bluuebunny/crossref_metadata_2025 huggingface dataset:
Epigenetic targeting of PGBD5-dependent DNA damage in SMARCB1-deficient sarcomas
Authors: Kazansky Yaniv , Mueller Helen S. , Cameron Daniel , Demarest Phillip , Zaffaroni Nadia , Arrighetti Noemi , Zuco Valentina , Mundi Prabhjot S. , Kuwahara Yasumichi , Somwar Romel , Qu Rui , Califano Andrea , de Stanchina Elisa , Dela Cruz Filemon S. , Kung Andrew L. , Gounder Mrinal M. , Kentsis Alex
Published: May 2024

Despite the potential of targeted epigenetic therapies, most cancers do not respond to current epigenetic drugs. The Polycomb repressive complex EZH2 inhibitor tazemetostat was recently approved for the treatment ofSMARCB1-deficient epithelioid sarcomas, based on the functional antagonism between PRC2 and loss of SMARCB1. Through the analysis of tazemetostat-treated patient tumors, we recently defined key principles of their response and resistance to EZH2 epigenetic therapy. Here, using transcriptomic inference fromSMARCB1-deficient tumor cells, we nominate the DNA damage repair kinase ATR as a target for rational combination EZH2 epigenetic therapy. We show that EZH2 inhibition promotes DNA damage in epithelioid and rhabdoid tumor cells, at least in part via its induction of the transposase-derived PGBD5. We leverage this collateral synthetic lethal dependency to target PGBD5-dependent DNA damage by inhibition of ATR but not CHK1 using elimusertib. Consequently, combined EZH2 and ATR inhibition improves therapeutic responses in diverse patient-derived epithelioid and rhabdoid tumorsin vivo. This advances a combination epigenetic therapy based on EZH2-PGBD5 synthetic lethal dependency suitable for immediate translation to clinical trials for patients.
Does standard adjustment for genomic population structure capture direct genetic effects?
Authors: Sotoudeh Ramina , Trejo Sam , Harpak Arbel , Conley Dalton
Published: May 2024

Contemporary genomic studies of complex traits, such as genome-wide association studies (GWASs) and polygenic index (PGI) analyses, often use the principal components of the genotype matrix (PCs) to adjust for population stratification. In this paper, we explore the extent to which we may be discounting direct genetic effects by adjusting for PCs. Using family-based models that control for parental genotype (obtained via Mendelian imputation), we test whether PCs have a direct genetic effect on nine complex phenotypes in the White British subsample of the UK Biobank. Further, we assess the extent to which estimates of polygenic effects meaningfully change when adjusting for PCs in within-family models. Across the nine traits, within-family effects of the top 40 PCs are highly similar to their population effects, suggesting that standard PC adjustments diminish, albeit to a small degree, detectable signals of direct genetic effects. Within family models also confirm that PCs have significant marginal effects on a few traits, most consistently, height and educational attainment. Nonetheless, the variance explained by the effects of PCs is modest, and adjusting for PCs does not appear to affect the magnitude and significance of PGI effects in within-family models.
Efficient and durable gene activation by Cas9-mediated epigenome editing in vivo
Authors: Qin Yuanbo , Akbulut Talha , Mandraju Rajakumar , Connolly Keith , Bechill John , Assadian Farzaneh , Shottek Alison , Levy Seth , Benoit Jamie , Yamagata Tetsuya
Published: May 2024

Epigenome editing technology holds great promise for treating diverse genetic disorders. While a series of advances has been made on epigenetic silencing using programmable editors, little progress has been made in leveraging epigenetic activation for therapeutic application. Here we demonstrate epigenetic activation of the LAMA1 gene for the treatment of LAMA2-CMD, a severe congenital muscle dystrophy (CMD) caused by biallelic mutations in the LAMA2 gene. LAMA1 is a sister homologue that is known to compensate for the function of LAMA2. However, supplementing LAMA1 or LAMA2 gene via viral platform is not feasible due to the large size of their coding sequences. Through a single administration of our (Adeno-associated virus) AAV vector encoding all the necessary elements for epigenetic activation, a platform termed CRISPR guide-nucleotide directed modulation (GNDM), we observed significant LAMA1 gene upregulation and phenotype improvements in DyW mice, a severe disease model of LAMA2-CMD. Notably, sustained expression of the GNDM gene and subsequent activation of the LAMA1 gene persisted beyond analyzed period of one year despite immune recognition of the GNDM protein by the host immune system. Regulatory T (Treg) cells appeared to facilitate tolerance to GNDM in the transduced muscle tissue. The muscle-tropic AAV capsid exhibited desired vector biodistribution and promising pharmacodynamics with good safety profiles in adult non-human primates (NHPs). Moreover, administration to juvenile NHPs demonstrated superior pharmacodynamics compared to adults, even at half the adult dose, suggesting safer and more effective therapeutic outcomes in mostly pediatric LAMA2-CMD patients. Our approach holds broad applicability for a range of loss-of-function genetic disorders and could offer a therapeutic breakthrough where active epigenome brings clinical benefit.
Postnatal hearing development limits early parent-to-offspring vocal communication and gates sensorimotor learning in the zebra finch
Authors: Anttonen Tommi , Christensen-Dalsgaard Jakob , Elemans Coen P. H.
Published: May 2024

