bluuebunny/crossref_metadata_2025 huggingface dataset:
Nurses’ Support of Treatment Decision-Making for Patients with Cancer During the COVID-19 Pandemic in Japan
Authors: Yoshida Shiori , Sasaki Konosuke , Sato Fumiko
Published: June 2024

During the COVID-19 pandemic, cancer patients became reluctant to come to the hospital, receive cancer treatment, and were willing to interrupt or postpone treatment due to concerns about infection. The purpose of this study was to discuss effective treatment strategy decision making support for cancer patients by nurses recognized during the COVID-19 pandemic. The study population comprised nurse of decision-making support at cancer care during COVID-19 from May to July 2021 at 49 the cancer care center hospitals were established in each prefecture, who had engaged 50% of their nursing care provided to patients with cancer.

Data were collected on treatment strategy decision-making support using an online cross-sectional survey. Factors that influenced patients’ decision-making were identified using multivariable logistic regression analysis. A total of 182 (25.0%) were nurses engaged in decision making were enrolled in this study. Factors that influenced patients’ decision to receive treatment to their satisfaction were their resignation or compromise in accepting the decision due to the pandemic (odds ratio [OR] 0.44 (95% CI [0.22, 0.87]), videoconference follow-up (OR 0.17, 95% Cl [0.04, 0.66]), and infection prevention information provision (OR 3.82, 95% Cl [1.54,9.46]). Factors influencing patients’ decision to give up and accept the doctor’s recommendation even though they were not convinced included fear of disease progression (OR 2.51, 95% Cl [1.21, 5.22]), anger at not receiving the treatment they desired (OR 2.48, 95% Cl [1.17, 5.27]), and compromise with the pandemic situation (OR 3.15, 95% Cl [1.53, 6.50]). The factor that influenced patients’ continued treatment even though they were not convinced included the nurse listened to the patients’ thoughts (OR 0.07, 95% Cl [0.01, 0.51]). Treatment decision support of patients with cancer during COVID-19 included lifestyle guidance to prevent the spread of infection and listening to their concerns to help them find meaning in their choices.
Koina: Democratizing machine learning for proteomics research
Authors: Lautenbacher Ludwig , Yang Kevin L. , Kockmann Tobias , Panse Christian , Chambers Matthew , Kahl Elias , Yu Fengchao , Gabriel Wassim , Bold Dulguun , Schmidt Tobias , Li Kai , MacLean Brendan , Nesvizhskii Alexey I. , Wilhelm Mathias
Published: June 2024

Recent developments in machine-learning (ML) and deep-learning (DL) have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML/DL models for various applications and peptide properties are frequently published, the rate at which these models are adopted by the community is slow, which is mostly due to technical challenges. We believe that, for the community to make better use of state-of-the-art models, more attention should be spent on making models easy to use and accessible by the community. To facilitate this, we developed Koina, an open-source containerized, decentralized and online-accessible high-performance prediction service that enables ML/DL model usage in any pipeline. Using the widely used FragPipe computational platform as example, we show how Koina can be easily integrated with existing proteomics software tools and how these integrations improve data analysis.
Lightweight taxonomic profiling of long-read metagenomic datasets with Lemur and Magnet
Authors: Sapoval Nicolae , Liu Yunxi , Curry Kristen , Kille Bryce , Huang Wenyu , Kokroko Natalie , Nute Michael G , Tyshaieva Alona , Dilthey Alexander T , Molloy Erin , Treangen Todd J
Published: June 2024

The advent of long-read sequencing of microbiomes necessitates the development of new taxonomic profilers tailored to long-read shotgun metagenomic datasets. Here, we introduce Lemur and Magnet, a pair of tools optimized for lightweight and accurate taxonomic profiling for long-read shotgun metagenomic datasets. Lemur is a marker-gene-based method that leverages an EM algorithm to reduce false positive calls while preserving true positives; Magnet is a whole-genome read mapping based method that provides detailed presence and absence calls for bacterial genomes. We demonstrate that Lemur and Magnet can run in minutes to hours on a laptop with 32 GB of RAM, even for large inputs, a crucial feature given the portability of long-read sequencing machines. Furthermore, the marker gene database used by Lemur is only 4 GB and contains information from over 300,000 RefSeq genomes. Lemur and Magnet are open-source and available at https://github.com/treangenlab/lemur and https://github.com/treangenlab/magnet.
FORECAST-RBD: Forecasting Phenoconversion Risks and Its Clinical Phenotype in Patients with Isolated RBD Using Machine Learning and Explainable AI
Authors: Shin Yong Woo , Byun Jung-Ick , Kim Han-Joon , Jung Ki-Young
Published: June 2024

Background and Objectives

Isolated Rapid Eye Movement (REM) sleep behavior disorder (iRBD) is a sleep disorder associated with neurodegenerative diseases such as Parkinson’s disease and dementia with Lewy bodies. Predicting which iRBD patients will phenoconvert to neurodegenerative diseases is crucial for prognosis and management. The objective of this study is to develop a machine learning model using clinical markers to predict phenoconversion in patients with RBD.

