bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical exercise and cardiovascular response: design and implementation of a pediatric CMR cohort study
Authors: Bongers-Karmaoui Meddy N. , Hirsch Alexander , Budde Ricardo P. J. , Roest Arno A. W. , Jaddoe Vincent W. V. , Gaillard Romy
Published: October 2023

To examine feasibility and reproducibility and to evaluate the cardiovascular response to an isometric handgrip exercise in low-risk pediatric population using Cardiovascular Magnetic Resonance measurements. In a subgroup of 207 children with a mean age of 16 years participating in a population-based prospective cohort study, children performed an isometric handgrip exercise. During rest and exercise, continuous heart rate and blood pressure were measured. Cardiovascular magnetic resonance (CMR) measurements included left ventricular mass, aortic distensibility and pulse wave velocity at rest and left ventricular end-diastolic and end-systolic volumes, ejection fraction, stroke volume and cardiac output during rest and exercise. 207 children had successful CMR measurements in rest and 184 during exercise. We observed good reproducibility for all cardiac measurements. Heart rate increased with a mean ± standard deviation of 42.6% ± 20.0 and blood pressure with 6.4% ± 7.0, 5.4% ± 6.1 and 11.0% ± 8.3 for systolic, diastolic and mean arterial blood pressure respectively (p-values < 0.05). During exercise, left ventricular end-diastolic and end-systolic volumes and cardiac output increased, whereas left ventricular ejection fraction slightly decreased (p-values < 0.05). Stroke volume did not change significantly. A sustained handgrip exercise of 7 min at 30–40% maximal voluntary contraction is a feasible exercise-test during CMR in a healthy pediatric population, which leads to significant changes in heart rate, blood pressure and functional measurements of the left ventricle in response to exercise. This approach offers great novel opportunities to detect subtle differences in cardiovascular health.
Dissolution of hemp yarns by 1-ethyl-3-methylimidazolium acetate studied with time-temperature superposition
Authors: Alrefaei Nora S. , Hine Peter J. , Ries Michael E.
Published: October 2023

This study investigated the dissolution of hemp yarns in the ionic liquid 1-ethyl-3-methylimidazolium acetate. The yarns were submerged in the ionic liquid at various temperatures and times, then coagulated in water. This resulted in the formation of a composite yarn where two optical microscopy methods were employed to track the growth of the coagulated matrix. In the first, the submerged yarns within water were measured from a side view. In the second, the yarns were dried then analysed by encapsulating in epoxy resin. In both methods, the growth of the swollen ring thickness and the coagulated fraction was tracked as a function of time and temperature. It was found to obey time-temperature superposition, giving a dissolution activation energy of $$78\pm 2 \text{k}\;\text{J}/\text{m}\text{o}\text{l}$$

78
±
2
k

J
/
mol

. In water the yarn is swollen; the swelling ratios of the different regions were calculated to be $$4.4\pm 0.2 \; \text{a}\text{n}\text{d} \; 1.4\pm 0.1$$

4.4
±
0.2

and

1.4
±
0.1

 for the outer dissolved ring and the undissolved core, respectively. A novel finding in this study was that the growth of the coagulated region follows a diffusion process, increasing with the square root of time, and so could be modelled to give a diffusion coefficient for the ionic liquid of $$6.74\times {10}^{-13}\;{\text{ m}}^{2}/{\text{s}}$$

6.74
×

10

-
13

m

2

/
s

. This compared well with previously published NMR data for a saturated cellulose solution (23.5%). This strongly suggests that the diffusion of the ions through a saturated layer of cellulose solution controls the dissolution of the yarn. This finding has significant implications for cellulose-based composite production and thus the recycling of cellulose textiles.
On the Question of the Sign of Size Effects in the Elastic Behavior of Foams
Authors: Kirchhof Stephan , Ams Alfons , Hütter Geralf
Published: October 2023

Due to their good ratio of stiffness and strength to weight, foam materials find use in lightweight engineering. Though, in many applications like structural bending or tension, the scale separation between macroscopic structure and the foam’s mesostructure like cells size, is relatively weak and the mechanical properties of the foam appear to be size dependent. Positive as well as negative size effects have been observed for certain basic tests of foams, i.e., the material appears either to be more compliant or stiffer than would be expected from larger specimens. Performing tests with sufficiently small specimens is challenging as any disturbances from damage of cell walls during sample preparation or from loading devices must be avoided. Correspondingly, the number of respective data in literature is relatively low and the results are partly contradictory.