Hearing is critical for vocal communication, and in birds its onset is linked to egg hatching. Hearing develops after hatching in early hatching (altricial) species, while already functional in the egg in later hatching (precocial) species. Recent work suggests that altricial zebra finches exhibit parent-to-embryo acoustic communication, requiring functional, high-frequency hearing already in the egg. Yet, the early postnatal development of their auditory sensitivity remains unknown. By measuring hearing and vibration-detection capacity during postnatal development in zebra finches, we show that zebra finch hatchlings are deaf even to loud, broadband sounds. Auditory nerve sensitivity develops gradually in a low-to-high frequency manner. Auditory nerve responses show adult-like properties only after 20 days from hatching. Our data provide evidence against the plausibility of early parent-to-offspring acoustic communication in zebra finches and suggest that hearing functionality may set the onset of vocal learning in zebra finches.
Estropausal gut microbiota transplant improves measures of ovarian function in adult mice
Authors: Kim Minhoo , Wang Justin , Pilley Steven E. , Lu Ryan J. , Xu Alan , Kim Younggyun , Liu Minying , Fu Xueyan , Booth Sarah L. , Mullen Peter J. , Benayoun Bérénice A.
Published: May 2024

Decline in ovarian function with age not only affects fertility but is also linked to a higher risk of age-related diseases in women (e.g. osteoporosis, dementia). Intriguingly, earlier menopause is linked to shorter lifespan; however, the underlying molecular mechanisms of ovarian aging are not well understood. Recent evidence suggests the gut microbiota may influence ovarian health. In this study, we characterized ovarian aging associated microbial profiles in mice and investigated the effect of the gut microbiome from young and estropausal female mice on ovarian health through fecal microbiota transplantation. We demonstrate that the ovarian transcriptome can be broadly remodeled after heterochronic microbiota transplantation, with a reduction in inflammation-related gene expression and trends consistent with transcriptional rejuvenation. Consistently, these mice exhibited enhanced ovarian health and increased fertility. Using metagenomics-based causal mediation analyses and serum untargeted metabolomics, we identified candidate microbial species and metabolites that may contribute to the observed effects of fecal microbiota transplantation. Our findings reveal a direct link between the gut microbiota and ovarian health.
Pred-AHCP: Robust feature selection enabled Sequence-Specific Prediction of Anti-Hepatitis C Peptides via Machine Learning
Authors: Saraswat Akash , Sharma Utsav , Gandotra Aryan , Wasan Lakshit , Artham Sainithin , Maitra Arijit , Singh Bipin
Published: May 2024

Every year, an estimated 1.5 million people worldwide contract Hepatitis C (HepC), a significant contributor to liver disease. Although many studies have explored machine learning’s potential to predict antiviral peptides, very few have addressed predicting peptides against specific viruses such as Hepatitis C. In this study, we demonstrate the use of machine learning (ML) algorithms to predict peptides that are effective against HepC. We developed an explainable ML model that harnesses the amino acid sequence of a peptide to predict its potential as an anti-HepC (AHC) agent. Specifically, features were computed based on sequence and physicochemical properties, with feature selection performed utilizing a combined scheme of mutual information and variance inflation factor. This facilitated the removal of redundant and multicollinear features from the sequence data, enhancing the model’s generalizability in predicting AHCPs. The model using therandom forestalgorithm produced the best performance with an accuracy of about 90%. The feature selection analysis highlights that the distribution of hydrophobicity and polarizability, as well as the frequencies of glycine residues and di-peptide motifs—YXL, LXK, VXXXF, VL, LV, CC, RR, TXXXV, VXXA, CXXXC—emerged as the key predictors for identifying AHCPs targeting different components of the HepC virus. The model developed can be accessed through the Pred-AHCP web server, provided athttp://tinyurl.com/web-Pred-AHCP. This resource facilitates the prediction and re-engineering of AHCPs for designing peptide-based therapeutics while also proposing an exploration of similar strategies for designing peptide inhibitors effective against other viruses.
Theoretical analyses for the evolution of biogenic volatile organic compounds (BVOCs) emission strategy
Authors: Hirose Sotaro , Satake Akiko
Published: May 2024