Methods

Analyzing a cohort of 178 iRBD patients over a median follow-up period of 3.6 years, during which 30 patients converted to neurodegenerative conditions, we leveraged an comprehensive dataset encompassing demographics, medication history, cognitive assessments, sleep quality, autonomic symptoms, and parkinsonian signs. We explored a variety of feature selection methods and survival models. Additionally, separate models to predict the subtype of photoconversion—whether motor-first or cognition-first—were developed.

Results

The extreme gradient boosting survival embeddings-Kaplan neighbors (XGBSE-KN) model demonstrated the best performance, achieving a concordance index of 0.823 and integrated Brier score of 0.123 on 10-fold cross-validation. Explainable AI methods provided insights into prediction rationales and key risk factors including age, RBDQ-KR factor 2 (behavioral factors), weight, antidepressant, coffee use, and UPDRS III excluding tremor score. For subtype classification, the RandomForestClassifier utilizing three features (PSQI-TST, MoCA, and age), emerged as the most effective, achieving a Matthews Correlation Coefficient of 0.697 in 100 repeated 5-fold cross-validations. These models have been deployed on a server for physician access.

Discussion

These models can aid prognosis and enable personalized management in RBD patients, potentially improving patient care and outcomes. While these findings are promising, further external validation of the models is necessary to confirm their efficacy and reliability in clinical settings. Future research should focus on incorporating additional biomarkers and exploring the models’ performance in larger, diverse cohorts.
Predicting Spatially Resolved Gene Expression via Tissue Morphology using Adaptive Spatial GNNs
Authors: Song Tianci , Cosatto Eric , Wang Gaoyuan , Kuang Rui , Gerstein Mark , Min Martin Renqiang , Warrell Jonathan
Published: June 2024

Motivation

Spatial transcriptomics technologies, which generate a spatial map of gene activity, can deepen the understanding of tissue architecture and its molecular underpinnings in health and disease. However, the high cost makes these technologies difficult to use in practice. Histological images co-registered with targeted tissues are more affordable and routinely generated in many research and clinical studies. Hence, predicting spatial gene expression from the morphological clues embedded in tissue histological images, provides a scalable alternative approach to decoding tissue complexity.

Results

Here, we present a graph neural network based framework to predict the spatial expression of highly expressed genes from tissue histological images. Extensive experiments on two separate breast cancer data cohorts demonstrate that our method improves the prediction performance compared to the state-of-the-art, and that our model can be used to better delineate spatial domains of biological interest.

Availability

https://github.com/song0309/asGNN/
Optimal sequencing depth for measuring the concentrations of molecular barcodes
Authors: Ocari Tommaso , Zin Emilia A. , Tekinsoy Muge , Van Meter Timothé , Cammarota Chiara , Dalkara Deniz , Nemoto Takahiro , Ferrari Ulisse
Published: June 2024

In combinatorial genetic engineering experiments, next-generation sequencing (NGS) allows for measuring the concentrations of barcoded or mutated genes within highly diverse libraries. When designing and interpreting these experiments, sequencing depths are thus important parameters to take into account. Service providers follow established guidelines to determine NGS depth depending on the type of experiment, such as RNA sequencing or whole genome sequencing. However, guidelines specifically tailored for measuring barcode concentrations have not yet reached an accepted consensus. To address this issue, we combine the analysis of NGS datasets from barcoded libraries with a mathematical model taking into account the PCR amplification in library preparation. We demonstrate on several datasets that noise in the NGS counts increases with the sequencing depth; consequently, beyond certain limits, deeper sequencing does not improve the precision of measuring barcode concentrations. We propose, as rule of thumb, that the optimal sequencing depth should be about ten times the initial amount of barcoded DNA before any amplification step.
Enrichment of glycoRNAs using galactose oxidase, hydrazide chemistry, and glycosidase digestion
Authors: Miao Xinyu , Deng Jianbo , Wang Xiaotong , Wen Sheng-Ye , Zhou Zeyang , Li Shuwei , Yang Xiaodong , Yang Shuang
Published: June 2024

Ribonucleic acid (RNA), essential for protein production and immune function, undergoes glycosylation, a process that attaches carbohydrates to RNA, creating unique glycoRNAs. These sugar-coated RNA molecules regulate immune responses and may be related to immune disorders. However, studying them is challenging due to RNA’s fragility. Therefore, a robust method for identifying glycosylated RNA is important. To address this, we optimized methods for enriching and identifying glycoRNAs, opening doors to explore their potential interactions with immune receptors and tumor suppression. Our approach involved investigating factors such as preservation solutions, enzyme buffers, digestion temperature, and incubation time. We successfully achieved efficient digestion of both N-linked and O-linked glycoRNAs at room temperature using 25 mM ammonium bicarbonate, demonstrating the effectiveness of this method. Additionally, RNA preservation in RNAlater at -80°C allows controlled release of glycoRNAs within hours. While sequential digestion of different glycoRNA types is possible, significant degradation occurs after the first enzyme step. Thus, we recommend separate harvesting for each type of glycoRNA. These optimized protocols, utilizing SPCgRNA and TnORNA methods, pave the way for further research on N- and O-glycoRNAs in health and disease.
Parental thermal conditions affect the brain activity response to alarm cue in larval zebrafish
Authors: Sourisse Jade M. , Semmelhack Julie L. , Schunter Celia
Published: June 2024