In order to avoid the problems from sample preparation or bearings, the present study employs virtual tests with CT data of real medium-density ceramic foams. A number of samples of different size is “cut” from the resulting voxel data. Subsequently, the apparent elastic properties of each virtual sample are “measured” directly by a free vibrational analysis using finite cell method, thereby avoiding any disturbances from load application or bearings. The results exhibit a large scatter of the apparent moduli per sample size, but with a clear negative size effect in all investigated basic modes of deformation (bending, torsion, uniaxial). Finally, the results are compared qualitatively and quantitatively to available experimental data from literature, yielding common trends as well as open questions.
Hybrid session-aware recommendation with feature-based models
Authors: Bauer Josef , Jannach Dietmar
Published: October 2023

Session-based recommender systems model the interests of users based on their browsing behavior with the goal of making suitable item suggestions in an ongoing usage session. Most existing work in this growing research area make only use of the most recent observed interactions for each user, and they typically solely rely on user–item interaction data (e.g., click events) for interest modeling. Thus, they do not leverage important forms of other information which are commonly available in practical settings. In this work, we therefore propose a hybrid approach forpersonalizedsession-based (“session-aware”) recommendation, which(i)is able to take into account various types of side information as model features and which(ii)can be combined with existing session-based (or session-aware) recommendation models. Technically, our approach is based on stacking several session-based modeling approaches with efficient machine learning methods for tabular data, in our case using Gradient Boosting Machines (GBMs). We successfully evaluated our approach (namedHySAR) on two public e-commerce datasets. Specifically, we also demonstrate the effectiveness of a number of novel model features that we engineered in the course of this research. These features, which were mostly unexplored in previous works, relate to various types of information related to the users, their actions, the items, as well as contextual session characteristics. Different existing recommendation approaches and further problem specific features can be easily added in our generic method to improve recommendations.
Metabolic and genetic responses to simulated overwintering conditions of alfalfa-rhizobia associations contrasted in their freezing tolerance
Authors: D’Amours Emmanuelle , Bertrand Annick , Cloutier Jean , Claessens Annie , Rocher Solen , Seguin Philippe
Published: October 2023

The study of winter stress tolerance in perennial legumes needs to consider the complete symbiotic system including both plants and bacteria since these two partners are differentially affected by stress conditions. Here, we compared the regrowth after a freezing stress of four different associations of two alfalfa populations differing in freezing tolerance (A-TF0 and A-TF7) inoculated with two Sinorhizobium (Ensifer) meliloti strains (B399 and NRG34) of contrasted adaptation to cold. To understand the contribution of each partner to a better regrowth performance of an association after freezing, we identified molecular traits having major roles in cold acclimation, freezing tolerance, and those involved in the crosstalk between alfalfa and its symbiotic partner. Regrowth after exposure to a freezing stress was 35% larger in the A-TF7 × NRG34 than in the A-TF0 × B399 association. The metabolomic study of roots, crowns and, more specifically, nodules, revealed profound changes in these organs, switching from a sink to support cold acclimation to a source of reserves enabling regrowth after deacclimation. Marked increases in concentrations of stachyose and raffinose, two sugars of the raffinose-family oligosaccharides (RFO), and in the expression level of a gene of the RFO synthetic pathway were observed in response to cold acclimation supporting the importance of a protective role for RFO in alfalfa. Both cold-adapted partners of the symbiotic association contributed to increases in arginine concentration in nodules in response to cold acclimation and deacclimation underscoring the importance of N storage and remobilization for a successful overwintering in alfalfa.
GP120 and tenofovir alafenamide alter cannabinoid receptor 1 expression in hippocampus of mice
Authors: Kulbe Jacqueline Renee , Le Alexandra Anh , Mante Michael , Florio Jazmin , Laird Anna Elizabeth , Swinton Mary K. , Rissman Robert A. , Fields Jerel Adam
Published: October 2023

Central nervous system (CNS) dysfunction remains prevalent in people with HIV (PWH) despite effective antiretroviral therapy (ART). There is evidence that low-level HIV infection and ART drugs may contribute to CNS damage in the brain of PWH with suppressed viral loads. As cannabis is used at a higher rate in PWH compared to the general population, there is interest in understanding how HIV proteins and ART drugs interact with the endocannabinoid system (ECS) and inflammation in the CNS. Therefore, we investigated the effects of the HIV envelope protein gp120 and tenofovir alafenamide (TAF) on cannabinoid receptor 1 (CB1R), glial fibrillary acidic protein (GFAP), and IBA1 in the brain and on locomotor activity in mice. The gp120 transgenic (tg) mouse model was administered TAF daily for 30 days and then analyzed using the open field test before being euthanized, and their brains were analyzed for CB1R, GFAP, and IBA1 expression using immunohistochemical approaches. CB1R expression levels were significantly increased in CA1, CA2/3, and dentate gyrus of gp120tg mice compared to wt littermates; TAF reversed these effects. As expected, TAF showed a medium effect of enhancing GFAP in the frontal cortex of gp120tg mice in the frontal cortex. TAF had minimal effect on IBA1 signal. TAF showed medium to large effects on fine movements, rearing, total activity, total distance, and lateral activity in the open-field test. These findings suggest that TAF may reverse gp120-induced effects on CB1R expression and, unlike tenofovir disoproxil fumarate (TDF), may not affect gliosis in the brain.
Emotion Recognition in Children and Adolescents with ASD and ADHD: a Systematic Review
Authors: Lievore Rachele , Crisci Giulia , Mammarella Irene C.
Published: October 2023