Plants emit biogenic volatile organic compounds (BVOCs) as signaling molecules, playing a crucial role in inducing resistance against herbivores. Neighboring plants that eavesdrop on BVOC signals can also increase defenses against herbivores or alter growth patterns to respond to potential risks of herbivore damage. Despite the significance of BVOC emissions, the evolutionary rationales behind their release and the factors contributing to the diversity in such emissions remain poorly understood. To unravel the conditions for the evolution of BVOC emission, we developed a spatially-explicit model that formalizes the evolutionary dynamics of BVOC emission and non-emission strategies. Our model considered two effects of BVOC signaling that impact the fitness of plants: intra-individual communication, which mitigates herbivore damage through the plant’s own BVOC signaling incurring emission costs, and inter-individual communication, which alters the influence of herbivory based on BVOC signals from other individuals without incurring emission costs. Employing two mathematical models—the lattice model and the random distribution model—we investigated how intra-individual communication, inter-individual communication, and spatial structure influenced the evolution of BVOC emission strategies. Our analysis revealed that the increase in intra-individual communication promotes the evolution of the BVOC emission strategy. In contrast, the increase in inter-individual communication effect favors cheaters who benefit from the BVOCs released from neighboring plants without bearing the costs associated with BVOC emission. Our analysis also demonstrated that the narrower the spatial scale of BVOC signaling, the higher the likelihood of BVOC evolution. This research sheds light on the intricate dynamics governing the evolution of BVOC emissions and their implications for plant-plant communication.
Genetic Inactivation of the β1 adrenergic receptor prevents Cerebral Cavernous Malformations in zebrafish
Authors: Li Wenqing , McCurdy Sara , Lopez-Ramirez Miguel A. , Lee Ho-sup , Ginsberg Mark H.
Published: May 2024

Propranolol reduces experimental murine cerebral cavernous malformations (CCMs) and prevents embryonic caudal venous plexus (CVP) lesions in zebrafish that follow mosaic inactivation ofccm2. Because morpholino silencing of the β1 adrenergic receptor (adrb1) prevents the embryonic CVP lesion, we proposed thatadrb1plays a role in CCM pathogenesis. Here we report thatadrb1−/-zebrafish exhibited 86% fewer CVP lesions and 87% reduction of CCM lesion volume relative to wild type brood mates at 2dpf and 8-10 weeks stage, respectively. Treatment with metoprolol, a β1 selective antagonist, yielded a similar reduction in CCM lesion volume.Adrb1−/-zebrafish embryos exhibited reduced heart rate and contractility and reduced CVP blood flow. Similarly, slowing the heart and eliminating the blood flow in CVP by administration of 2,3-BDM suppressed the CVP lesion. In sum, our findings provide genetic and pharmacological evidence that the therapeutic effect of propranolol on CCM is achieved through β1 receptor antagonism.
Host-encoded DNA methyltransferases modify the epigenome and host tropism of invading phages
Authors: Takahashi Michiko , Hiraoka Satoshi , Matsumoto Yuki , Shibagaki Rikako , Ujihara Takako , Maeda Hiromichi , Seo Satoru , Nagasaki Keizo , Takeuchi Hiroaki , Matsuzaki Shigenobu
Published: May 2024

A part of prokaryotic DNA methyltransferases (MTases) is associated with phage-defense systems (e.g., restriction-modification [RM] system) to combat the invasion of foreign DNA (e.g., phages). To date, the epigenomes of host and phage during the infection cycle have not been directly observed, and their association with phage infection efficiency remains unclear. Here, using the wide-host-range phage KHP30T and three Helicobacter pylori strains (26695, 3401T, and HPK5) that possess different sets of MTases, we investigated changes in infection efficiency and epigenomes of the phage via adaptation to each host strain. Based on the designed multi-stage infection flow, adapted phages showed higher titers only against the last infected H. pylori strain, suggesting an attendant change in host tropism. Using single-molecule real-time sequencing, we retrieved each complete genome and 15 and 20 methylated motifs from H. pylori 3401T and HPK5, respectively. In general, the methylated motifs were common between pairs of adapted phages and the last infected host strain. Some exceptions were identified that may arise from phase variation. Our results demonstrate phage genomes are methylated by host-encoded MTases during the infection cycle as they pass through the host RM system, resulting in increased infection efficiency of phages against the same host strain.
Daily light-induced transcription in visual cortex neurons drives downward Firing Rate Homeostasis and stabilizes sensory processing
Authors: Kushinsky Dahlia , Tsivourakis Emmanouil , Apelblat Daniella , Roethler Ori , Breger-Mikulincer Mor , Malina Katayun Cohen-Kashi , Spiegel Ivo
Published: May 2024