With temperature being a crucial factor affecting the physiology of ectothermic animals, global warming will likely impact neural mechanisms aquatic organisms use to perceive their environment over generations. However, exposure to elevated temperature during specific life stages and across generations may confer fish resilience through phenotypic plasticity. In this study, we investigate the effects of developmental and parental temperature on brain activity response to an olfactory cue in the larval zebrafish,Danio rerio. We exposed parents during reproduction and their offspring during development to control (28°C) or elevated temperature (30°C) and observed the response of the larval telencephalon to an alarm cue using live calcium imaging. Parental exposure to elevated temperature decreased the time till maximum brain activity response regardless of the offspring’s developmental temperature, revealing that parental thermal conditions can affect the excitability of the offspring’s neural circuitry. Furthermore, brain activity duration was affected by the interaction between parental and offspring thermal conditions, tending to last longer when either parents or offspring were exposed to elevated temperature, yet more similar to control when elevated temperature was experienced by both parents and offspring. This could represent an anticipatory parental effect influencing the offspring’s brain response to match the parental environment, or an early developmental effect occurring within a susceptible short time window post-fertilization. Overall, our results suggest that future predicted warming can alter processes involved in brain transmission and show that parental conditions could aid in the preparation of their offspring to respond to olfactory stimuli in a changing environment.
A novel hybrid high speed mass spectrometer allows rapid translation from biomarker candidates to targeted clinical tests using 15N labeled proteins
Authors: Wahle Maria , Remes Philip M. , Albrecht Vincent , Mueller-Reif Johannes , Steigerwald Sophia , Heymann Tim , Niu Lili , Lössl Philip , Horning Stevan , Jacob Cristina C. , Mann Matthias
Published: June 2024

Recent developments in affinity binder or mass spectrometry (MS)-based plasma proteomics are now producing panels of potential biomarker candidates for diagnosis or prognosis. However, clinical validation and implementation of these biomarkers remain limited by the reliance on dated triple quadrupole MS technology. Here, we evaluate a novel hybrid high-speed mass spectrometer, Stellar MS, which integrates the robustness of triple quadrupoles with the enhanced capabilities of an advanced linear ion trap analyzer. This instrument allows for extremely rapid and sensitive parallel reaction monitoring (PRM) and MS3 targeting. The Stellar MS allowed targeting thousands of peptides originally measured on Orbitrap Astral MS, achieving high reproducibility and low coefficients of variation (CV) as well as sensitivity and specificity sufficient for more than the top 1000 plasma proteins. Furthermore, we developed targeted assays for alcohol-related liver disease (ALD) biomarkers, showcasing the potential of Stellar MS in clinical applications. Absolute quantification is typically a requirement for clinical assays and we explore the use of15N labeled protein standards in a rapid, streamlined and generic manner. Our results indicate that Stellar MS can bridge the gap between proteomics discovery and routine clinical testing, enhancing the diagnostic and prognostic utility of protein biomarkers.
Automated classification of cellular expression in multiplexed imaging data with Nimbus
Authors: Rumberger J. Lorenz , Greenwald Noah F. , Ranek Jolene S. , Boonrat Potchara , Walker Cameron , Franzen Jannik , Varra Sricharan Reddy , Kong Alex , Sowers Cameron , Liu Candace C. , Averbukh Inna , Piyadasa Hadeesha , Vanguri Rami , Nederlof Iris , Wang Xuefei Julie , Van Valen David , Kok Marleen , Hollmann Travis J. , Kainmueller Dagmar , Angelo Michael
Published: June 2024

Multiplexed imaging offers a powerful approach to characterize the spatial topography of tissues in both health and disease. To analyze such data, the specific combination of markers that are present in each cell must be enumerated to enable accurate phenotyping, a process that often relies on unsupervised clustering. We constructed the Pan-Multiplex (Pan-M) dataset containing 197 million distinct annotations of marker expression across 15 different cell types. We used Pan-M to create Nimbus, a deep learning model to predict marker positivity from multiplexed image data. Nimbus is a pre-trained model that uses the underlying images to classify marker expression across distinct cell types, from different tissues, acquired using different microscope platforms, without requiring any retraining. We demonstrate that Nimbus predictions capture the underlying staining patterns of the full diversity of markers present in Pan-M. We then show how Nimbus predictions can be integrated with downstream clustering algorithms to robustly identify cell subtypes in image data. We have open-sourced Nimbus and Pan-M to enable community use athttps://github.com/angelolab/Nimbus-Inference.
Polygenic Resilience Scores are Associated with Lower Penetrance of Schizophrenia Risk Genes, Protection Against Psychiatric and Medical Disorders, and Enhanced Mental Well-Being and Cognition
Authors: Hess Jonathan L. , Barnett Eric J. , Hou Jiahui , Faraone Stephen V. , Glatt Stephen J.
Published: June 2024