Children and adolescents with autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD) show difficulties in recognizing emotions. Similarities and differences between these two clinical groups’ emotion recognition (ER) have been little explored. This systematic review aims to summarize the results of comparative studies that included samples of cases with ASD and ADHD. A systematic search was conducted following PRISMA guidelines, and 24 papers were included. Behavioral, brain-based, and eye-tracking studies were considered, paying particular attention to the different methods used and to the characteristics of the study groups, such as cognitive factors, age-related differences, and comorbidities. This review provides some insight on the complex process of ER in ASD and ADHD, highlighting important directions for future research.
Machine learning based data collection protocol for intelligent transport systems: a real-time implementation on Dublin M50, Ireland
Authors: Gillani Maryam , Niaz Hafiz Adnan
Published: October 2023

The continuous global urbanization with rapid and dynamic transitioning in traffic situations among highly populated cities results in difficulty for data collection and communication. Data collection for millions of vehicles hinders by various problems, i.e., higher cost of energy, time, space, and storage resources. Moreover, higher data traffic results in higher delays, larger throughput, excessive bottlenecks, and frequent repetition of data. To better facilitate the aforementioned challenges and to provide a solution, we have proposed a lightweight Machine Learning based data collection protocol named ML-TDG to effectively deal with higher data volumes in a real-time traffic environment capable of bringing the least burden on the network while utilizing less space, time, and energy. ML-TDG is functional based on Apache Spark, an effective data processing engine that indexes the data based on two logs, i.e., old commuters or frequent/daily commuters and second new/occasional commuters. The proposed protocol’s main idea is to utilize real-time traffic, distinguish the indexes in parallel based on two assigned logs criteria to train the network, and collect data with the least sources. For energy and time optimization, dynamic segmentation switching is introduced which is an intelligent road segments division and switching for reducing bottlenecks and replication. ML-TDG is tested and verified on Dublin, Ireland’s busiest motorway M50. ML-TDG performs the data collection, data sorting, and network training to decide the next execution altogether for better optimization every time. The experimental results verify that our proposed protocol is attaining higher performance with lower resource requirements along with rich and time-efficient sustainable data collection clusters in comparison with baseline protocols.
Bilateral network with rich semantic extractor for real-time semantic segmentation
Authors: Zhao Shan , Wu Xuan , Tian Kaiwen , Yuan Yang
Published: October 2023

Recently, owing to the requirements of inference speed, most real-time semantic segmentation networks often have shallow network depth, which limits the receptive field size of the model, leading to the limited acquisition of semantic information and resulting in intraclass inconsistency and ultimately a decrease in segmentation accuracy. Additionally, the shallow network depth also restricts the feature extraction capability of the network, reducing its robustness and ability to adapt to complex scenes. To address these issues, a bilateral network with a rich semantic extractor (RSE) for real-time semantic segmentation (BRSeNet) is presented to perform real-time semantic segmentation. First, to solve the problem of insufficient semantic feature information extraction, an RSE is proposed, which includes a multiscale global semantic extraction module (MGSEM) and a semantic fusion module (SFM). The MGSEM can extract rich global semantics and expand the effective receptive field. Simultaneously, the SFM efficiently integrates multiscale local semantics with multiscale global semantics, resulting in more comprehensive semantic information for the network. Finally, based on the characteristics of detail and semantic branches, a bilateral reconstruction aggregation module is designed to reconstruct the contextual information of detail features, model the interdependencies on semantic feature channels, and enhance feature representation. Comprehensive experiments on the challenging Cityscapes and ADE20K datasets are conducted. The experimental results show that the proposed BRSeNet achieves mean intersection over union of 74.9% and 35.7% at inference speeds of 74 and 65 frames per second, respectively, and ensures a favorable balance between segmentation accuracy and inference speed.
“Stay in Your Own Lane” the Inherent Flaws Undermining Children’s Rights Within Australia’s Family Law System: A Perspective from the Field
Authors: Dodds Laura , Creamer Catherine , Powell Zalia , Davis Cindy
Published: October 2023

The social scientists and legal professionals who work in family law in Australia should be recognised for working tirelessly in a complex, overworked, and archaic system. A system that underserves their capacity to maintain integrity, expertise, and ethical diligence in the professions they are assigned. In this perspective piece, we acknowledge the innovative work being done within this system to strive to meet the best interests of the children they serve, whilst highlighting the fundamental flaws of an adversarial system that breeds acculturation across disciplines and disables the practitioners who operate within these systems from legitimately performing their duties and championing the human rights of children.
Perverse sheaves on Riemann surfaces as Milnor sheaves
Authors: Dyckerhoff Tobias , Kapranov Mikhail , Soibelman Yan
Published: October 2023

