bluuebunny/crossref_metadata_2025 huggingface dataset:
Probing the nature of the X-ray source IGR J16327-4940 with Chandra
Authors: Sidoli L , Sguera V , Postnov K , Esposito P , Oskinova L , Mereminskiy I A
Published: September 2023

We report on the results of a Chandra observation of the source IGR J16327-4940, suggested to be a high-mass X-ray binary hosting a luminous blue variable star (LBV). The source field was imaged by ACIS-I in 2023 to search for X-ray emission from the LBV star and eventually confirm this association. No X-ray emission is detected from the LBV star, with an upper limit on the X-ray luminosity of L$_{\rm 0.5-10 \,keV}\lt 2.9(^{+1.6} _{-1.1})\times 10^{32}$ erg s−1 (at the LBV distance d = 12.7$^{+3.2} _{-2.7}$ kpc). We detected 21 faint X-ray sources, 8 of which inside the INTEGRAL error circle. The brightest one is the best candidate soft X-ray counterpart of IGR J16327-4940, showing a hard power-law spectrum and a flux corrected for the absorption UF0.5–10 keV = 2.5 × 10−13 erg cm−2 s−1, implying a luminosity of 3.0 × 1033 d$_{10~{\rm kpc}}^2$ erg s−1. No optical/near-infrared counterparts have been found. Previous X–ray observations of the source field with Swift/XRT and ART-XC did not detect any source consistent with the INTEGRAL position. These findings exclude the proposed LBV star as the optical association, and pinpoint the most likely soft X-ray counterpart. In this case, the source properties suggest a low-mass X-ray binary, possibly a new member of the very faint X-ray transient class.
The ‘small’ asteroid population: a spectroscopic survey
Authors: Michimani Jonatan , Rondón Eduardo , Perna Davide , Ieva Simone , Dotto Elisabetta , Mazzotta Epifani Elena , Barucci Antonella , Petropoulou Vasiliki , Lazzaro Daniela
Published: September 2023

The study of near-Earth objects (NEOs) allow us to obtain information on the Solar system smallest bodies due to their closeness to Earth. In this work, we present the results of visible spectroscopic observations of 43 small and newly discovered NEOs, obtained during eighteen observing runs between October 2020 and December 2021, using the Goodman High Throughput Spectrograph at the 4.1-m Southern Astrophysical Research telescope (Cerro Pachón, Chile). We found a taxonomic distribution dominated by S-type asteroids but with an overabundance of A- and D-types. This result is in agreement with recent works on NEOs’ characterization and has implications for possible differences in the taxonomic distribution of ‘large’ and ‘small’ objects and emphasizes the idea of a non-homogeneous NEO population.
Reviving stochasticity: uncertainty in SMBH binary eccentricity is unavoidable
Authors: Rawlings Alexander , Mannerkoski Matias , Johansson Peter H , Naab Thorsten
Published: September 2023

We study supermassive black hole (SMBH) binary eccentricity of equal-mass galaxy mergers in N-body simulations with the ketju code, which combines the gadget-4 fast multipole gravity solver with accurate regularized integration and post-Newtonian corrections around SMBHs. In simulations with realistic, high-eccentricity galactic merger orbits, the hard binary eccentricity is found to be a non-linear function of the deflection angle in the SMBH orbit during the final, nearly radial close encounter between the SMBHs before they form a bound binary. This mapping between the deflection angle and the binary eccentricity has no apparent resolution dependence in our simulations spanning the resolution range of 1 × 105 to 8 × 106 particles per galaxy. The mapping is also captured using a simple model with an analytical potential, indicating that it is driven by the interplay between a smooth asymmetric stellar background potential and dynamical friction acting on the SMBHs. Due to the non-linearity of this mapping, in eccentric major merger configurations, small, parsec-scale variations in the merger orbit can result in binary eccentricities varying in nearly the full possible range between e = 0 and e = 1. In idealized simulations, such variations are caused by finite resolution effects, and convergence of the binary eccentricity can be achieved with increasing resolution. However, in real galaxies, other mechanisms such as nuclear gas and substructure that perturb the merger orbit are likely to be significant enough for the binary eccentricity to be effectively random. Our results indicate that the distribution of these effectively random eccentricities can be studied using even moderate resolution simulations.
Void BAO measurements on quasars from eBOSS
Authors: Tamone Amélie , Zhao Cheng , Forero-Sánchez Daniel , Variu Andrei , Chuang Chia-Hsun , Kitaura Francisco-Shu , Kneib Jean-Paul , Tao Charling
Published: September 2023