Balancing plasticity and stability in neural circuits is essential for an animal’s ability to learn from its environment while preserving the proper processing and perception of sensory information. However, unlike the mechanisms that drive plasticity in neural circuits, the activity-induced molecular mechanisms that convey functional stability remain poorly understood. Focusing on the visual cortex of adult mice and combining transcriptomics, electrophysiology and 2-photon imaging, we find that the daily appearance of light induces in excitatory neurons a large gene program along with rapid and transient shifts in the ratio of excitation and inhibition (E/I-ratio) and ongoing neural activity. Furthermore, we find that the light-induced transcription factor NPAS4 drives these daily normalizations of E/I-ratio and neural activity rates and that it stabilizes the neurons’ response properties. These findings indicate that daily sensory-induced transcription normalizes E/I-ratio and drives downward Firing Rate Homeostasis to maintain proper sensory processing and perception.
Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk
Authors: Kramer Nicole E , Byun Seyoun , Coryell Philip , D’Costa Susan , Thulson Eliza , Kim HyunAh , Parkus Sylvie M , Bond Marielle L , Klein Emma R , Shine Jacqueline , Chubinskaya Susanna , Love Michael I , Mohlke Karen L , Diekman Brian O , Loeser Richard F , Phanstiel Douglas H
Published: May 2024

Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce. We mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA-seq in chondrocytes from 101 donors across two conditions uncovered 3782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 10 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development.

Highlights

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Comprehensive analysis of sex- and age-related global gene expression in human chondrocytes revealed differences that correlate with osteoarthritis

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First response eQTLs in chondrocytes treated with an OA-related stimulus

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Deeply sequenced Hi-C in resting and activated chondrocytes helps connect OA risk variants to their putative causal genes

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Colocalization analysis reveals 13 (including 10 novel) putative OA risk genes
Verbal working memory and syntactic comprehension segregate into the dorsal and ventral streams
Authors: Matchin William , Mollasaraei Zeinab K. , Bonilha Leonardo , Rorden Chris , Hickok Gregory , den Ouden Dirk , Fridriksson Julius
Published: May 2024

Syntactic processing and verbal working memory are both essential components to sentence comprehension. Nonetheless, the separability of these systems in the brain remains unclear. To address this issue, we performed causal-inference analyses based on lesion and connectome network mapping using MRI and behavioral testing in 103 individuals with chronic post-stroke aphasia. We employed a rhyme judgment task with heavy working memory load without articulatory confounds, controlling for the overall ability to match auditory words to pictures and to perform a metalinguistic rhyme judgment, isolating the effect of working memory load. We assessed noncanonical sentence comprehension, isolating syntactic processing by incorporating residual rhyme judgment performance as a covariate for working memory load. Voxel-based lesion analyses and structural connectome-based lesion symptom mapping controlling for total lesion volume were performed, with permutation testing to correct for multiple comparisons (4,000 permutations). We observed that effects of working memory load localized to dorsal stream damage: posterior temporal-parietal lesions and frontal-parietal white matter disconnections. These effects were differentiated from syntactic comprehension deficits, which were primarily associated with ventral stream damage: lesions to temporal lobe and temporal-parietal white matter disconnections, particularly when incorporating the residual measure of working memory load as a covariate. Our results support the conclusion that working memory and syntactic processing are associated with distinct brain networks, largely loading onto dorsal and ventral streams, respectively.
Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning
Authors: Ruzmetov Talant , Hung Ta I , Jonnalagedda Saisri Padmaja , Chen Si-han , Fasihianifard Parisa , Guo Zhefeng , Bhanu Bir , Chang Chia-en A.
Published: May 2024

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure–function relationship, and numerous transient but stable conformations of Intrinsically Disordered Proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduce a deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from Molecular Dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β1-42(Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42’s conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability of deep learning to utilize learned natural atomistic motions in protein conformation sampling.
FKBP11 targeted plasma cells promotes abdominal aortic aneurysm progression through an m6A-dependent mechanism
Authors: He Yuchen , Xing Jia , Wang Shiyue , Jiang Han , Lun Yu , Han Yanshuo , Erhart Philipp , Dittmar Böckler , Zhang Jian
Published: May 2024

Objective

Despite surgical advance, effective targeted drugs for non-surgical treatment of abdominal aortic aneurysm (AAA) are lacking because of the unclear pathogenesis of AAA. N6-methyladenosine (m6A) methylation, acknowledged for its pivotal influence on RNA metabolism, including aspects such as stability, transport, translation, and splicing, is largely implied for its role in AAA mechanism. This study aims to elucidate the involvement of m6A methylation in the progression of AAA through an integrative multi-omics and machine learning approach.