Constructible sheaves of abelian groups on a stratified space can be equivalently described in terms of representations of the exit-path category. In this work, we provide a similar presentation of the abelian category of perverse sheaves on a stratified surface in terms of representations of the so-called paracyclic category of the surface. The category models a hybrid exit–entrance behaviour with respect to chosen sectors of direction, placing it ‘in between’ exit and entrance path categories. In particular, this perspective yields an intrinsic definition of perverse sheaves as an abelian category without reference to derived categories and t-structures.
High-impact invasive plants expanding into mid-Atlantic states: identifying priority range-shifting species for monitoring in light of climate change
Authors: Salva Justin D. , Bradley Bethany A.
Published: October 2023

One way that climate change is projected to affect invasive plant management is by shifting the ranges of invasive plants. In some regions, hundreds of new, potentially invasive species could establish in coming decades. These species are prime candidates for early detection and rapid response. However, with limited resources, it is unlikely that invasive plant managers will be able to monitor and treat this large number of novel species. Determining which species are likely to have the greatest impacts could inform further risk assessment and mitigate the greatest amount of potential damage. Here, we used the Environmental Impact Classification for Alien Taxa (EICAT) protocol to evaluate the potential impacts of 104 invasive plant species that are projected to establish in Delaware, Kentucky, Maryland, New Jersey, Ohio, Pennsylvania, Virginia, and/or West Virginia by midcentury with climate change. These species were identified using the Invasive Range Expanders Listing Tool to predict which invasive species are likely to shift their ranges into the target states by midcentury. We used Web of Science to search for studies on each species involving impacts to ecological or socioeconomic sectors. We scored ecological impacts on a scale of 1 (“minimal concern”) to 4 (“major concern”) and socioeconomic impacts as present or not present. We evaluated 674 papers and categorized the species into these categories: 32 high-impact species, 20 moderate-impact species, and 13 minor- or minimal-impact species. Two of the 32 high-impact species (panic veldtgrass [Ehrharta erecta Lam.] and Athel tamarisk [Tamarix aphylla (L.) Karst.]) pose a risk to all eight mid-Atlantic states. There were also 46 species that pose a risk to socioeconomic sectors, including agriculture, the economy, and human health. Twenty-four species were listed as data deficient (no data could be found on them). This study provides a comprehensive review of reported impacts of range-shifting invasive plants in the mid-Atlantic.
Curvature effects on the structure of near-wall turbulence
Authors: Selvatici Davide , Quadrio Maurizio , Chiarini Alessandro
Published: October 2023

The interaction between near-wall turbulence and wall curvature is described for the incompressible flow in a plane channel with a small concave–convex–concave bump on the bottom wall, with height comparable to the wall-normal location of the main turbulent structures. The analysis starts from a database generated by a direct numerical simulation and hinges upon the anisotropic generalised Kolmogorov equations, i.e. the exact budget equations for the second-order structure function tensor. The influence of the bump on the wall cycle and on the energy production, redistribution and transfers is described in the physical and scale spaces. Over the upstream side of the bump, the energy drained from the mean flow to sustain the streamwise fluctuations decreases, and the streaks of high and low streamwise velocity weaken and are stretched spanwise. After the bump tip, instead, the production of streamwise fluctuations grows and the streaks intensify, progressively recovering their characteristic spanwise scale. The wall-normal fluctuations, and thus the quasi-streamwise vortices, are sustained by the mean flow over the upstream side of the bump, while energy flows from the vertical fluctuations to the mean field over the downstream side. On the concave portion of the upstream side, the near-wall fluctuations form structures of spanwise velocity which are consistent with Taylor–Görtler vortices at an early stage of development. Their evolution is described by analysing the scale-space pressure–strain term. A schematic description of the bump flow is presented, in which various regions are identified according to the signs of curvature and streamwise pressure gradient.
Perceived vulnerability to infectious disease and perceived harmfulness are as predictive of citizen response to COVID-19 as partisanship
Authors: Cassario Abigail
Published: October 2023

Partisans have biased perceptions of objective conditions. At first glance, the COVID-19 pandemic would appear to be an example of this phenomenon. Noting that most citizens have consistently agreed about the pandemic, I argue that we have overlooked pre-political factors that are as influential as partisanship in shaping citizens’ responses to the pandemic. I identify one such construct in perceived vulnerability to infectious disease (PVD). In one cross-sectional study and one panel study, I find that the influence of PVD on citizens’ perceptions of COVID-19 equals that of partisanship. I also find that PVD can moderate the influence of partisanship on perceptions of harmfulness, nearly erasing the impact of being a Republican on perceiving COVID-19 as a threat. When led by PVD as well as partisanship to accurately perceive harm, citizens, including Republicans, attribute more responsibility to former president Donald Trump for his failed handling of the crisis.
The Long Hand of Anti-Corruption: Israeli Judicial Reform in Comparative Perspective
Authors: Ginsburg Tom
Published: October 2023