In the past decade, significant advances have been made in finding genomic risk loci for schizophrenia (SCZ). This, in turn, has enabled the search for SCZ resilience loci that mitigate the impact of SCZ risk genes. Recently, we discovered the first genomic resilience profile for SCZ, completely independent from the established risk loci for SCZ. We posited that these resilience loci protect against SCZ for those having a heighted genomic risk for SCZ. Nevertheless, our understanding of genetic resilience remains limited. It remains unclear whether resilience loci foster protection against adverse states associated with SCZ risk related to clinical, cognitive, and brain-structural phenotypes. To address this knowledge gap, we analyzed data from 487,409 participants from the UK Biobank, and found that resilience loci for SCZ afforded protection against lifetime psychiatric (schizophrenia, bipolar disorder, anxiety, and depression) and non-psychiatric medical disorders (such as asthma, cardiovascular disease, digestive disorders, metabolic disorders, and external causes of morbidity and mortality). Resilience loci also protected against self-harm behaviors, improved fluid intelligence, and larger whole-brain and brain-regional sizes. Overall, this study sheds light on the range of phenotypes that are significantly associated with resilience loci within the general population, revealing distinct patterns separate from those associated with SCZ risk loci. Our findings indicate that resilience loci may offer protection against serious psychiatric and medical outcomes, co-morbidities, and cognitive impairment. Therefore, it is conceivable that resilience loci facilitate adaptive processes linked to improved health and life expectancy.
Young Women’s Preferences for a Self-Sampling Intervention to Diagnose Sexually Transmitted Infections: A Discrete Choice Experiment
Authors: Jaya Ziningi N. , Mapanga Witness , Ogunsakin Ropo , Mashamba-Thompson Tivani P
Published: June 2024

The high rates of sexually transmitted infections (STIs) in young women in South Africa warrant the use of innovative interventions like self-sampling to diagnose both symptomatic and asymptomatic infections. Although proven as an effective measure in the fight against STIs, there is limited evidence on the preferred attributes of this intervention. We conducted a discrete choice experiment (DCE) to understand young women’s preferred attributes for self-sampling which included accessibility and convenience of self-sampling kits, education and normalisation, confidentiality and communication of results, self-sampling collection method, cost, and youth-friendliness as developed using a nominal group technique. A total of 206 young women aged between 18 – 24 years residing in underserved communities in Ethekwini Metropolitan Municipality, in KwaZulu-Natal, participated in the study. Study findings highlighted young women’s preference for enhanced accessibility, comprehensive education on STIs and self-sampling, confidential result communication, autonomy in self-collection method selection, and youth-friendly healthcare environments. The design of effective self-sampling interventions that promote STI testing thereby reducing transmission of infection, should address these preferences. Policymakers and healthcare providers should engage youth in the design of such initiatives and promote patient-centred healthcare to meet their preferences and improve STI-related health outcomes in this population.
Endogenous Promotor-Driven Split Nanoluciferase Biosensor for Assessing G Protein Recruitment
Authors: Humphrys Laura J. , Höring Carina , Gattor Albert O.
Published: June 2024

HEK293 cells are a common immortal cell line used in biological research, and their popularity has led to different distinct lineages across the world. Commonly used for overexpression of proteins, HEK293 cells also natively express biological targets, such as G protein coupled receptors (GPCRs) and their downstream signalling partners, G proteins, although this often confounds rather than compliments research. CRISPR/Cas9 gene editing can be used to harness these native proteins and make use of their presence. Here, a cost- and time-effective, plasmid-based CRISPR/Cas9 approach is used to tag well-characterised GPCRS – the β-adrenoceptors 1 and 2 – with one part of a split Nanoluciferase and replace the Gαscoupling partner with the complimentarily tagged minimal Gsprotein in HEK293T cells. Compared to untagged proteins, the CRISPR/Cas9 cells allow for better selective-ligand characterisation at the native β-adrenoceptors. Overexpressed tagged systems produce similar results to the CRISPR/Cas9 cells, however subtle changes in the characterisation of partial agonists, such as salbutamol, demonstrate the potential for utilising tagged native receptors in analysing biological effectors.

Summary Statement

For the first time, a split-luciferase tagged minimal Gs protein and β1AR is inserted under endogenous promotors in HEK293T cells using CRISPR/Cas9 gene modification, avoiding protein overexpression in the assay.
Single-cell profiling of penta- and tetradactyl mouse limb buds identifies mesenchymal progenitors controlling digit numbers and identities
Authors: Palacio Victorio , Pancho Anna , Morabito Angela , Malkmus Jonas , He Zhisong , Soussi Geoffrey , Zeller Rolf , Treutlein Barbara , Zuniga Aimée
Published: June 2024

