bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractCentral 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

AbstractChildren 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

AbstractThe 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

AbstractRecently, 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

AbstractThe 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

Abstract
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

AbstractOne 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.
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

AbstractPartisans 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

AbstractThere 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.
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

AbstractThis 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

AbstractThe 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

AbstractEquatorial 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.
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

Abstract
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

AbstractTP53 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

AbstractSubstance 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.