There are many ways in which to examine the current Israeli constitutional crisis. This article uses the lens of anti-corruption, a global movement which has changed politics in many countries. The long empowerment of the legal system in Israel arguably has its origins in policing corruption, which may be a particularly powerful motivator for the current governing coalition's efforts to assert more control over the Supreme Court. The dynamics of anti-corruption in Israel are somewhat distinct from those of other countries in ways that may bode well for the Court in its confrontation with the government.
What qualitative research can tell us about food and nutrition security in the UK and why we should pay attention to what it is telling us
Authors: Douglas Flora
Published: October 2023

Poor dietary patterns leading to poorer health and increased health care use have affected people living in disadvantaged economic circumstances in the UK for decades, which many fear will be exacerbated due to the UK's current so-called ‘cost of living crisis’. The voices of experts by experience of those health and social inequalities are not routinely included in health improvement intervention development in relation to obesity prevention policy and programmes. Obesity is highly correlated with food insecurity experience in high-income country contexts (where food insecurity data are routinely collected) and is similarly socially patterned. Using a health equity lens, this review paper highlights qualitative research findings that have revealed the perspectives and direct experiences of people living with food insecurity, or those others supporting food-insecure households, that shed light on the role and influence of the socio-economic contextual factors food-insecure people live with day-to-day. Insights from qualitative research that have focused on the granular detail of day-to-day household resource management can help us understand not only how food insecurity differentially impacts individual household members, but also how behavioural responses/food coping strategies are playing into pathways that lead to avoidable ill health such as obesity, diabetes and other chronic health conditions, including mental health problems. This review paper concludes by discussing research and policy implications in relation to food-insecure households containing people with chronic health conditions, and for pregnant women and families with infants and very young children living in the UK today.
E-government service quality, perceived value, satisfaction, and loyalty: evidence from a newly emerging country
Authors: Pham Long , Limbu Yam B. , Le Mai Thi Thu , Nguyen Ngoc Lan
Published: October 2023

This study examines the relationships between e-government service quality, perceived value, satisfaction, and loyalty toward e-government services. Survey data were collected from 340 randomly selected e-government service users in Vietnam. The results reveal that (1) e-government service quality consists of five dimensions: ease of interaction, fulfillment, citizen care, security and privacy, and trustworthiness; (2) among the five dimensions of e-government service quality, only trustworthiness and fulfillment are significantly related to perceived value; however, trustworthiness has a stronger association with perceived value than does fulfillment; and (3) both perceived value and satisfaction are positively associated with loyalty. The results indicate that the e-government can create value for the citizens by improving service quality, which may help satisfy citizens’ needs and build their loyalty.
Annotation-free learning of a spatio-temporal manifold of the cell life cycle
Authors: delas Peñas Kristofer , Dmitrieva Mariia , Waithe Dominic , Rittscher Jens
Published: October 2023

The cell cycle is a complex biological phenomenon, which plays an important role in many cell biological processes and disease states. Machine learning is emerging to be a pivotal technique for the study of the cell cycle, resulting in a number of available tools and models for the analysis of the cell cycle. Most, however, heavily rely on expert annotations, prior knowledge of mechanisms, and imaging with several fluorescent markers to train their models. Many are also limited to processing only the spatial information in the cell images. In this work, we describe a different approach based on representation learning to construct a manifold of the cell life cycle. We trained our model such that the representations are learned without exhaustive annotations nor assumptions. Moreover, our model uses microscopy images derived from a single fluorescence channel and utilizes both the spatial and temporal information in these images. We show that even with fewer channels and self-supervision, information relevant to cell cycle analysis such as staging and estimation of cycle duration can still be extracted, which demonstrates the potential of our approach to aid future cell cycle studies and in discovery cell biology to probe and understand novel dynamic systems.
Automated Detection and Tracking of Equatorial Plasma Bubbles Utilizing Global‐Scale Observations of the Limb and Disk (GOLD) 135.6 nm Data
Authors: Adkins V. J. , England S. L.
Published: October 2023

Equatorial plasma bubbles (EPBs) are regions of depleted plasma within the ionosphere that form during post‐sunset hours near the magnetic equator. EPBs tend to align with local geomagnetic field lines, extend hundreds of kilometers along geomagnetic longitudes, and thousands of kilometers along geomagnetic latitudes. EPBs can attenuate lower frequency radio waves, such as HF radar. Smaller features, usually 10s of meters, along the EPB's wall can interfere with centimeter scale wavelengths, such as GPS, via Bragg scattering. Statistical analysis of EPBs can further understanding of their occurrence and behavior. The current study utilizes Global‐Scale Observations of the Limb and Disk (GOLD) 135.6 nm nightglow data from 5 October 2018 to 30 September 2022. GOLD has a unique perspective from geostationary orbit, allowing consistent viewing of nightglow and structures over the Americas and Atlantic. An EPB detection method is developed and used to generate a database of occurrences. Occurrences are used to calculate EPB drift speeds and separations. All data is looked at as a whole, including any possible solar or geomagnetic disturbance periods. Seasonality in occurrence rate is evident. Occurrences peak during December solstice and minimize during June solstice for longitudes seen by GOLD. Within GOLD's view, higher occurrences are seen to the west during December solstice and to the east during June solstice. EPB drift speeds and separations show consistent distributions regardless of magnetic latitude region, geographic region, or season. This suggests EPBs behave consistently and regularly once formed, at least on spatial scales observed by GOLD.
Bird Biodiversity Reports Reflect Cities’ Redlined Past
Authors: Cartier Kimberly
Published: October 2023