The cellular mechanisms controlling digit numbers and identities have remained elusive. Profiling of wild-type (pentadactyl) andGrem1tetradactyl mouse limb buds identifies cellular changes affecting two limb bud mesenchymal progenitor (LMP) populations. In mutant limb buds, the anteriorly biased distribution of peripheral LMPs (pLMPs) is lost and the population expanded, while the distal-posterior LMP (dLMP) population is reduced from early stages onward. Analysis of LMP signature genes in wildtype and mutant mouse limb buds with digit loss or gain establishes that pLMPs are positively regulated by BMP signaling, while dLMPs require GREM1-mediated BMP antagonism. dLMPs encompass digit progenitors and altering their population size prefigures changes in digit numbers. The anteriorly biased pLMP distribution is linked to digit asymmetry as loss of this bias in tetradactyl mouse and pig limb buds underlies middle digit symmetry and identity loss. This study indicates that variable spatialGrem1expression in mutant and evolutionary diversified limb buds tunes BMP activity, impacting both LMP populations in a complementary manner.
MONFIT: Multi-omics factorization-based integration of time-series data sheds light on Parkinson’s disease
Authors: Mihajlović Katarina , Malod-Dognin Noël , Ameli Corrado , Skupin Alexander , Pržulj Nataša
Published: June 2024

Parkinson’s disease (PD) is a severe and complex multifactorial neurodegenerative disease with still elusive pathophysiology preventing the development of curative treatments. Molecular deep phenotyping by longitudinal multi-omics is a promising approach to identify mechanisms of PD aetiology and its progression. However, the heterogeneous data require new analysis frameworks to understand disease progression across biological entities and processes. Here, we present MONFIT, a holistic analysis pipeline that integrates and mines time-series single-cell RNA-sequencing data with bulk proteomics and metabolomics data by non-negative matrix tri-factorization, enabling prior knowledge incorporation from molecular networks. First, MONIFT integrates time-point-specific data and then holistically mines the integrated data across time points. By applying MONFIT to longitudinal multi-omics data of differentiation of PD and control patient-derived induced pluripotent stem cells into dopaminergic neurons, we identify novel PD-associated genes, emphasize molecular pathways that play important roles in PD pathology, and suggest new intervention opportunities using drug-repurposing. MONFIT is fully adaptable to other multi-omics data sets.
Epithelial tubule interconnection driven by HGF-Met signaling in the kidney
Authors: López-García Isabel , Oh Sunhee , Chaney Chris , Tsunezumi Jun , Drummond Iain , Oxburgh Leif , Carroll Thomas , Marciano Denise K.
Published: June 2024

The formation of functional epithelial tubules is a central feature of many organ systems. Although the process of tubule formation by epithelial cells is well-studied, the way in which tubules connect with each other (i.e. anastomose) to form functional networks bothin vivoandin vitrois not well understood. A key, unanswered question in the kidney is how the renal vesicles of the embryonic kidney connect with the nascent collecting ducts to form a continuous urinary system. We performed a ligand-receptor pair analysis on single cell RNA-seq data from embryonic mouse kidney tubules undergoing anastomosis to select candidates that might mediate this processin vivo. This analysis identified hepatocyte growth factor (HGF), which has known roles in cell proliferation, migration, and tubulogenesis, as one of several possible candidates. To test this possibility, we designed a novel assay to quantitatively examine epithelial tubule anastomosisin vitrousing epithelial spheroids with fluorescently-tagged apical surfaces to enable direct visualization of anastomosis. This revealed that HGF is a potent inducer of tubule anastomosis. Tubule anastomosis occurs through a proliferation-independent mechanism that acts through the MAPK signaling cascade and matrix metalloproteinases (MMPs), the latter suggestive of a role in extracellular matrix turnover. Accordingly, treatment of explanted embryonic mouse kidneys with HGF and collagenase was sufficient to induce kidney tubule anastomosis. These results lay the groundwork for investigating how to promote functional interconnections between tubular epithelia, which have important clinical implications for utilizingin vitrogrown kidney tissue in transplant medicine.
Near-Field Spin Chern Number Quantized by Real-Space Topology of Optical Structures
Authors: Fu Tong , Zhang Ruo-Yang , Jia Shiqi , Chan C. T. , Wang Shubo
Published: June 2024

The Chern number has been widely used to describe the topological properties of periodic structures in momentum space. Here, we introduce a real-space spin Chern number for the optical near fields of finite-sized structures. This new spin Chern number is intrinsically quantized and equal to the structure’s Euler characteristic. The relationship is robust against continuous deformation of the structure’s geometry and is irrelevant to the specific material constituents or external excitation. Our Letter enriches topological physics by extending the Chern number to real space, opening exciting possibilities for exploring the real-space topological properties of light.

Published by the American Physical Society
2024
Kondo enabled transmutation between spinons and superconducting vortices: Origin of magnetic memory in
4Hb−TaS2
Authors: Lin Shi-Zeng
Published: June 2024

Recent experiments [Persky , ] demonstrate a magnetic memory effect in 4Hb−TaS2 above its superconducting transition temperature, where Abriokosov vortices are spontaneously generated by lowering the temperature at zero magnetic field after field training the normal state. Motivated by the experiment, we propose the chiral quantum spin liquid (QSL) stabilized in the constituent layers of 4Hb−TaS2 as a mechanism. We model 4Hb−TaS2 as coupled layers of the chiral QSL and the superconductor. Through the Kondo coupling between the localized moments and conduction electrons, there is mutual transmutation between spinons and vortices during the thermal-cycling process, which yields the magnetic memory effect observed in experiments. We also propose a mechanism to stabilize chiral and nematic superconductivity in 4Hb−TaS2 through the Kondo coupling of conduction electrons to the chiral QSL. Our picture suggests 4Hb−TaS2 as an exciting platform to explore the interplay between QSL and superconductivity through the Kondo effect.