We present the clustering of voids based on the quasar (QSO) sample of the extended Baryon Oscillation Spectroscopic Survey Data Release 16 in configuration space. We define voids as overlapping empty circumspheres computed by Delaunay tetrahedra spanned by quartets of quasars, allowing for an estimate of the depth of underdense regions. To maximize the baryon acoustic oscillation (BAO) signal-to-noise ratio, we consider only voids with radii larger than 36h−1Mpc. Our analysis shows a negative BAO peak in the cross-correlation of QSOs and voids. The joint BAO measurement of the QSO autocorrelation and the corresponding cross-correlation with voids shows an improvement in 70  per cent of the QSO mocks with an average improvement of $\sim 5~{{\ \rm per\ cent}}$. However, on the SDSS data, we find no improvement compatible with cosmic variance. For both mocks and data, adding voids does not introduce any bias. We find under the flat ΛCDM assumption, a distance joint measurement on data at the effective redshift zeff = 1.51 of DV(zeff) = 26.558 ± 0.553. A forecast of a DESI-like survey with 1000 boxes with a similar effective volume recovers the same results as for light-cone mocks with an average of 4.8  per cent improvement in 68  per cent of the boxes.
A census of rotating radio transients at 150 MHz with the Irish LOFAR station
Authors: McKenna D J , Keane E F , Gallagher P T , McCauley J
Published: September 2023

Rotating radio transients (RRATs) are neutron stars that emit detectable radio bursts sporadically. They are statistically distinct in the neutron star population, in many observable properties, but by their nature are practically difficult to study in depth. In this paper, we present the results from 1408 h of observations of RRAT candidates using the Irish station of the Low Frequency Array (LOFAR) at 150 MHz. As of October 2022, this census involved observing 113 sources, leading to 29 detections which were then followed up systematically. Single-pulse emission was detected from 25 sources, and periodic emission from 14 sources. Eighteen sources were found to have emission behaviour that is not discussed in prior works using LOFAR instruments. Four novel or modified source periods have been determined, ranging from 1.5 to 3.9 s, and eight new or updated phase-coherent pulsar timing ephemerides have been produced using detected bursts. One unexpected single-pulse with a clearly-Galactic dispersion measure was detected as a part of this work but has not been re-detected in follow-up observations. Observations are ongoing to expand the number of observed sources and further characterize and improve ephemerides for the detected sources. This census has demonstrated the capability for international LOFAR stations to detect, monitor, and characterize a significant fraction of these unique sources.
Telomeric i-motifs and C-strands inhibit parallel G-quadruplex extension by telomerase
Authors: El-Khoury Roberto , Roman Morgane , Assi Hala Abou , Moye Aaron L , Bryan Tracy M , Damha Masad J
Published: September 2023

Telomeric C-rich repeated DNA sequences fold into tetrahelical i-motif structures in vitro at acidic pH. While studies have suggested that i-motifs may form in cells, little is known about their potential role in human telomere biology. In this study, we explore the effect of telomeric C-strands and i-motifs on the ability of human telomerase to extend G-rich substrates. To promote i-motif formation at neutral pH, we use telomeric sequences where the cytidines have been substituted with 2′-fluoroarabinocytidine. Using FRET-based studies, we show that the stabilized i-motifs resist hybridization to concomitant parallel G-quadruplexes, implying that both structures could exist simultaneously at telomeric termini. Moreover, through telomerase activity assays, we show that both unstructured telomeric C-strands and telomeric i-motifs can inhibit the activity and processivity of telomerase extension of parallel G-quadruplexes and linear telomeric DNA. The data suggest at least three modes of inhibition by C-strands and i-motifs: direct hybridization to the substrate DNA, hybridization to nascent product DNA resulting in early telomerase dissociation, and interference with the unique mechanism of telomerase unwinding and extension of a G-quadruplex. Overall, this study highlights a potential inhibitory role for the telomeric C-strand in telomere maintenance.
Global profiling of ribosomal protein acetylation reveals essentiality of acetylation homeostasis in maintaining ribosome assembly and function
Authors: Ni Jinjing , Li Shuxian , Lai Yanan , Wang Zuoqiang , Wang Danni , Tan Yongcong , Fan Yongqiang , Lu Jie , Yao Yu-Feng
Published: September 2023

Acetylation is a global post-translational modification that regulates various cellular processes. Bacterial acetylomic studies have revealed extensive acetylation of ribosomal proteins. However, the role of acetylation in regulating ribosome function remains poorly understood. In this study, we systematically profiled ribosomal protein acetylation and identified a total of 289 acetylated lysine residues in 52 ribosomal proteins (r-proteins) from Salmonella Typhimurium. The majority of acetylated lysine residues of r-proteins were found to be regulated by both acetyltransferase Pat and metabolic intermediate acetyl phosphate. Our results show that acetylation plays a critical role in the assembly of the mature 70S ribosome complex by modulating r-proteins binding to rRNA. Moreover, appropriate acetylation is important for the interactions between elongation factors and polysomes, as well as regulating ribosome translation efficiency and fidelity. Dysregulation of acetylation could alter bacterial sensitivity to ribosome-targeting antibiotics. Collectively, our data suggest that the acetylation homeostasis of ribosomes is crucial for their assembly and function. Furthermore, this mechanism may represent a universal response to environmental signals across different cell types.
Coordination between aminoacylation and editing to protect against proteotoxicity
Authors: Zhang Hong , Murphy Parker , Yu Jason , Lee Sukyeong , Tsai Francis T F , van Hoof Ambro , Ling Jiqiang
Published: September 2023

