Following the introduction of support from geriatricians to older people’s mental health inpatient wards, we wanted to see if this intervention was effective and acceptable to clinicians.

Methods

We performed a retrospective cohort service evaluation on the impact of a liaison geriatrician, using routinely collected data, and assessed acceptability among medical staff by semi-structured interview.

Intervention

Our service introduced regular sessions from consultant community geriatricians across older adults psychiatric wards including a mixture of video conference and face-to-face input.

Results

There was no significant decrease in emergency transfers but there was a significant reduction in length of stay with an associated cost benefit for the service after the introduction of a liaison geriatrician. There was a significant increase in geriatrician consultations and a decrease in specialty consultations to other specialists. There was no change in discharge prescriptions or destination. There was a significant reduction in falls in the intervention arm but not in falls leading to emergency hospital admissions geriatricians gave confidence to psychiatrists of all grades to treat physical health care issues.

Conclusions

A liaison geriatrician service may be a component in reducing length of stay (although there are many others) and improving continuity of care, although it confers no impact on emergency transfers. The intervention was highly acceptable to clinicians.
Physical compatibility of sulbactam/durlobactam with select intravenous drugs during simulated Y-site administration
Authors: Ruiz Victor H , Shen Yuwei , Abouelhassan Yasmeen , Fouad Aliaa , Nicolau David P , Kuti Joseph L
Published: September 2023

Purpose

Sulbactam/durlobactam is a combination antibiotic designed to target Acinetobacter baumannii, including carbapenem-resistant and multidrug-resistant strains. The objective of this study was to determine the physical compatibility of sulbactam/durlobactam solution during simulated Y-site administration with 95 intravenous (IV) drugs.

Methods

Vials of sulbactam/durlobactam solution were diluted in 0.9% sodium chloride injection to a volume of 100 mL (the final concentration of both drugs was 15 mg/mL). All other IV drugs were reconstituted according to the manufacturer’s recommendations and diluted with 0.9% sodium chloride injection to the upper range of concentrations used clinically or tested undiluted as intended for administration. Y-site conditions were simulated by mixing 5 mL of sulbactam/durlobactam with 5 mL of the tested drug solutions in a 1:1 ratio. Solutions were inspected for physical characteristics (clarity, color, and Tyndall effect), turbidity, and pH changes before admixture, immediately post admixture, and over 4 hours. Incompatibility was defined as any observed precipitation, significant color change, positive Tyndall test, or turbidity change of ≥0.5 nephelometric turbidity unit during the observation period.

Results

Sulbactam/durlobactam was physically compatible with 38 out of 42 antimicrobials tested (90.5%) and compatible overall with 86 of 95 drugs tested (90.5%). Incompatibility was observed with albumin, amiodarone hydrochloride, ceftaroline fosamil, ciprofloxacin, daptomycin, levofloxacin, phenytoin sodium, vecuronium, and propofol.

Conclusion

The Y-site compatibility of sulbactam/durlobactam with 95 IV drugs was described. These compatibility data will assist pharmacists and nurses to safely coordinate administration of IV medications with sulbactam/durlobactam.
Promoting Minority Language Use to Foster Revitalisation: Insights From New Speakers of West Frisian
Authors: Kircher Ruth , Kutlu Ethan , Vellinga Mirjam
Published: September 2023

Language planners are increasingly aware of the importance of new speakers (individuals acquiring a language outside the home, typically later-on in life) for the revitalisation of minority languages. Yet, little is known about new speakers’ activation (the process by which they become active and habitual minority language users). This article presents a questionnaire-based investigation of new speakers’ (n = 264) use of West Frisian in Fryslân, Netherlands—and the role traditional speakers play in new speakers’ activation. Qualitative and quantitative data show that participants use West Frisian only rarely; and when they do use it, it is mainly in the classroom. Minority language interactions outside the classroom, with traditional speakers, consist mostly of a few tokenistic words or phrases. The findings show to what extent different behaviours by traditional speakers discourage and/or encourage new speakers’ minority language use, highlighting how the complex dynamics between the speaker groups are hindering revitalisation efforts. The article discusses the implications of these findings for language planning to promote the activation of new speakers, and thereby the revitalisation of West Frisian.
A Call for Methodological Reflexivity in Researching Language Testing and Migration
Authors: Schildt Laura , Deygers Bart
Published: September 2023