Methods and Results

We utilized methylated RNA immunoprecipitation sequencing (MeRIP-seq) to map the m6A methylation landscape in AAA tissues and combined this with RNA sequencing (RNA-seq) from the GEO database, to explore the interplay between m6A methylation and gene expression. A machine learning-based AAA m6A-related mRNA signature (AMRMS) was developed to predict the risk of AAA dilation. The AMRMS showed robust predictive power in distinguishing between patients with large and small AAAs. Notably, FKBP11 was identified as a key gene significantly influencing the predictive model, and up-regulated in large AAAs compared to its in small AAAs. Further single-cell RNA sequencing (scRNA-seq) and histological analysis highlighted the critical role of FKBP11 in mediating the endoplasmic reticulum stress of plasma cells within the AAA walls and its correlation with m6A methylation.

Conclusions

The m6A modification regulatory network plays a vital role in the progression of AAA, and the AMRMS offers promising potential in assessing the risk of AAA dilation. Our findings suggest that elevated FKBP11, by activating endoplasmic reticulum stress in plasma cells, may significantly contribute to AAA expansion.
Measuring source properties and quasinormal mode frequencies of heavy massive black-hole binaries with LISA
Authors: Toubiana Alexandre , Pompili Lorenzo , Buonanno Alessandra , Gair Jonathan R. , Katz Michael L.
Published: May 2024

The Laser Interferometer Space Antenna (LISA) will be launched in the mid-2030s. It promises to observe the coalescence of massive black-hole (BH) binaries with signal-to-noise ratios (SNRs) reaching thousands. Crucially, it will detect some of these binaries with high SNR in both the inspiral and the merger-ringdown stages. Such signals are ideal for tests of general relativity (GR) using information from the whole waveform. Here, we consider astrophysically motivated binary systems at the high-mass end of the population observable by LISA and simulate their signals using the newly developed multipolar effective-one-body model: pSEOBNRv5HM. The merger-ringdown signal in this model depends on the binary properties (masses and spins) and also on parameters that describe fractional deviations from the GR quasinormal mode (complex) frequencies of the remnant BH. Performing full Bayesian analyses, we assess to which accuracy LISA will be able to constrain deviations from GR in the ringdown signal when using information from the whole signal. We find that these deviations can typically be constrained to within 10% and in the best cases to within 1%. We also show that with this model we can measure the binary masses and spins with great accuracy even for very massive BH systems with low SNR in the inspiral. In particular, individual source-frame masses can typically be constrained to within 10% and as precisely as 1%, and individual spins can typically be constrained to within 0.1 and, in the best cases, to within 0.001. We also probe the accuracy of the SEOBNRv5HM waveform family by performing synthetic injections of GR numerical-relativity waveforms. Using a novel method that we develop here to quantify the impact of systematic errors, we show that, already for sources with SNR O(100), we would measure erroneous deviations from GR due to waveform model inaccuracies. One of the main sources of error is the mismodeling of the relative alignment between harmonics. These results confirm the need for improving waveform models to perform tests of GR with binary BHs observed at high SNR by LISA.

Published by the American Physical Society
2024
Minimizing readout-induced noise for early fault-tolerant quantum computers
Authors: Zheng Yunzhe , Kanno Keita
Published: May 2024

Quantum error correcting code can diagnose potential errors and correct them based on measured outcomes by leveraging syndrome measurement. However, mid-circuit measurement has been technically challenging for early fault-tolerant quantum computers and the readout-induced noise acts as a main contributor to the logical infidelity. We present a different method for syndrome extraction, namely , that requires only a single-shot measurement on a single ancilla, while the canonical syndrome measurement requires multiple measurements to extract the eigenvalue for each stabilizer generator. As such, we can detect the error in the logical state with minimized readout-induced noise. By adopting our method as a precheck routine for quantum error correcting cycles, we can significantly reduce the readout overhead, the idling time, and the logical error rate during syndrome measurement. We numerically analyze the performance of our protocol using Iceberg code and Steane code under realistic noise parameters based on superconducting hardware and demonstrate the advantage of our protocol in the near-term scenario. As mid-circuit measurements are still error-prone for near-term quantum hardware, our method could boost the applications of early fault-tolerant quantum computing.

Published by the American Physical Society
2024
Separability criterion using one observable for special states: Entanglement detection via quantum quench
Authors: Ghosh Roopayan , Bose Sougato
Published: May 2024

Detecting entanglement in many-body quantum systems is crucial but challenging, typically requiring multiple measurements. Here, we establish a class of states where measuring connected correlations in just basis gives a necessary condition to detect bipartite separability, thus offering a sufficient condition to detect entanglement, provided the appropriate basis and observables are chosen. This methodology leverages prior information about the state, which, although insufficient to reveal the complete state or its entanglement, enables our one basis approach to be effective. We discuss the possibility of one observable entanglement detection in a variety of systems, including those without conserved charges, such as the transverse Ising model, reaching the appropriate basis via quantum quench. This provides a much simpler pathway of detection than previous works. It also shows improved sensitivity from Pearson correlation detection techniques.