Published by the American Physical Society
2024
Tailoring bistability in optical tweezers with vortex beams and spherical aberration
Authors: da Fonseca Arthur L. , Diniz Kainã , Monteiro Paula B. , Pires Luís B. , Moura Guilherme T. , Borges Mateus , Dutra Rafael S. , Ether Diney S. , Viana Nathan B. , Neto Paulo A. Maia
Published: June 2024

We demonstrate a bistable optical trap by tightly focusing a vortex laser beam. The optical potential has the form of a Mexican hat with an additional minimum at the center. The bistable trapping corresponds to a nonequilibrium steady state, where the microsphere continually hops, due to thermal activation, between an axial equilibrium state and an orbital state driven by the optical torque. We develop a theoretical model for the optical force field, based entirely on experimentally accessible parameters, combining a Debye-type nonparaxial description of the focused vortex beam with Mie scattering by the microsphere. The theoretical prediction that the microsphere and the annular laser focal spot should have comparable sizes is confirmed experimentally by taking different values for the topological charge of the vortex beam. Spherical aberration introduced by refraction at the interface between the glass slide and the sample is considered and allows us to finetune between axial, bistable, and orbital states as the sample is shifted with respect to the objective focal plane. We find overall agreement between theory and experiment for a rather broad range of topological charges. Our results open the way for applications in stochastic thermodynamics, as they establish a control parameter—the height of the objective focal plane with respect to the glass slide—that allows us to shape the optical force field in real time and in a controllable way.

Published by the American Physical Society
2024
Decoherence rate in random Lindblad dynamics
Authors: Yang Yifeng , Xu Zhenyu , del Campo Adolfo
Published: June 2024

Open quantum systems undergo decoherence, which is responsible for the transition from quantum to classical behavior. The time scale in which decoherence takes place can be analyzed using upper limits to its rate. We examine the dynamics of open chaotic quantum systems governed by random Lindblad operators sourced from Gaussian and Ginibre ensembles with Wigner-Dyson symmetry classes. In these systems, the ensemble-averaged purity decays monotonically as a function of time. This decay is governed by the decoherence rate, which is upper-bounded by the dimension of their Hilbert space and is independent of the ensemble symmetry. These findings hold upon mixing different ensembles, indicating the universal character of the decoherence rate limit. Moreover, our findings reveal that open chaotic quantum systems governed by random Lindbladians tend to exhibit the most rapid decoherence, regardless of the initial state. This phenomenon is associated with the concentration of the decoherence rate near its upper bound. Our work identifies primary features of decoherence in dissipative quantum chaos, with applications ranging from quantum foundations to high-energy physics and quantum technologies.

Published by the American Physical Society
2024
High-efficiency realization of the super-robust Rydberg Deutsch gate
Authors: Li A. , Liu B.-B. , Yan L.-L. , Su S.-L. , Chen Gang , Feng M.
Published: June 2024

Quantum logic gates are the essential components of quantum computation and have broad practical applications, especially for the multiple-qubit logic gates. Compared with appliying a series of single- and two-qubit gates, constrcuting quantum computation with multiple-qubit logic gates can be more efficient and high-fidelity. As a three-qubit logic gate, Deutsch gate enables the realization of any feasible quantum computations. Based on neutral atoms, we present a scheme of super-robust Deutsch gate via optimal control technique. Utilizing the Rydberg blockade effect of neutral atoms, we design an implementable D(β) based on the three-step program. One of the notable advantages of this function is that β can be achieved arbitrarily between 0 and π with the operation of target atom. In addition, we give an analytical solution agreed very well with numerical simulations for the residual blocking effect between next-neighbor atoms that affects the performance quality of Deutsch gate. The fidelity of our proposed scheme is demonstrated by numerical simulation of the master equation based on the full Hamiltonian, and the robustness of our scheme with control errors is also illustrated. Our proposal offers an alternative promising scheme for fault-tolerant quantum computation.