The lack of bird records in formerly redlined areas creates an inaccurate picture of urban biodiversity, leading to gaps in conservation efforts.
Impact of persistent PSA after salvage radical prostatectomy: a multicenter study
Authors: Preisser Felix , Incesu Reha-Baris , Rajwa Pawel , Chlosta Marcin , Nohe Florian , Ahmed Mohamed , Abreu Andre Luis , Cacciamani Giovanni , Ribeiro Luis , Kretschmer Alexander , Westhofen Thilo , Smith Joseph A. , Steuber Thomas , Calleris Giorgio , Raskin Yannic , Gontero Paolo , Joniau Steven , Sanchez-Salas Rafael , Shariat Shahrokh F. , Gill Inderbir , Karnes R. Jeffrey , Cathcart Paul , Van Der Poel Henk , Marra Giancarlo , Tilki Derya
Published: October 2023

Background and objective

Persistent prostatic specific antigen (PSA) represents a poor prognostic factor for recurrence after radical prostatectomy (RP). However, the impact of persistent PSA on oncologic outcomes in patients undergoing salvage RP is unknown. To investigate the impact of persistent PSA after salvage RP on long-term oncologic outcomes.

Material and methods

Patients who underwent salvage RP for recurrent prostate cancer between 2000 and 2021 were identified from twelve high-volume centers. Only patients with available PSA after salvage RP were included. Kaplan-Meier analyses and multivariable Cox regression models were used to test the effect of persistent PSA on biochemical recurrence (BCR), metastasis and any death after salvage RP. Persistent PSA was defined as a PSA-value ≥ 0.1 ng/ml, at first PSA-measurement after salvage RP.

Results

Overall, 580 patients were identified. Of those, 42% (n = 242) harbored persistent PSA. Median follow-up after salvage RP was 38 months, median time to salvage RP was 64 months and median time to first PSA after salvage RP was 2.2 months. At 84 months after salvage RP, BCR-free, metastasis-free, and overall survival was 6.6 vs. 59%, 71 vs. 88% and 77 vs. 94% for patients with persistent vs. undetectable PSA after salvage RP (all p < 0.01). In multivariable Cox models persistent PSA was an independent predictor for BCR (HR: 5.47, p < 0.001) and death (HR: 3.07, p < 0.01).

Conclusion

Persistent PSA is common after salvage RP and represents an independent predictor for worse oncologic outcomes. Patients undergoing salvage RP should be closely monitored after surgery to identify those with persistent PSA.
Human endogenous retroviruses as epigenetic therapeutic targets in TP53-mutated diffuse large B-cell lymphoma
Authors: Fang Ying , Zhang Mu-Chen , He Yang , Li Chen , Fang Hai , Xu Peng-Peng , Cheng Shu , Zhao Yan , Feng Yan , Liu Qian , Wang Li , Zhao Wei-Li
Published: October 2023

TP53 mutation (TP53mut) occurs in 10–20% of diffuse large B-cell lymphoma (DLBCL) cases and serves as an unfavorable biomarker of DLBCL progression. It confers resistance to immunochemotherapy, high-dose chemotherapy, autologous stem cell transplantation, and anti-CD19 chimeric antigen receptor T-cell therapy. Therapeutic targeting of TP53mut remains a significant challenge in DLBCL treatment. Here we assessed TP53mut in 667 patients with newly diagnosed DLBCL, including 576 patients treated with immunochemotherapy rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and 91 patients with decitabine plus R-CHOP (DR-CHOP, NCT02951728 and NCT04025593). TP53mut independently predicted an inferior prognosis in R-CHOP-treated DLBCL, although this could be mitigated by DR-CHOP treatment. In TP53mut patients, multiple viral regulation pathways were repressed, resulting in the inhibition of immune modulation, as revealed by gene set enrichment analysis. TP53mut DLBCL exhibited increased methyltransferase SUV39H1 expression and H3K9 trimethylation (H3K9me3), contributing to repression of endogenous retroviruses (ERVs) and immunosuppressive tumor microenvironment. In TP53mut DLBCL cell lines, decitabine down-regulated SUV39H1, inhibited H3K9me3 occupancy on ERVs, and triggered ERV expression, thereby unleashing interferons program and CD4+T/CD8+T cell activation. Molecular silencing of SUV39H1 significantly abrogated decitabine-induced H3K9me3 inhibition and ERV expression. In TP53mut patient-derived xenograft models and TP53mut patients, the anti-tumor effect was improved upon the use of combined treatment of decitabine and doxorubicin via SUV39H1-H3K9me3-ERVs axis. Collectively, our findings highlight an ERV regulatory circuitry in TP53mut DLBCL and the crucial roles ERVs for epigenetically reprogramming tumor microenvironment for treating TP53mut-driven cancers.
Consequences of adolescent drug use
Authors: Steinfeld Michael R. , Torregrossa Mary M.
Published: October 2023