Published by the American Physical Society
2024
What works to promote staff health in prison settings: a systematic review
Authors: Woodall James
Published: May 2024

Purpose

Given epidemiological data highlighting poor health outcomes for prison staff and correctional workers, this systematic review aims to understand what health promotion interventions, delivered in prison settings, are effective for prison staff health.

Design/methodology/approach

A systematic review was undertaken, with search parameters encompassing papers published over a ten-year period (2013–2023). Health promotion programmes; well-being programmes; and occupational health interventions to support prison staff health as part of a targeted approach or as part of a whole-prison approach were included in the review.

Findings

The review identified 354 studies, of which 157 were duplicates and 187 did not meet the inclusion criteria. This left ten studies in the review from five countries. Reducing the impact of tobacco smoke was the commonly cited intervention, with four studies focusing on smoke-free prison legislation, but other studies focused on stress reduction for staff and supporting holistic health. The papers were of poor methodological quality, with the exception of three included studies that had robust designs. Most studies showed limited or no impact of interventions to support prison staff health, the exception being policy interventions to reduce second-hand smoke exposure.

Originality/value

Prison staff have poor health outcomes and yet limited attention has been paid to interventions to support their health. This review suggests a number of considerations for future policy and practice and direction for further research to improve prison staff health.
Research on the creep response of lead-free die attachments in power electronics
Authors: Gharaibeh Mohammad A. , Wilde Jürgen
Published: May 2024

Purpose

The purpose of this paper is to investigate the thermomechanical response of four well-known lead-free die attach materials: sintered silver, sintered nano-copper particles, gold-tin solders and silver-tin transient liquid phase (TLP) bonds.

Design/methodology/approach

This examination is conducted through finite element analysis. The mechanical properties of all die attach systems, including elastic and Anand creep parameters, are obtained from relevant literature and incorporated into the numerical analysis. Consequently, the bond stress-strain relationships, stored inelastic strain energies and equivalent plastic strains are thoroughly examined.

Findings

The results indicate that silver-tin TLP bonds are prone to exhibiting higher inelastic strain energy densities, while sintered silver and copper interconnects tend to possess higher levels of plastic strains and deformations. This suggests a higher susceptibility to damage in these metallic die attachments. On the other hand, the more expensive gold-based solders exhibit lower inelastic strain energy densities and plastic strains, implying an improved fatigue performance compared to other bonding configurations.

Originality/value

The utilization of different metallic material systems as die attachments in power electronics necessitates a comprehensive understanding of their thermomechanical behavior. Therefore, the results of the present paper can be useful in the die attach material selection in power electronics.
Symmetric and asymmetric modeling to examine individuals’ intention to follow fitness YouTube channels: an integrated perspective of the UTAUT2 and UGT
Authors: Chiu Weisheng , Won Doyeon , Bae Jung-sup
Published: May 2024

Purpose

The current study aims to explore the determinants of user intentions towards fitness YouTube channels, employing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Uses and Gratifications Theory (UGT) as theoretical frameworks.

Design/methodology/approach

Symmetric and asymmetric analyses were employed for data analysis, utilizing partial least squares-structural equation modeling (PLS-SEM) for symmetric analysis and fuzzy-set qualitative comparative analysis (fsQCA) for asymmetric analysis.

Findings

The study revealed significant impacts of most UTAUT2 determinants and all UGT determinants on user intentions. Additionally, the fsQCA results supported the concept of equifinality, indicating that various configurations of causal combinations can predict a high level of behavioral intention. These findings underscore the significance of comprehending user motivations and factors related to technology and social media in the context of maintaining or increasing followership and viewership for fitness content providers.

Originality/value

The findings suggest that individuals with high expectations and facilitating conditions, as per UTAUT, and heightened hedonic and socializing motivations, in line with UGT, are more inclined to follow fitness YouTube channels. This study offers valuable insights for fitness content creators and marketers navigating the complexities of the digital age.
Replicating the Nordic welfare model: policy prescriptions that recognize the cultural antecedents of solidarity
Authors: Lakeman Amy , Jindra Michael
Published: May 2024

Purpose

In this article, we examine the historical and cultural foundations of Nordic states’ strong contemporary social indicators to understand whether their successes can be replicated in other contexts.

Design/methodology/approach

We draw on a range of academic literature to frame a comparison of two regions’ cultural and theological roots, identifying contrasts to make arguments about prescriptions for contemporary welfare policy.