A growing scholarly literature in a subfield of applied linguistics focuses on language testing and language requirements for migrants. We sought to understand what theoretical paradigms and methodological approaches have framed this research and propose future research directions. To this end, we conducted a systematic review of articles on language testing and migration published between 2001 and 2022 in the applied linguistics field. For each of the 46 studies which met inclusion/exclusion criteria, we randomly selected a control article from the same journals. Both the test corpus and the control corpus were double coded for theoretical and methodological characteristics and analysed using contingency tables, Mann–Whitney tests, and forward stepwise logistic regression to predict group membership. The findings revealed that literature on language testing and migration is highly reliant on critical theory and less reliant on features associated with empirical methods. We suggest that research in this domain would benefit from methodological reflexivity (i.e. questioning prevalent assumptions and employing theoretical variety) and that complementary approaches could lead to a more nuanced research consensus and promote research-policy collaboration.
Management of Lipedema Beyond Liposuction: A Case Study
Authors: Bouillon Victoria N , Hinson Chandler S , Hu MengJie , Brooks Ronald M
Published: September 2023

Lipedema is a pathologic accumulation of adipose tissue in the subcutaneous layer of the extremities. This connective tissue disorder, which predominately affects females, is often misdiagnosed despite an incidence of ∼11%. Misdiagnosis often leads to delays in appropriate treatment, further increasing the morbidity of the condition. The authors report their facilities' experience in treating a patient with lipedema, requiring multiple surgical interventions involving liposuction and skin debulking to achieve desired aesthetic outcomes. The patient presented to the plastic surgery clinic with severe lipedema of the bilateral lower extremities. She previously underwent a panniculectomy and bilateral lower extremity liposuction without achieving the desired aesthetic results. Prior conservative management and liposuction alone were both unsuccessful treatment options and she required debulking procedures, along with further liposuction, as definitive management. The patient underwent 2 procedures at the clinic, both consisting of liposuction and panniculectomy of the lower extremities and buttocks. The procedures were conducted 1 year apart but were able to achieve the patient's desired aesthetics goals. Management of lipedema can be challenging, but not impossible. This case report shows that local excision is a viable option for treatment if minimally invasive options yield limited results.

Level of Evidence: 5
Adaptive differentiable grids for cryo-electron tomography reconstruction and denoising
Authors: Wang Yuanhao , Idoughi Ramzi , Rückert Darius , Li Rui , Heidrich Wolfgang
Published: September 2023

Motivation

Tilt-series cryo-electron tomography is a powerful tool widely used in structural biology to study 3D structures of micro-organisms, macromolecular complexes, etc. Still, the reconstruction process remains an arduous task due to several challenges: The missing-wedge acquisition, sample misalignment and motion, the need to process large data, and, especially, a low signal-to-noise ratio.

Results

Inspired by the recently introduced neural representations, we propose an adaptive learning-based representation of the density field of the captured sample. This representation consists of an octree structure, where each node represents a 3D density grid optimized from the captured projections during the training process. This optimization is performed using a loss that combines a differentiable image formation model with different regularization terms: total variation, boundary consistency, and a cross-nodes non-local constraint. The final reconstruction is obtained by interpolating the learned density grid at the desired voxel positions. The evaluation of our approach using captured data of viruses and cells shows that our proposed representation is well adapted to handle missing wedges, and improves the signal-to-noise ratio of the reconstructed tomogram. The reconstruction quality is highly improved in comparison to the state-of-the-art methods, while using the lowest computing time footprint.