Substance use in adolescence is a known risk factor for the development of neuropsychiatric and substance use disorders in adulthood. This is in part due to the fact that critical aspects of brain development occur during adolescence, which can be altered by drug use. Despite concerted efforts to educate youth about the potential negative consequences of substance use, initiation remains common amongst adolescents world-wide. Additionally, though there has been substantial research on the topic, many questions remain about the predictors and the consequences of adolescent drug use. In the following review, we will highlight some of the most recent literature on the neurobiological and behavioral effects of adolescent drug use in rodents, non-human primates, and humans, with a specific focus on alcohol, cannabis, nicotine, and the interactions between these substances. Overall, consumption of these substances during adolescence can produce long-lasting changes across a variety of structures and networks which can have enduring effects on behavior, emotion, and cognition.
α1,3-fucosylation of MEST promotes invasion potential of cytotrophoblast cells by activating translation initiation
Authors: Wang Hao , Cui Xinyuan , Wang Luyao , Fan Ningning , Yu Ming , Qin Huamin , Liu Shuai , Yan Qiu
Published: October 2023

Embryo implantation into the uterus is the gateway for successful pregnancy. Proper migration and invasion of embryonic trophoblast cells are the key for embryo implantation, and dysfunction causes pregnancy failure. Protein glycosylation plays crucial roles in reproduction. However, it remains unclear whether the glycosylation of trophoblasts is involved in trophoblast migration and invasion processes during embryo implantation failure. By Lectin array, we discovered the decreased α1,3-fucosylation, especially difucosylated Lewis Y (LeY) glycan, in the villus tissues of miscarriage patients when compared with normal pregnancy women. Downregulating LeY biosynthesis by silencing the key enzyme fucosyltransferase IV (FUT4) inhibited migration and invasion ability of trophoblast cells. Using proteomics and translatomics, the specific LeY scaffolding glycoprotein of mesoderm-specific transcript (MEST) with glycosylation site at Asn163 was identified, and its expression enhanced migration and invasion ability of trophoblast cells. The results also provided novel evidence showing that decreased LeY modification on MEST hampered the binding of MEST with translation factor eIF4E2, and inhibited implantation-related gene translation initiation, which caused pregnancy failure. The α1,3-fucosylation of MEST by FUT4 may serve as a new biomarker for evaluating the functional state of pregnancy, and a target for infertility treatment.
MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data
Authors: Du Yuxuan , Sun Fengzhu
Published: October 2023

Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.
Distinct and targetable role of calcium-sensing receptor in leukaemia
Authors: Pereira Raquel S. , Kumar Rahul , Cais Alessia , Paulini Lara , Kahler Alisa , Bravo Jimena , Minciacchi Valentina R. , Krack Theresa , Kowarz Eric , Zanetti Costanza , Godavarthy Parimala Sonika , Hoeller Fabian , Llavona Pablo , Stark Tabea , Tascher Georg , Nowak Daniel , Meduri Eshwar , Huntly Brian J. P. , Münch Christian , Pampaloni Francesco , Marschalek Rolf , Krause Daniela S.
Published: October 2023

Haematopoietic stem cells (HSC) reside in the bone marrow microenvironment (BMM), where they respond to extracellular calcium [eCa2+] via the G-protein coupled calcium-sensing receptor (CaSR). Here we show that a calcium gradient exists in this BMM, and that [eCa2+] and response to [eCa2+] differ between leukaemias. CaSR influences the location of MLL-AF9+ acute myeloid leukaemia (AML) cells within this niche and differentially impacts MLL-AF9+ AML versus BCR-ABL1+ leukaemias. Deficiency of CaSR reduces AML leukaemic stem cells (LSC) 6.5-fold. CaSR interacts with filamin A, a crosslinker of actin filaments, affects stemness-associated factors and modulates pERK, β-catenin and c-MYC signaling and intracellular levels of [Ca2+] in MLL-AF9+ AML cells. Combination treatment of cytarabine plus CaSR-inhibition in various models may be superior to cytarabine alone. Our studies suggest CaSR to be a differential and targetable factor in leukaemia progression influencing self-renewal of AML LSC via [eCa2+] cues from the BMM.
Topologically crafted spatiotemporal vortices in acoustics
Authors: Zhang Hongliang , Sun Yeyang , Huang Junyi , Wu Bingjun , Yang Zhaoju , Bliokh Konstantin Y. , Ruan Zhichao
Published: October 2023