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes that ligate amino acids to tRNAs, and often require editing to ensure accurate protein synthesis. Recessive mutations in aaRSs cause various neurological disorders in humans, yet the underlying mechanism remains poorly understood. Pathogenic aaRS mutations frequently cause protein destabilization and aminoacylation deficiency. In this study, we report that combined aminoacylation and editing defects cause severe proteotoxicity. We show that the ths1-C268A mutation in yeast threonyl-tRNA synthetase (ThrRS) abolishes editing and causes heat sensitivity. Surprisingly, experimental evolution of the mutant results in intragenic mutations that restore heat resistance but not editing. ths1-C268A destabilizes ThrRS and decreases overall Thr-tRNAThr synthesis, while the suppressor mutations in the evolved strains improve aminoacylation. We further show that deficiency in either ThrRS aminoacylation or editing is insufficient to cause heat sensitivity, and that ths1-C268A impairs ribosome-associated quality control. Our results suggest that aminoacylation deficiency predisposes cells to proteotoxic stress.
Specificity of cancer-related chromosomal translocations is linked to proximity after the DNA double-strand break and subsequent selection
Authors: Canoy Reynand Jay , Shmakova Anna , Karpukhina Anna , Lomov Nikolai , Tiukacheva Eugenia , Kozhevnikova Yana , André Franck , Germini Diego , Vassetzky Yegor
Published: September 2023

Most cancer-related chromosomal translocations appear to be cell type specific. It is currently unknown why different chromosomal translocations occur in different cells. This can be due to either the occurrence of particular translocations in specific cell types or adaptive survival advantage conferred by translocations only in specific cells. We experimentally addressed this question by double-strand break (DSB) induction at MYC, IGH, AML and ETO loci in the same cell to generate chromosomal translocations in different cell lineages. Our results show that any translocation can potentially arise in any cell type. We have analyzed different factors that could affect the frequency of the translocations, and only the spatial proximity between gene loci after the DSB induction correlated with the resulting translocation frequency, supporting the ‘breakage-first’ model. Furthermore, upon long-term culture of cells with the generated chromosomal translocations, only oncogenic MYC–IGH and AML–ETO translocations persisted over a 60-day period. Overall, the results suggest that chromosomal translocation can be generated after DSB induction in any type of cell, but whether the cell with the translocation would persist in a cell population depends on the cell type-specific selective survival advantage that the chromosomal translocation confers to the cell.
Shared decision making in elderly patients with kidney failure
Authors: Kanbay Mehmet , Basile Carlo , Battaglia Yuri , Mantovani Alessandro , Yavuz Furkan , Pizzarelli Francesco , Luyckx Valerie A , Covic Adrian , Liakopoulos Vassilios , Mitra Sandip
Published: September 2023

‘Elderly’ is most commonly defined as an individual aged 65 years or older. However, this definition fails to account for the differences in genetics, lifestyle and overall health that contribute to significant heterogeneity among the elderly beyond chronological age. As the world population continues to age, the prevalence of chronic diseases, including chronic kidney disease (CKD), is increasing and CKD frequently progresses to kidney failure. Moreover, frailty represents a multidimensional clinical entity highly prevalent in this population, which needs to be adequately assessed to inform and support medical decisions. Selecting the optimal treatment pathway for the elderly and frail kidney failure population, be it haemodialysis, peritoneal dialysis or conservative kidney management, is complex because of the presence of comorbidities associated with low survival rates and impaired quality of life. Management of these patients should involve a multidisciplinary approach including doctors from various specialties, nurses, psychologists, dieticians and physiotherapists. Studies are mostly retrospective and observational, lacking adjustment for confounders or addressing selection and indication biases, making it difficult to use these data to guide treatment decisions. Throughout this review we discuss the difficulty of making a one-size-fits-all recommendation for the clinical needs of older patients with kidney failure. We advocate that a research agenda for optimization of the critical issues we present in this review be implemented. We recommend prospective studies that address these issues, and systematic reviews incorporating the complementary evidence of both observational and interventional studies. Furthermore, we strongly support a shared decision-making process matching evidence with patient preferences to ensure that individualized choices are made regarding dialysis vs conservative kidney management, dialysis modality and optimal vascular access.
Multifunction-oriented high-mobility polymer semiconductors
Authors: Zhu Mingliang , Guo Yunlong , Liu Yunqi
Published: September 2023

Recent progress in multifunction-oriented high-mobility polymer semiconductors is profiled, with current challenges and future directions proposed in this perspective.
Evaluation on the Sex-Specific Association Between Cigarette Smoke Exposure and Inflammation Markers—C-Reactive Protein and White Blood Cell Count
Authors: Koh Dong-Hee , Choi Sangjun , Park Ju-Hyun , Lee Sang-Gil , Kim Hwan-Cheol , Kim Inah , Park Dong-Uk
Published: September 2023

Introduction

Cigarette smoke increases peripheral white blood cell (WBC) count. However, the dose-dependent association between smoking and C-reactive protein (CRP), an important inflammatory marker, has been reported as inconsistent.