Availability and implementation

The code is available on Github at https://github.com/yuanhaowang1213/adaptivediffgrid_ex.
Atomistic simulations suggest dietary flavonoids from Beta vulgaris (beet) as promising inhibitors of human angiotensin-converting enzyme and 2-alpha-adrenergic receptors in hypertension
Authors: Adetunji Joy A , Ogunyemi Oludare M , Gyebi Gideon A , Adewumi Anuoluwapo E , Olaiya Charles O
Published: September 2023

Motivation

Beta vulgaris (beet) is extensively reported for its antihypertensive activity. However, the mechanismunderpinning its antihypertensive activity is not well understood. In this study, we evaluated the in silico interactionsof 70 compounds derived from beta vulgaris against the active sites of angiotensin-converting enzyme (ACE) and alpha-adrenergic receptor (AR).

Results

Structure-based virtual screening against angiotensin-converting enzyme revealed that, Cochliophilin A (−9.0 Kcal/mol), Miraxanthin (−8.3 Kcal/mol), and quercimeritrin (−9.7 Kcal/mol) had lower docking scores than the reference lisinopril (−7.9 Kcal/mol). These compounds exhibited dual binding tendency as they also ranked top compounds upon screening against adrenergic receptor. The thermodynamic parameters computed from the resulting trajectories obtained from the 100 ns full atomistic molecular dynamics simulation revealed structural stability and conformational flexibility of the ligand–receptor complexes as indicated by the RMSD, RMSF, RoG, SASA, and H-bond calculations. The molecular mechanics with generalized Born and surface area solvation binding energy calculations revealed that the proteins exhibit considerable binding energy with the phytochemicals in a dynamic environment. Furthermore, the hit compounds possess good physicochemical properties and drug-likeness. Overall, cochliophilin and quercimeritrin are promising dual-target directed flavonoids from Beta vulgaris; and are suggested for further experimental and preclinical evaluation.

Availability and implementation

All data was provided in the manuscript.
GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype
Authors: Jeong Dabin , Koo Bonil , Oh Minsik , Kim Tae-Bum , Kim Sun
Published: September 2023

Motivation

Asthma is a heterogeneous disease where various subtypes are established and molecular biomarkers of the subtypes are yet to be discovered. Recent availability of multi-omics data paved a way to discover molecular biomarkers for the subtypes. However, multi-omics biomarker discovery is challenging because of the complex interplay between different omics layers.

Results

We propose a deep attention model named Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network (GOAT) for identifying molecular biomarkers for eosinophilic asthma subtypes with multi-omics data. GOAT identifies genes that discriminate subtypes using a graph neural network by modeling complex interactions among genes as the attention mechanism in the deep learning model. In experiments with multi-omics profiles of the COREA (Cohort for Reality and Evolution of Adult Asthma in Korea) asthma cohort of 300 patients, GOAT outperforms existing models and suggests interpretable biological mechanisms underlying asthma subtypes. Importantly, GOAT identified genes that are distinct only in terms of relationship with other genes through attention. To better understand the role of biomarkers, we further investigated two transcription factors, CTNNB1 and JUN, captured by GOAT. We were successful in showing the role of the transcription factors in eosinophilic asthma pathophysiology in a network propagation and transcriptional network analysis, which were not distinct in terms of gene expression level differences.

Availability and implementation

Source code is available https://github.com/DabinJeong/Multi-omics_biomarker. The preprocessed data underlying this article is accessible in data folder of the github repository. Raw data are available in Multi-Omics Platform at http://203.252.206.90:5566/, and it can be accessible when requested.
Unbiased curriculum learning enhanced global-local graph neural network for protein thermodynamic stability prediction
Authors: Gong Haifan , Zhang Yumeng , Dong Chenhe , Wang Yue , Chen Guanqi , Liang Bilin , Li Haofeng , Liu Lanxuan , Xu Jie , Li Guanbin
Published: September 2023

Motivation

Proteins play crucial roles in biological processes, with their functions being closely tied to thermodynamic stability. However, measuring stability changes upon point mutations of amino acid residues using physical methods can be time-consuming. In recent years, several computational methods for protein thermodynamic stability prediction (PTSP) based on deep learning have emerged. Nevertheless, these approaches either overlook the natural topology of protein structures or neglect the inherent noisy samples resulting from theoretical calculation or experimental errors.