Published by the American Physical Society
2024
Probing the Mott insulating behavior of
Ba2MgReO6
with
DFT+DMFT
Authors: Merkel Maximilian E. , Tehrani Aria Mansouri , Ederer Claude
Published: June 2024

We investigate the interplay of spin-orbit coupling, electronic correlations, and lattice distortions in the 5d1 double perovskite Ba2MgReO6. Combining density-functional theory (DFT) and dynamical mean-field theory (DMFT), we establish the Mott insulating character of Ba2MgReO6 in both its cubic and tetragonal paramagnetic phases. Despite substantial spin-orbit coupling, its impact on the formation of the insulating state is minimal, consistent with theoretical expectations for d1 systems. We further characterize the electronic properties of the cubic and tetragonal phases by analyzing spectral functions and local occupations in terms of multipole moments centered on the Re sites. Our results confirm the presence of ferroically ordered z2 quadrupoles in addition to the antiferroic x2−y2-type order. We compare two equivalent but complementary descriptions in terms of either effective Re-t2g frontier orbitals or more localized atomiclike Re-d and O-p orbitals. The former maps directly on a physically intuitive picture in terms of nominal d1 Re cations, while the latter explicitly demonstrates the role of hybridization with the ligands in the spin-orbit splitting and the formation of the charge quadrupoles around the Re sites. Finally, we compare our DFT+DMFT results with a previous DFT+U study of the tetragonal paramagnetic state. We find good qualitative agreement for the dominant charge quadrupoles, but also notable differences in the corresponding spectral functions, underscoring the need for more comparative studies between these two methods.

Published by the American Physical Society
2024
Origin of symmetry breaking in the grasshopper model
Authors: Llamas David , Kent-Dobias Jaron , Chen Kun , Kent Adrian , Goulko Olga
Published: June 2024

The planar grasshopper problem, originally introduced by Goulko and Kent [], is a striking example of a model with long-range isotropic interactions whose ground states break rotational symmetry. In this paper we analyze and explain the nature of this symmetry breaking with emphasis on the importance of dimensionality. Interestingly, rotational symmetry is recovered in three dimensions for small jumps, which correspond to the nonisotropic cogwheel regime of the two-dimensional problem. We discuss simplified models that reproduce the symmetry properties of the original system in N dimensions. For the full grasshopper model in two dimensions we obtain quantitative predictions for optimal perturbations of the disk. Our analytical results are confirmed by numerical simulations.

Published by the American Physical Society
2024
Entangled two-photon quantum heat engine: Dissipative nonequilibrium dynamics and correlated statistics
Authors: Chen JunJie , Dorfman Konstantin
Published: June 2024

Recently, the thermodynamics of open quantum systems driven by light fields has been investigated in the framework of quantum heat engines, whose output work can be measured as a spectroscopic signal. In this work, we investigate a four-level quantum heat engine that generates cascaded entangled photon pairs, treating the hot bath as an incoherent thermal pump and focusing on the correlation statistics of the output work and photon indistinguishability. We show that the dissipative nonequilibrium dynamics of this thermodynamic open quantum system can be reconstructed by correlation measurements under carefully mediated optical control. Comparing our findings with the traditional coherently pumped model, we find that the thermal pumping has the potential to generate nonclassical correlations resulting in photon indistinguishability, displaying an advantage in probing the nonequilibrium effects induced by the baths at different temperatures. Our work also demonstrates that incoherent pumping can optimize such correlations in output work beyond the classical limit. Lastly, we show that nonclassical correlations and resonant power at steady state cannot be simultaneously maximized in the weak coupling regime.

Published by the American Physical Society
2024
Mutual information as a measure of mixing efficiency in viscous fluids
Authors: Shi Yihong , Golestanian Ramin , Vilfan Andrej
Published: June 2024

Because of the kinematic reversibility of the Stokes equation, fluid mixing at the microscale requires an interplay between advection and diffusion. Here, we introduce mutual information between particle positions before and after mixing as a measure of mixing efficiency. We demonstrate its application in a Couette flow in an annulus and show that nonuniform rotation sequences can lead to more efficient mixing. We also determine mutual information from Brownian dynamics simulations using data compression algorithms. Our results show that mutual information provides a universal and assumption-free measure of mixing efficiency in microscale flows.

Published by the American Physical Society
2024
Frequency-Dependent Ecological Interactions Increase the Prevalence, and Shape the Distribution, of Preexisting Drug Resistance
Authors: Maltas Jeff , Tadele Dagim Shiferaw , Durmaz Arda , McFarland Christopher D. , Hinczewski Michael , Scott Jacob G.
Published: June 2024

The evolution of resistance remains one of the primary challenges for modern medicine, from infectious diseases to cancers. Many of these resistance-conferring mutations often carry a substantial fitness cost in the absence of treatment. As a result, we would expect these mutants to undergo purifying selection and be rapidly driven to extinction. Nevertheless, preexisting resistance is frequently observed from drug-resistant malaria to targeted cancer therapies in non-small-cell lung cancer (NSCLC) and melanoma. Solutions to this apparent paradox have taken several forms, from spatial rescue to simple mutation supply arguments. Recently, in an evolved resistant NSCLC cell line, we found that frequency-dependent ecological interactions between ancestor and resistant mutant ameliorate the cost of resistance in the absence of treatment. Here, we hypothesize that frequency-dependent ecological interactions in general play a major role in the prevalence of preexisting resistance. We combine numerical simulations with robust analytical approximations to provide a rigorous mathematical framework for studying the effects of frequency-dependent ecological interactions on the evolutionary dynamics of preexisting resistance. First, we find that ecological interactions significantly expand the parameter regime under which we expect to observe preexisting resistance. Next, even when positive ecological interactions between mutants and ancestors are rare, these resistant clones provide the primary mode of evolved resistance because even weak positive interaction leads to significantly longer extinction times. We then find that even in the case where mutation supply alone is sufficient to predict preexisting resistance, frequency-dependent ecological forces still contribute a strong evolutionary pressure that selects for increasingly positive ecological effects (negative frequency-dependent selection). Finally, we genetically engineer several of the most common clinically observed resistance mechanisms to targeted therapies in NSCLC, a treatment notorious for preexisting resistance. We find that each engineered mutant displays a positive ecological interaction with their ancestor. As a whole, these results suggest that frequency-dependent ecological effects can play a crucial role in shaping the evolutionary dynamics of preexisting resistance.