Aims and Methods

Here, we evaluated the associations between smoking and CRP using both smoking questionnaires and urine cotinine as exposure markers. The Korea National Health and Nutrition Examination Survey data were used for analyzing the associations. Multiple regression analyses were performed to examine the associations between cigarette smoke exposure, as assessed by questionnaires and urine cotinine, and health effects, as measured by CRP and WBC count, controlling for potential confounders. The confounders, including age, sex, body mass index, blood pressure, cholesterol, glucose, alanine aminotransferase, and uric acid, were selected a priori based on the literature.

Results

A total of 11 435 participants were included for analysis. For the exposure-response relationship, the results indicated a significant increase in CRP levels in male smokers compared to male nonsmokers (p = .002), whereas no significant increase was found in female smokers compared to female nonsmokers (p = .680). For the dose–response relationship, a significant positive association was observed between urine cotinine and CRP in male smokers (p = .018), whereas no significant association was found in female smokers (p = .508). WBC count consistently showed significant exposure-response and dose–response relationships in both sexes.

Conclusions

WBC count was found to be a consistent effect marker of cigarette smoke exposure, while the association between CRP level and smoking was inconsistent and varied by sex. The sex-specific response to cigarette smoke exposure warrants further exploration in future studies.

Implications

Cigarette smoke exposure is known to increase inflammation and has been thought to increase CRP, a significant inflammation marker. However, recent studies have reported conflicting results regarding the dose-dependent association between cigarette smoke exposure and CRP. This study found that the association between smoking and CRP is inconsistent and varies by sex, showing significant exposure response in men but not in women. Furthermore, the study suggests that WBC count is a more consistent marker for cigarette smoke exposure.
Exchange rates and binary political events
Authors: Venturi Pedro , Ferreira Alex , Gozluklu Arie , Gong Yujing
Published: September 2023

This article introduces a rational expectations model that explains exchange rate dynamics and the predictability of forecast errors using private (aggregated via order flow) and public (probabilities of a binary event) information. We test the model for the periods leading up to the presidential impeachment vote in Brazil, the Brexit Referendum, and Donald Trump’s election in 2016. Proxies of the physical probabilities of these events reveal that they are a crucial source of pricing information for the BRL, GBP, and MXN currency pairs with the US dollar. They also explain forecast errors. The information content of order flow changes before and after an actual regime change resolves uncertainty.
Beyond Institutional Adaptation: Legislative Europeanisation and Parliamentary Attention to the EU in the Hungarian Parliament
Authors: Bíró-Nagy András , Buzogány Aron
Published: September 2023

While studies of the formal adaptation of parliaments to the European Union (EU) have dominated legislative scholarship in the last two decades, there is a growing interest in the substantive impact of the EU on legislative production and parliamentary behaviour. We contribute to this research agenda by exploring the effects of Europeanisation on the national parliament of one democratically backsliding EU member state, Hungary. Comparing periods marked by Europhile and Eurosceptic parliamentary majorities between 2004 and 2018 shows that governmental attitudes towards the EU are not reflected in parliamentary law-making and that parliamentary attention is mainly influenced by the level of Europeanisation of the policy field. This shows that backsliding governments do not generally oppose greater integration and underscores the necessity to distinguish between rhetorical Euroscepticism and Eurosceptic legislative action.
From ACEs to early relational health: Implications for clinical practice
Authors: Williams Robin C
Published: September 2023

Children grow and develop in an environment of relationships. Safe, stable, nurturing relationships help build resilience and buffer the negative impact of adverse experiences. Promoting relational health in clinical practice shifts the focus from adverse childhood experiences (ACEs) to positive childhood experiences (PCEs). This approach evaluates a family’s strengths and assets, and can be incorporated into both well-child and subspecialty care. While the optimal window for such interventions is in the prenatal period or as early as possible within the first 3 years of life, it is never too late to start. This statement describes how clinicians can bring a relational health approach to any medical encounter by understanding: what toxic stress is and how it can affect the developing brain, family relationships, and child development; how positive relationships, experiences, and behaviours can help buffer such effects and build resilience; observable signs of relational health and risk in parent–child interactions; the attributes of trustful, therapeutic relationships with families; and how to optimize these benefits through conversation and clinical practice.
Big data policing: The use of big data and algorithms by the Netherlands Police
Authors: Schuilenburg Marc , Soudijn Melvin
Published: September 2023

In recent years, the rise of big data has revolutionized many domains, including policing. Research is lacking, however, on the various ways in which the police use big data applications. This study provides new insights into the ways the Netherlands Police currently use big data and algorithmic applications. Based on a novel data source—job vacancies in the IT domain for the Netherlands Police—we distinguish three areas in which big data is used: frontline policing, criminal investigations, and intelligence. Our research shows that the use of big data by the Netherlands Police mainly involves relatively simple applications and that—in contrast to police forces in the USA—big data applications with the objective of assessing risks are the least common. The research also shows that big data policing leads to greater discretionary powers for police functions such as software developers and network designers.
Circulating sex hormone-binding globulin levels and ischemic stroke risk: a Mendelian randomization study
Authors: Zeng Youjie , Cao Si , Yang Heng
Published: September 2023

Purpose

Previous studies have presented conflicting findings regarding the protective effects of circulating sex hormone-binding globulin (SHBG) on ischemic stroke (IS). This study aimed to assess the causal effect of SHBG on IS using Mendelian randomization (MR) analysis and to identify potential mediators.