Results

We propose a novel Global-Local Graph Neural Network powered by Unbiased Curriculum Learning for the PTSP task. Our method first builds a Siamese graph neural network to extract protein features before and after mutation. Since the graph’s topological changes stem from local node mutations, we design a local feature transformation module to make the model focus on the mutated site. To address model bias caused by noisy samples, which represent unavoidable errors from physical experiments, we introduce an unbiased curriculum learning method. This approach effectively identifies and re-weights noisy samples during the training process. Extensive experiments demonstrate that our proposed method outperforms advanced protein stability prediction methods, and surpasses state-of-the-art learning methods for regression prediction tasks.

Availability and implementation

All code and data is available at https://github.com/haifangong/UCL-GLGNN.
Using a novel structure/function approach to select diverse swine major histocompatibility complex 1 alleles to predict epitopes for vaccine development
Authors: Khatooni Zahed , Teymourian Navid , Wilson Heather L
Published: September 2023

Motivation

Swine leukocyte antigens (SLAs) (i.e. swine major histocompatibility complex proteins) conduct a fundamental role in swine immunity. To generate a protective vaccine across an outbred species, such as pigs, it is critical that epitopes that bind to diverse SLA alleles are used in the vaccine development process. We introduced a new strategy for epitope prediction.

Results

We employed molecular dynamics simulation to identify key amino acids for interactions with epitopes. We developed an algorithm wherein each SLA-1 is compared to a crystalized reference allele with unique weighting for non-conserved amino acids based on R group and position. We then performed homology modeling and electrostatic contact mapping to visualize how relatively small changes in sequences impacted the charge distribution in the binding site. We selected eight diverse SLA-1 alleles and performed homology modeling followed, by protein–peptide docking and binding affinity analyses, to identify porcine reproductive and respiratory syndrome virus matrix protein epitopes that bind with high affinity to these alleles. We also performed docking analysis on the epitopes identified as strong binders using NetMHCpan 4.1. Epitopes predicted to bind to our eight SLA-1 alleles had equivalent or higher energetic interactions than those predicted to bind to the NetMHCpan 4.1 allele repertoire. This approach of selecting diverse SLA-1 alleles, followed by homology modeling, and docking simulations, can be used as a novel strategy for epitope prediction that complements other available tools and is especially useful when available tools do not offer a prediction for SLAs/major histocompatibility complex.

Availability and implementation

The data underlying this article are available in the online Supplementary Material.
DeepUMQA3: a web server for accurate assessment of interface residue accuracy in protein complexes
Authors: Liu Jun , Liu Dong , Zhang Gui-Jun
Published: September 2023

Motivation

Model quality assessment is a crucial part of protein structure prediction and a gateway to proper usage of models in biomedical applications. Many methods have been proposed for assessing the quality of structural models of protein monomers, but few methods for evaluating protein complex models. As protein complex structure prediction becomes a new challenge, there is an urgent need for model quality assessment methods that can accurately assess the accuracy of interface residues of complex structures.

Results

Here, we present DeepUMQA3, a web server for evaluating the accuracy of interface residues of protein complex structures using deep neural networks. For an input complex structure, features are extracted from three levels of overall complex, intra-monomer, and inter-monomer, and an improved deep residual neural network is used to predict per-residue lDDT and interface residue accuracy. DeepUMQA3 ranks first in the blind test of interface residue accuracy estimation in CASP15, with Pearson, Spearman, and AUC of 0.564, 0.535, and 0.755 under the lDDT measurement, which are 17.6%, 23.6%, and 10.9% higher than the second best method, respectively. DeepUMQA3 can also assess the accuracy of all residues in the entire complex and distinguish high- and low-precision residues.