Published by the American Physical Society
2024
The drivers of sharing willingness regarding sustainable fashion brand image based on commitment theory
Authors: Yang Yingjie , Chen Meihua , Meng Hu
Published: June 2024

Purpose

Sustainability is considered a core trend in the development of the fashion industry. Clarifying the driving factors of consumers’ sharing willingness regarding sustainable image from the perspective of psychology can help fashion brands implement sustainable management and deepen industrial sustainable development.

Design/methodology/approach

Based on commitment theory, this paper proposes a conceptual model that includes three antecedents: perception of greenwashing, environmental, social and governance (ESG) and social media content quality. These affect consumers’ sharing willingness regarding sustainable image through affective commitment, continuance commitment and normative commitment. Furthermore, 310 participants reported their tendencies in a formal empirical study.

Findings

The results show that unlike green perception, which has a significant negative effect, consumers have a significant positive commitment to high perceived levels of ESG and social media content quality. Besides, all three dimensions under the commitment theory play a partial mediating role between consumer perception and sharing willingness.

Originality/value

This study not only extends the research on the commitment theory to the field of fashion marketing and management but also enriches the research context of brand image sharing willingness, which explains the differential effects of different consumer commitments on their information sharing willingness. Moreover, several management implications applicable to the fashion industry have also been proposed based on the conclusion.
To stay or to switch: the mediation effect of scepticism on switching intention to halal cosmetics from the perspective of the pull-push-mooring theory
Authors: Mohd Shelahudin Nur Raudhatul Jannah , Ngah Abdul Hafaz , Rahi Samar , Gabarre Serge , Mokhlis Safiek , Al-Gasawneh Jassim Ahmad
Published: June 2024

Purpose

The purpose of this paper is to extend the Push-Pull-Mooring (PPM) theory to identify the factors influencing Muslim customers’ switching intention to halal-certified cosmetics.

Design/methodology/approach

A snowballing sampling method was used to distribute an online questionnaire via social media platforms. Of 403 questionnaires, only 363 were usable. SmartPLS 4 was used to analyse the data using a structural equation modelling approach.

Findings

The findings of this paper confirmed that social influence and scepticism have a positive effect on the switching intention to halal cosmetics. However, compatibility with current cosmetic products has a negative effect on the switching intention to halal cosmetics. On the other hand, negative side effects and negative past experiences have a positive effect on scepticism. Scepticism was also found to mediate the relationship between negative side effects and negative past experiences toward the switching intention to halal cosmetics.

Practical implications

The findings of this study primarily benefit cosmetics manufacturers, whether halal-certified or otherwise.

Originality/value

This study extends the PPM theory with negative side effects and negative past experiences. Moreover, this study also introduces new relationships and untested relationships between scepticism and switching intention. This study shows the mediating effects of scepticism on the relationship between negative side effects and negative past experiences toward switching intention.
Anthropology in times of escalating conflicts
Authors: Schaeublin Emanuel
Published: June 2024

Escalating conflicts often lead to the proliferation of oversimplified narratives and intense pressure to conform to them. Anthropology can play a crucial role in such situations by (1) analysing the origins and mechanisms of enforcement of these narratives across various contexts, providing a more nuanced understanding of the conflict's dynamics; (2) challenging dominant framings of specific aspects of the conflict by producing contextualized knowledge, thereby offering alternative perspectives and insights; and (3) highlighting narratives that acknowledge the responsibility of the involved actors and explore new possibilities for political co‐existence. To illustrate these points, this guest editorial applies narrative conflict theory to the violence between Israelis and Palestinians since 7 October 2023 and invites readers to reflect on the discipline's responsibilities and methods in the face of the normalization of war and annihilation.
Compensation for cultural loss in Indigenous Australia
Authors: Martin Richard J.
Published: June 2024

The issue of compensation for harm to Indigenous culture is increasingly prominent in Australian society, given the High Court's landmark decision in Northern Territory v Griffiths (2019). The High Court sought to assess the meaning of cultural loss from Indigenous testimony and ‘translate the spiritual hurt from the compensable acts into compensation’. The destruction of Juukan Gorge in Western Australia's Pilbara region in 2020 also prompted efforts to assess, evaluate and remedy the harm Puutu Kunti Kurrama and Pinikura peoples suffered. Parallel debates about treaties have also raised the possibility of reparations for colonization. This article considers the challenges these legal and political developments pose for anthropology in Australia, where scholars have avoided discussing the concept of cultural loss for a generation.