Methods

First, the causal effect of SHBG on any IS (AIS), cardioembolic stroke (CES), large artery stroke (LAS), and small vessel stroke (SVS) was assessed by inverse variance weighed (IVW) method. Two additional MR methods (weighted median and MR-Egger) were used to supplement the IVW results. Subsequently, a two-step MR was further performed to assess whether three glycemic profiles [fasting glucose, fasting insulin, and glycated hemoglobin (HbA1c)] and five lipid profiles (high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, non-HDL cholesterol, total cholesterol, and triglycerides) mediated the causal effect. Furthermore, Cochrane’s Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were performed for sensitivity analyses.

Results

The IVW results showed that SHBG significantly reduced SVS risk (odds ratio= 0.60, 95% confidence interval: 0.47–0.77, P = 4.60E-05). The weighted median and MR-Egger results were parallel to IVW. However, no significant associations were found between SHBG and AIS, CES, and LAS. Mediation analysis indicated that HbA1c may be involved in SHBG reducing SVS risk. Sensitivity tests demonstrated the reliability of causal estimates.

Conclusions

Circulating SHBG levels may decrease SVS risk by lowering HbA1c levels. Therefore, individuals with low circulating SHBG levels should focus on glycemic control to reduce future SVS risk.
Differences in empathy levels among physicians based on specialty: a nationwide cross-sectional study
Authors: Watari Takashi , Houchens Nathan , Otsuka Tomoe , Endo Takeshi , Odagawa Seiji , Nakano Yasuhisa , Kataoka Hitomi , Miwa Mamoru , Yamasaki Daisaku , Tokuda Yasuharu , Shiraishi Yoshihiko , Sakaguchi Kota
Published: September 2023

Purpose of study

A physician’s ability to empathize is crucial for patient health outcomes, and this differs according to speciality, personal characteristics, and environmental factors. This study aimed to examine the empathy levels among physicians based on their specialities and to identify the influencing factors.

Study design

A nationwide, online, cross-sectional survey was conducted using the Nikkei Business Publication online physician member homepage. Participants were 5441 physicians in Japan registered as members of Nikkei Medical Online across 20 specialities. We used the Jefferson Scale of Empathy (JSE) to measure the physicians’ empathy levels. Cronbach’s alpha was 0.84.

Results

The mean JSE score was 100.05, SD = 15.75. Multivariate analyses showed that the highest JSE scores were for general medicine [+5.58, 95% confidence interval (CI) 2.60–8.56], general surgery (+3.63, 95% CI 0.97–6.28), psychiatry (+3.47, 95% CI 1.76–5.17), and paediatrics (+1.92, 95% CI 0.11–3.73). Factors associated with higher JSE scores were being female (+5.86, 95% CI 4.68–7.04), managers (+1.11, 95% CI 0.16–2.07), working in a small hospital (+2.19, 95% CI 0.23–4.15), and with children (+3.32, 95% CI 2.29–4.36).

Conclusions

A significant decrease in the empathy levels was found when the parent of the participant was also a medical provider. Being a general medicine physician or a female physician in a high position who has children was positively and significantly correlated with high empathy levels.
Novel insights into the role of leaf in the cutting process of Camellia sinensis using physiological, biochemical and transcriptome analyses
Authors: Zhang Hong , Chen Binrui , Zhao Xiaoyi , Hu Jing , Dong Zhijie , Xiao Hui , Yuan Yanwen , Guo Fei , Wang Yu , Ni Dejiang , Wang Pu
Published: September 2023

Cuttage is the preferred approach for rapid propagation of many species including tea plant (Camellia sinensis). Leaf serves as a key part of nodal cutting, but there is a lack of systematic research on its role in the cutting process. In this study, 24 tea cultivars were employed to prove the necessity of leaf and light during cuttage. Further leaf physiological parameters found that lower net photosynthesis rate probably promoted rooting. Phytohormone content detection showed that auxin content and composition pattern were related to rooting ability. Leaf transcriptome analyses of cuttings from a representative easy-to-root cultivar (cv. Echa 10) revealed that genes involved in carbohydrate metabolism, signal transduction, metabolite biosynthesis and transportation were differentially expressed during the rooting process. CsTSA1, CsYUC10, CsAUX1s, CsPIN3 and CsPIN5 were selected as the candidate genes, which possibly regulate the rooting of nodal cuttings. These results illustrate the necessity of the leaf in cuttage and provide molecular evidence that leaf is an important place for signal transduction, metabolite synthesis and transport during the rooting process.
Bone histology of the Late Pleistocene Prolagus sardus (Lagomorpha: Mammalia) provides further insights into life-history strategy of insular giant small mammals
Authors: Fernández-Bejarano Eva , Blanco Alejandro , Angelone Chiara , Zhang Zhaoqun , Moncunill-Solé Blanca
Published: September 2023