Vortices in fluids and gases have piqued the human interest for centuries. Development of classical-wave physics and quantum mechanics highlighted wave vortices characterized by phase singularities and topological charges. In particular, vortex beams have found numerous applications in modern optics and other areas. Recently, optical spatiotemporal vortex states exhibiting the phase singularity both in space and time have been described. Here, we report the topologically robust generation of acoustic spatiotemporal vortex pulses. We utilize an acoustic meta-grating with broken mirror symmetry which exhibits a topological phase transition with a pair of phase singularities with opposite topological charges emerging in the momentum-frequency domain. We show that these vortices are topologically robust against structural perturbations of the meta-grating and can be employed for the generation of spatiotemporal vortex pulses. Our work paves the way for studies and applications of spatiotemporal structured waves in acoustics and other wave systems.
Improving model fairness in image-based computer-aided diagnosis
Authors: Lin Mingquan , Li Tianhao , Yang Yifan , Holste Gregory , Ding Ying , Van Tassel Sarah H. , Kovacs Kyle , Shih George , Wang Zhangyang , Lu Zhiyong , Wang Fei , Peng Yifan
Published: October 2023

Deep learning has become a popular tool for computer-aided diagnosis using medical images, sometimes matching or exceeding the performance of clinicians. However, these models can also reflect and amplify human bias, potentially resulting inaccurate missed diagnoses. Despite this concern, the problem of improving model fairness in medical image classification by deep learning has yet to be fully studied. To address this issue, we propose an algorithm that leverages the marginal pairwise equal opportunity to reduce bias in medical image classification. Our evaluations across four tasks using four independent large-scale cohorts demonstrate that our proposed algorithm not only improves fairness in individual and intersectional subgroups but also maintains overall performance. Specifically, the relative change in pairwise fairness difference between our proposed model and the baseline model was reduced by over 35%, while the relative change in AUC value was typically within 1%. By reducing the bias generated by deep learning models, our proposed approach can potentially alleviate concerns about the fairness and reliability of image-based computer-aided diagnosis.
Dual water-electricity cooperation improves economic benefits and water equality in the Lancang-Mekong River Basin
Authors: Zhang Bingyao , Li Yu , Zhang Chi , Hu Chunhong , Fu Guangtao , Cai Ximing
Published: October 2023

Transboundary river cooperation provides an effective pathway to maintain regional security and sustainable development; however, its implementation is a pressing and prominent concern due to lack of appropriate compensation measures and effective incentive strategies. Here we develop a dual water-electricity cooperation (DWEC) framework that combines water and electricity trading to meet the often-conflicting demands of participating countries. The results from the Lancang-Mekong River Basin reveal that substantial benefits in both economic and social aspects can be achieved through coupling regional water and electricity trades. Economic benefits can be obtained by expanding cooperation space and thereby greatly improving the willingness of countries to participate in basin-wide cooperation. Electricity trading plays a key role in loss compensation for water exporters, ensuring no loss for any party and maximizing basin-wide benefits. Furthermore, the DWEC improves regional water use equality, especially in water shortage periods when there is severe competition among water users. The proposed cooperation framework provides a viable way to implement cooperation in transboundary river basins.
Quantum speed limit for complex dynamics
Authors: Zhang Mao , Yu Huai-Ming , Liu Jing
Published: October 2023

Quantum speed limit focuses on the minimum time scale for a fixed mission and hence is important in quantum information where fast dynamics is usually beneficial. Most existing tools for the depiction of quantum speed limit are the lower-bound-type tools, which are in fact difficult to reveal the true minimum time, especially for many-body systems or complex dynamics. Therefore, the evaluation of this true minimum time in these scenarios is still an unsolved problem. Hereby we provide the operational definition of quantum speed limit for a general target and propose a three-step (classification-regression-calibration) methodology based on machine learning to evaluate the true minimum time in complex dynamics. Moreover, the analytical expression of the true minimum time is also provided for the time-dependent Hamiltonians with time-independent eigenstates.
Understanding and leveraging phenotypic plasticity during metastasis formation
Authors: Shah Saumil , Philipp Lisa-Marie , Giaimo Stefano , Sebens Susanne , Traulsen Arne , Raatz Michael
Published: October 2023

Cancer metastasis is the process of detrimental systemic spread and the primary cause of cancer-related fatalities. Successful metastasis formation requires tumor cells to be proliferative and invasive; however, cells cannot be effective at both tasks simultaneously. Tumor cells compensate for this trade-off by changing their phenotype during metastasis formation through phenotypic plasticity. Given the changing selection pressures and competitive interactions that tumor cells face, it is poorly understood how plasticity shapes the process of metastasis formation. Here, we develop an ecology-inspired mathematical model with phenotypic plasticity and resource competition between phenotypes to address this knowledge gap. We find that phenotypically plastic tumor cell populations attain a stable phenotype equilibrium that maintains tumor cell heterogeneity. Considering treatment types inspired by chemo- and immunotherapy, we highlight that plasticity can protect tumors against interventions. Turning this strength into a weakness, we corroborate current clinical practices to use plasticity as a target for adjuvant therapy. We present a parsimonious view of tumor plasticity-driven metastasis that is quantitative and experimentally testable, and thus potentially improving the mechanistic understanding of metastasis at the cell population level, and its treatment consequences.