Availability and implementation

The web sever of DeepUMQA3 are freely available at http://zhanglab-bioinf.com/DeepUMQA_server/.
Neoadjuvant chemotherapy for locally advanced colonic cancer is the standard of care
Authors: Morton Dion , Seligmann Jenny
Published: September 2023

Recently completed multi-national trials have demonstrated major patient benefits from neoadjuvant therapy from colon cancer. It is now timely to institute these treatment pathways in our MDTs for the benefit of our patients.
Soluble TREM2 triggers microglial dysfunction in neuromyelitis optica spectrum disorders
Authors: Qin Chuan , Chen Man , Dong Ming-Hao , Yang Sheng , Zhang Hang , You Yun-Fan , Zhou Luo-Qi , Chu Yun-Hui , Tang Yue , Pang Xiao-Wei , Wu Long-Jun , Tian Dai-Shi , Wang Wei
Published: September 2023

Microglia-mediated neuroinflammation contributes to acute demyelination in neuromyelitis optica spectrum disorders (NMOSD). Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in the CSF has been associated with microglial activation in several neurodegenerative diseases. However, the basis for this immune-mediated attack and the pathophysiological role of sTREM2 in NMOSD remain to be elucidated.

Here, we performed Mendelian randomization analysis and identified a genetic association between increased CSF sTREM2 and NMOSD risk. CSF sTREM2 was elevated in patients with NMOSD and was positively correlated with neural injury and other neuroinflammation markers. Single-cell RNA sequencing of human macrophage/microglia-like cells in CSF, a proxy for microglia, showed that increased CSF sTREM2 was positively associated with microglial dysfunction in patients with NMOSD. Furthermore, we demonstrated that sTREM2 is a reliable biomarker of microglial activation in a mouse model of NMOSD. Using unbiased transcriptomic and lipidomic screens, we identified that excessive activation, overwhelmed phagocytosis of myelin debris, suppressed lipid metabolism and enhanced glycolysis underlie sTREM2-mediated microglial dysfunction, possibly through the nuclear factor kappa B (NF-κB) signalling pathway.

These molecular and cellular findings provide a mechanistic explanation for the genetic association between CSF sTREM2 and NMOSD risk and indicate that sTREM2 could be a potential biomarker of NMOSD progression and a therapeutic target for microglia-mediated neuroinflammation.
Kū Kia‘i Kahuku: indigenizing social media, civic streaming, and sociospatial symmetry
Authors: Burroughs Benjamin , Ka‘ili Tēvita O
Published: September 2023

This research critiques Western approaches to social media by using an Indigenous theoretical tool/concept, the Moanan (Pacific Islander) conception of tā and vā, to center Indigenous knowledge through an analysis of the Kū Kiaʻi Kahuku community movement (an Indigenous and ecological stand for environmental justice to protect native species and push back against colonial development in the form of giant wind turbines (568 feet high) placed over schools and the homes of community members and Kanaka Maoli in Kahuku, Hawaiʻi). We argue that Kū Kiaʻi Kahuku’s livestreaming inspired movement within the space of digital connectivity, a civic rhythm, forging symmetry and reciprocity within sociospatial ties. Moanan peoples inscribed within social media a distinct Moanan rhythm. In this case, the vibrations of the protecting, an affectively charged tā, engaged the community and diaspora in a moment of rupture—opening up a space for symmetry within the dissymmetry of colonial capitalism.
Long-acting Injectable Cabotegravir/Rilpivirine Effective in a Small Patient Cohort With Virologic Failure on Oral Antiretroviral Therapy
Authors: Brock James B , Herrington Peyton , Hickman Melissa , Hickman Aubri
Published: September 2023

We report 12 patients with persistent viremia on oral antiretroviral therapy who were initiated on injectable cabotegravir/rilpivirine (iCAB/RPV) without oral lead-in. All patients achieved viral suppression without any virologic rebound. iCAB/RPV may be considered as an option for patients unable to maintain suppression on oral antiretroviral therapy.
More Than a Decade Since the Latest CONSORT Non-inferiority Trials Extension: Do Infectious Diseases Trials Do Enough?
Authors: Komorowski Adam S , Lo Carson K L , Kapoor Andrew K , Smieja Marek , Loeb Mark , Mertz Dominik , Bai Anthony D
Published: September 2023

More than a decade after the Consolidated Standards of Reporting Trials group released a reporting items checklist for non-inferiority randomized controlled trials, the infectious diseases literature continues to underreport these items. Trialists, journals, and peer reviewers should redouble their efforts to ensure infectious diseases studies meet these minimum reporting standards.