Fossils provide an excellent opportunity to study and understand the evolution of insular environments free of human-made perturbations. Here, we evaluated the life-history traits and strategy of the extinct insular giant Prolagus sardus (Mammalia: Lagomorpha) by examining microscopically its fossilized bone tissues (osteohistology, skeletochronology, and quantitative geometry). For this task, a complete ontogenetic series of femora retrieved from the Late Pleistocene Grotta della Medusa (NW Sardinia, Italy) were analysed. Our results reveal that: (i) P. sardus’ pups were weaned at large size; (ii) the species’ maturation was delayed in its life cycle; and (iii) P. sardus lived longer than expected for its size. Hence, the giant P. sardus should have a slow pace of life triggered by the low levels of extrinsic mortality of the insular habitat. On the other hand, bone tissue differences between P. sardus and Ochotona were found in the vascularization, slow- growing bone presence, and cortical and medullary growth trajectories. The results obtained in this study concur with the eco-evolutionary responses described to date in extinct insular lagomorphs, as well as provide new empirical evidence about the phenomenon known as ‘insular gigantism’ as a pattern of evolution of small-sized mammals in genuine insular ecosystems.
DOCK3 regulates normal skeletal muscle regeneration and glucose metabolism
Authors: Samani Adrienne , Karuppasamy Muthukumar , English Katherine G. , Siler Colin A. , Wang Yimin , Widrick Jeffrey J. , Alexander Matthew S.
Published: September 2023

DOCK (dedicator of cytokinesis) is an 11‐member family of typical guanine nucleotide exchange factors (GEFs) expressed in the brain, spinal cord, and skeletal muscle. Several DOCK proteins have been implicated in maintaining several myogenic processes such as fusion. We previously identified DOCK3 as being strongly upregulated in Duchenne muscular dystrophy (DMD), specifically in the skeletal muscles of DMD patients and dystrophic mice. Dock3 ubiquitous KO mice on the dystrophin‐deficient background exacerbated skeletal muscle and cardiac phenotypes. We generated Dock3 conditional skeletal muscle knockout mice (Dock3 mKO) to characterize the role of DOCK3 protein exclusively in the adult muscle lineage. Dock3 mKO mice presented with significant hyperglycemia and increased fat mass, indicating a metabolic role in the maintenance of skeletal muscle health. Dock3 mKO mice had impaired muscle architecture, reduced locomotor activity, impaired myofiber regeneration, and metabolic dysfunction. We identified a novel DOCK3 interaction with SORBS1 through the C‐terminal domain of DOCK3 that may account for its metabolic dysregulation. Together, these findings demonstrate an essential role for DOCK3 in skeletal muscle independent of DOCK3 function in neuronal lineages.
Reduction of Work-Related Musculoskeletal Disorders in Plastic Surgeons by Introduction of a Posture Training Device
Authors: Segal Rachel Marie , Zaldana-Flynn Michelle , Dean Riley , Gosman Amanda A. , Reid Chris M.
Published: September 2023

Background

Plastic surgeons have an increased risk for the development of musculoskeletal disorders because of frequent poor ergonomics of the operating room. This study characterizes selected plastic surgery procedures, with an attempt to identify high-risk procedures and procedural components as well as the impact of biofeedback on surgical ergonomics.

Methods

A commercially available posture training device was used to initially record neck and spine positioning and later to send biofeedback to prompt surgeons to correct posture. Device data were correlated with in-person observations to characterize factors associated with more time spent in the slouched/nonneutral cervical and thoracic spine posture.

Results

The proportion of time spent in the upright position during surgery was significantly different among male and female participants, level of training, participant height, in the sitting versus nonsitting positioning (P < 0.001), with loupes use, and if there was more than an 8-inch height difference between 2 participants (mean, 0.70 ± 0.285). Using the device intervention, all participants spent a larger proportion of operating time upright. Half of these improvements in posture were statistically significant. While in feedback mode, participants experienced shorter and more frequent periods of slouching/nonneutral posture. When comparing the same participant performing the same procedure with and without device biofeedback, 72.2% of participants spent more time in the upright/neutral posture during the surgery when the device was sending feedback.

Conclusions

Biofeedback devices used in the operating room can lead to improved surgical posture, which may translate to reduction of workplace injuries, and overall physician health. This study found that a commercially available posture training device and sitting stools in the operating room could significantly improve physician cervical and thoracic spine posture.
Fatigue reliability analysis of aeroengine blade-disc systems using physics-informed ensemble learning
Authors: Li Xue-Qin , Song Lu-Kai , Choy Yat-Sze , Bai Guang-Chen
Published: September 2023