Findings

We find Nordic history contributes to a duty-based culture with strong cohesion and social trust. These cultural norms make palatable welfare policies with strong activation measures, while the US model prefers to avoid the latter because of its strong cultural orientation to rights and autonomy.

Social implications

To mitigate differences between the Nordic states and other cultural contexts, policymakers seeking to replicate Nordic welfare successes should consider welfare programming that combines stronger activation policies with oversight and relational components that mitigate gaps in social cohesion.

Originality/value

We uniquely bring together the literature on comparative welfare policy and on religion and culture to understand the precursors of contemporary attitudes and their implications for welfare policy prescriptions.
Safeguarding carers: literature review on what is known about carers who are abused by the people they provide care for
Authors: Anka Ann , Penhale Bridget
Published: May 2024

Purpose

The purpose of this paper is to provide a literature review on what is known about unpaid family carers who are at risk of or have experienced abuse from the people they provide care for and relevant policy/legal and practice responses for affected family carers.

Design/methodology/approach

A literature search was carried out to locate literature relating to unpaid family carers who are at risk of or have experienced abuse from the people they provide care for. This also incorporated grey literature, including policy guidance and law, to determine the existing knowledge base, gaps in practice and areas that might require further research.

Findings

The findings suggest that although carer harm is serious, it is under-researched. In addition, the unique needs of unpaid family carers who are at risk of or have experienced abuse, violence and harm from the people they provide care for are subsumed in safeguarding policy/law processes and practice under the auspices of the protection of “adults at risk” rather than the protection of “carers at risk”.

Research limitations/implications

It is important that those who support unpaid family carers who are at risk of abuse and harm know about their unique safeguarding needs and concerns to offer appropriate support. It is also apparent that policy and law need to address the gap in provision relating to the unique safeguarding concerns involving the abuse of unpaid family carers by the people they provide care for. This paper is based on this literature review and not on other types of research.

Originality/value

The paper provides insights into what is known about the abuse of unpaid family carers by the people they provide care for, and the policy/legal and practice responses to affected unpaid family carers. It contributes to the body of knowledge on carer abuse and safeguarding carers from abuse and harm.
Resilience and purpose as predictors of Portuguese school leaders' work well-being
Authors: Castro Silva José , Almeida Ana Patricia , Pacheco Patricia , Ferreira Marco
Published: May 2024

Purpose

Resilience and purpose have been associated with work well-being. However, limited empirical evidence exists on the liaison between these constructs and Portuguese school leaders' psychological and physical distress and work well-being. This study explored the relationships between resilience, purpose, and well-being in 921 teachers who perform leadership roles in Portuguese schools.

Design/methodology/approach

Participants filled out an online self-report questionnaire, providing information on sociodemographic variables. Additionally, they responded to four questionnaires evaluating purpose (PURP), resilience (RES), psychological distress (PsyD), physical distress (PhyD), and work well-being (WWB). Data were analysed through structural equation modelling and mediation analysis.

Findings

The findings show that psychological and physical distress negatively predict school leadership work well-being, whereas resilience and purpose positively predict work well-being. The mediating analysis revealed one indirect mediation effect: resilience buffered the psychological distress and work well-being relationship.

Originality/value

The main findings align with existing literature and uniquely contribute to understanding the interplay between resilience, purpose, psychological and physical distress, and work well-being. This study provides empirical support for a conceptual model claiming that purpose and resilience promote school leaders' work well-being.
Growth in rural Punjab: inclusiveness or pseudo-inclusiveness?
Authors: Chadda Ishu
Published: May 2024

Purpose

The main purpose of this paper is to examine the status of poverty and its reduction by following the inclusive development approach. This study is designed to examine the benefits obtained from development programs, assess the government’s commitment to alleviating social inequality, and its impacts on the redistribution of wealth and poverty reduction.

Design/methodology/approach

To evaluate the implementation of the various development schemes and enhance grass-roots participation, a survey was carried out on 540 households, selected through multistage stratified sampling techniques in three different states of Punjab. The study employed an exploratory factor analysis on 21 independent variables to identify the key factors influencing poverty reduction subsequently followed by the binary logistic regression to access the sectoral impact of inclusiveness on poverty reduction in Punjab.

Findings

Exploratory Factor analysis extracted six key factors from the selected 21 variables, also called statements: “'Housing Development Resources”; “Human Capital Variables”; “Livelihood Essentials”, “Medical and Family Welfare Benefits”; “Receiving Educational Benefits”; and Social Security Benefits’. Binary logistic regression revealed that Housing Development Resources, Human Capital Variables, and Receiving Educational Facilities, significantly predict the likelihood of poverty reduction with inclusive growth in Punjab.