For the fatigue reliability analysis of aeroengine blade-disc systems, the traditional direct integral modelling methods or separate independent modelling methods will lead to low computational efficiency or accuracy. In this work, a physics-informed ensemble learning (PIEL) method is proposed, i.e. firstly, based on the physical characteristics of blade-disc systems, the complex multi-component reliability analysis is split into a series of single-component reliability analyses; moreover, the PIEL model is established by introducing the mapping of multiple constitutive responses and the multi-material physical characteristics into the ensemble learning; finally, the PIEL-based system reliability framework is established by quantifying the failure correlation with the Copula function. The reliability analysis of a typical aeroengine high-pressure turbine blade-disc system is regarded as an example to verify the effectiveness of the proposed method. Compared with the direct Monte Carlo, support vector regression, neural network, ensemble learning and physics-informed neural network, the proposed method exhibits the highest computing accuracy and efficiency, and is validated to be an efficient method for the reliability analysis of blade-disc systems. The current work can provide a novel insight for physics-informed modelling and fatigue reliability analyses.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Defect driven physics-informed neural network framework for fatigue life prediction of additively manufactured materials
Authors: Wang Lanyi , Zhu Shun-Peng , Luo Changqi , Niu Xiaopeng , He Jin-Chao
Published: September 2023

Additive manufacturing (AM) has attracted many attentions because of its design freedom and rapid manufacturing; however, it is still limited in actual application due to the existing defects. In particular, various defect features have been proved to affect the fatigue performance of components and lead to fatigue scatter. In order to properly assess the influences of these defect features, a defect driven physics-informed neural network (PiNN) is developed. By embedding the critical defects information into loss functions, the defect driven PiNN is enhanced to capture physical information during training progress. The results of fatigue life prediction for different AM materials show that the proposed PiNN effectively improves the generalization ability under small samples condition. Compared with the fracture mechanics-based PiNN, the proposed PiNN provides physically consistent and higher accuracy without depending on the choice of fracture mechanics-based model. Moreover, this work provides a scalable framework being able to integrate more prior knowledge into the proposed PiNN.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
A machine learning study on the fatigue crack path of short crack on an α titanium alloy
Authors: Shen Zhengyu , Lv Guanlin , Fu Daixin , Long Yihao , Zhang Zhouyu , Tan Kai , Li Lang , Wang Qingyuan , Wang Chong
Published: September 2023

In the present study, a physics-informed neural network model based on Bayesian hyperparameter optimization is proposed for the prediction of short crack growth paths. A large number of cyclic loadings at a lower amplitude were applied to an α titanium sample by an ultrasonic fatigue machine to ensure a sufficient amount of data for machine learning. The grain size, grain orientation and grain boundary direction on the path, as well as crack growth direction, were selected as feature data for training the prediction model. The optimizations of the size ratio and the angle operation were conducted to compare different data processing methods, respectively. After evaluation, eventually, a model for predicting crack growth path is obtained with a reliable performance of 10% tolerance on the path angle at each grain boundary. And the prediction effect of the proposed model is better than that of some classic machine learning models and slip trace analysis.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
A physics-guided modelling method of artificial neural network for multiaxial fatigue life prediction under irregular loading
Authors: Zhou Tianguo , Sun Xingyue , Chen Xu
Published: September 2023

To improve the generalization of the artificial neural network (ANN) model on the prediction of multiaxial irregular cases, a physics-guided modelling method is proposed with inspiration from the Basquin–Coffin–Manson equation. The method suggested using two neurons in the last hidden layer of the ANN model and constraining the sign of weight and bias value. In this way, the prior physical knowledge of fatigue life distribution is introduced into the ANN model, which resulted in a satisfactory performance on the life prediction of multiaxial loading cases and better extrapolation ability. Furthermore, the physics-guided ANN model can also provide satisfactory prediction on irregular cases with the training of only regular cases. Compared with the conventional model, the average relative error and root mean squared error (RMSE) of prediction decreased by 33.29% and 44.29%, respectively. It greatly broadens the application scenarios of neural networks on multiaxial fatigue life prediction.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Investigation of flexural behaviour of composite rebars for concrete reinforcement with experimental, numerical and machine learning approaches
Authors: Smolnicki Michał , Lesiuk Grzegorz , Stabla Paweł , Pedrosa Bruno , Duda Szymon , Zielonka Paweł , Lopes Cristiane Caroline Campos
Published: September 2023

Three different types (with glass, basalt and hybrid fibres) of composite rebars manufactured using the pultrusion process were loaded in four-point bending tests. All tests were carried out with acoustic emission sensors to better understand the mechanisms of damage. The data obtained were investigated using standard parameter analysis and also using unsupervised machine learning techniques called K-means. It was found that the best number of clusters is four or five. The numerical model using the finite-element method was calibrated on the basis of the experimental data. Further research will focus on numerical modelling of flexural behaviour of concrete beams reinforced with the presented composite rebars. The presented paper focuses on the characterization of the mechanical properties of composite rebars using a micromechanical approach, as well as analysis of progression damage processes appearing under flexural loading, using different perspectives provided by techniques such as acoustic emission analysis with machine learning-based clustering and numerical simulations. The presented research confirms that the proposed experimental–numerical approach can be applied in order to describe the flexural behaviour of Fibre Reinforcement Polymer (FRP) rods, which is relevant for investigating more complex cases of FRP concrete structures.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Neural optimization machine: a neural network approach for optimization and its application in additive manufacturing with physics-guided learning
Authors: Chen Jie , Liu Yongming
Published: September 2023

Neural networks (NNs) are increasingly used in design to construct the objective functions and constraints, which leads to the needs of optimization of NN models with respect to design variables. A Neural Optimization Machine (NOM) is proposed for constrained single/multi-objective optimization by appropriately designing the NN architecture, activation function and loss function. The NN's built-in backpropagation algorithm conducts the optimization and is seamlessly integrated with the additive manufacturing (AM) process-property model. The NOM is tested using several numerical optimization problems. It is shown that the increase in the dimension of design variables does not increase the computational cost significantly. Next, a brief review of the physics-guided machine learning model for fatigue performance prediction of AM components is given. Finally, the NOM is applied to design processing parameters in AM to optimize the mechanical fatigue properties through the physics-guided NN under uncertainties. One novel contribution of the proposed methodology is that the constrained process optimization is integrated with physics/knowledge and the data-driven AM process-property model. Thus, a physics-compatible process design can be achieved. Another significant benefit is that the training and optimization are achieved in a unified NN model, and no separate process optimization is needed.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Physics-informed machine learning and its structural integrity applications: state of the art
Authors: Zhu Shun-Peng , Wang Lanyi , Luo Changqi , Correia José A. F. O. , De Jesus Abílio M. P. , Berto Filippo , Wang Qingyuan
Published: September 2023

The development of machine learning (ML) provides a promising solution to guarantee the structural integrity of critical components during service period. However, considering the lack of respect for the underlying physical laws, the data hungry nature and poor extrapolation performance, the further application of pure data-driven methods in structural integrity is challenged. An emerging ML paradigm, physics-informed machine learning (PIML), attempts to overcome these limitations by embedding physical information into ML models. This paper discusses different ways of embedding physical information into ML and reviews the developments of PIML in structural integrity including failure mechanism modelling and prognostic and health management (PHM). The exploration of the application of PIML to structural integrity demonstrates the potential of PIML for improving consistency with prior knowledge, extrapolation performance, prediction accuracy, interpretability and computational efficiency and reducing dependence on training data. The analysis and findings of this work outline the limitations at this stage and provide some potential research direction of PIML to develop advanced PIML for ensuring structural integrity of engineering systems/facilities.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Preface to the theme issue ‘physics-informed machine learning and its structural integrity applications'
Authors: Zhu Shun-Peng , De Jesus Abílio M. P. , Berto Filippo , Michopoulos John G. , Iacoviello Francesco , Wang Qingyuan
Published: September 2023

The issue focuses on physics-informed machine learning and its applications for structural integrity and safety assessment of engineering systems/facilities. Data science and data mining are fields in fast development with a high potential in several engineering research communities; in particular, advances in machine learning (ML) are undoubtedly enabling significant breakthroughs. However, purely ML models do not necessarily carry physical meaning, nor do they generalize well to scenarios on which they have not been trained on. This is an emerging field of research that potentially will raise a huge impact in the future for designing new materials and structures, and then for their proper final assessment. This issue aims to update the current research state of the art, incorporating physics into ML models, and providing tools when dealing with material science, fatigue and fracture, including new and sophisticated algorithms based on ML techniques to treat data in real-time with high accuracy and productivity.

This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Predictors of futile recanalization in patients with large infarct: a post hoc analysis of the ANGEL-ASPECT trial
Authors: Yi Tingyu , Huo Xiaochuan , Lin Xiao-hui , Wang Mengxing , Wu Yan-Min , Pan Zhi-nan , Zheng Xiu-fen , Lin Ding-lai , Pan Yuesong , Miao Zhongrong , Chen Wen-huo
Published: September 2023

Background

Few studies have focused on factors associated with futile recanalization in acute anterior circulation stroke patients with large infarct cores who were treated with modern endovascular therapy (EVT). The aim of this study was to explore the factors associated with futile recanalization in patients with large ischemic strokes.

Methods

This is a post hoc analysis of the ANGEL-ASPECT trial. Demographic and clinical characteristics, acute stroke workflow interval times, and imaging characteristics were compared between the futile and meaningful recanalization groups. A favorable outcome was defined as a 90-day mRS score 0-3, successful reperfusion was defined as eTICI 2b, 2c and 3 on final angiogram, and futile recanalization was defined as failure to achieve a favorable outcome despite successful reperfusion. Multivariate analysis was performed to identify the predictors of futile recanalization.

Result

One hundred eighty-three patients were included in the final analysis; 91 (49.7%) patients had futile recanalization, and 92 (51.3%) patients had meaningful recanalization. In multivariable logistic regression analysis, older age (age ≥68, OR=3.29, P=0.004), higher NIHSS score (NIHSS ≥ 16, OR=3.33, P=0.003), diabetes (OR=3.23, P=0.017), larger final volume (FIV ≥ 174.7, OR=6.79, P<0.001), postoperative respiratory failure (OR=14.56, P=0.01), and female sex (OR=2.78, P=0.01) were independent predictors of futile recanalization.

Conclusions

Futile recanalization occurred in approximately half of acute stroke patients with a large infarct core following endovascular treatment. Old age, high baseline NIHSS score, diabetes mellitus, large FIV and respiratory failure were independent predictors of futile recanalization after endovascular therapy for large ischemic strokes. Stroke-related pneumonia control may improve prognosis.