Practical implications

To provide basic amenities to rural people, increased people’s participation, decentralized planning, extended irrigation facilities, improved equipped facilities, and improved cultivation techniques are pivotal. The Indian Government has implemented several programs and projects to develop and support rural households. However, these schemes have faced many challenges such as rigidity, non-adaptability to local conditions, late disbursements of funds, reallocation of funds to unrelated expenditures by some states, embezzlement, and bribery demands. Hence, the findings indicate the presence of pseudo-inclusivity in Punjab’s growth.

Originality/value

The study’s uniqueness lies in its focus on selected districts of Punjab and also its application of exploratory factor analysis and binary logistic regression to construct a statistical model from the selected variables.
Private investigations and ethical orientations: a cause for concern?
Authors: Kapend Richard , Button Mark , Stiernstedt Peter
Published: May 2024

Purpose

A significant number of criminal and deviant acts are investigated by nonpolice actors. These include private investigators who charge fees for their services, professional services firms such as firms of accountants who also charge fees, in-house investigators employed by private organisations and in-house investigators of public sector organisations who are not sworn police officers. Some of these investigators, such as private investigators, have been exposed in unethical activities such as illegal surveillance and blagging to name some. In this respect, this study aims to uncover the ethical orientations of investigators using cluster analysis.

Design/methodology/approach

This study is based upon an online survey of private investigators predominantly in the UK, i.e. investigators beyond the public police. An innovate statistical inferential analysis was used to investigate the sample which resulted in the development of three ethical orientations of such investigators.

Findings

Based upon a survey response from 331 of these types of investigators this study illustrates the extent they engage in unethical activities, showing a very small minority of largely private investigators who engage in such activities.

Originality/value

A unique feature of this study is the use of an innovative statistical approach using an unsupervised machine learning model, namely, TwoStep cluster analysis, to successfully group and classify respondents based on their ethical orientation. The model derived three types of ethical orientation: ethical, inbetweeners and risk takers.
A novel deep learning method to use feature complementarity for review helpfulness prediction
Authors: Li Xinzhe , Li Qinglong , Jeong Dasom , Kim Jaekyeong
Published: May 2024

Purpose

Most previous studies predicting review helpfulness ignored the significance of deep features embedded in review text and instead relied on hand-crafted features. Hand-crafted and deep features have the advantages of high interpretability and predictive accuracy. This study aims to propose a novel review helpfulness prediction model that uses deep learning (DL) techniques to consider the complementarity between hand-crafted and deep features.

Design/methodology/approach

First, an advanced convolutional neural network was applied to extract deep features from unstructured review text. Second, this study used previous studies to extract hand-crafted features that impact the helpfulness of reviews and enhance their interpretability. Third, this study incorporated deep and hand-crafted features into a review helpfulness prediction model and evaluated its performance using the Yelp.com data set. To measure the performance of the proposed model, this study used 2,417,796 restaurant reviews.

Findings

Extensive experiments confirmed that the proposed methodology performs better than traditional machine learning methods. Moreover, this study confirms through an empirical analysis that combining hand-crafted and deep features demonstrates better prediction performance.

Originality/value

To the best of the authors’ knowledge, this is one of the first studies to apply DL techniques and use structured and unstructured data to predict review helpfulness in the restaurant context. In addition, an advanced feature-fusion method was adopted to better use the extracted feature information and identify the complementarity between features.
It’s not just “who” you know, but “how” you know them: how social and commercial relationships differentially influence customer discounts
Authors: Johnson Bryan , Ross William T.
Published: May 2024

Purpose

The purpose of this study is to contribute to previous research on customer relationships by quantitatively examining differences in the monetary benefits obtained by consumers using social and commercial relationships to make purchases from small and medium-sized enterprises (SMEs).

Design/methodology/approach

Customer transaction and relationship data from an SME in the USA is used to quantitatively assess the value of different marketplace relationships in an entrepreneurial context. Tobit regression is used to empirically model and test the impact of specific relationship characteristics on customer discounts.

Findings

Customers using social connections to make purchases obtain significantly larger discounts than customers using commercial connections; customers using direct connections attain significantly larger discounts than consumers using indirect connections (referrals). Interestingly, when examined by connection type, direct and indirect connections do not produce significant differences for social connections, yet they yield notable differences for commercial connections. The findings provide valuable insights to entrepreneurs for understanding and managing customer relationships.

Originality/value

This study empirically demonstrates that social relationships can be both prevalent and influential in the marketplace. The methodology used to quantitatively assess the monetary value associated with different methods of engaging with SMEs allows objective comparisons among different types of customer relationships. Quantification also allows important relationship characteristics to be empirically examined, including how the relationships compare to one another and to nonpersonal marketing activities. Ultimately, these novel contributions generate important insights to help marketers and entrepreneurs better understand customer relationships.