bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Hitchhiker's guide to RNA–RNA structure and interaction prediction tools
Authors: Tieng Francis Yew Fu , Abdullah-Zawawi Muhammad-Redha , Md Shahri Nur Alyaa Afifah , Mohamed-Hussein Zeti-Azura , Lee Learn-Han , Mutalib Nurul-Syakima Ab 
Published: December 2023

Abstract
RNA biology has risen to prominence after a remarkable discovery of diverse functions of noncoding RNA (ncRNA). Most untranslated transcripts often exert their regulatory functions into RNA–RNA complexes via base pairing with complementary sequences in other RNAs. An interplay between RNAs is essential, as it possesses various functional roles in human cells, including genetic translation, RNA splicing, editing, ribosomal RNA maturation, RNA degradation and the regulation of metabolic pathways/riboswitches. Moreover, the pervasive transcription of the human genome allows for the discovery of novel genomic functions via RNA interactome investigation. The advancement of experimental procedures has resulted in an explosion of documented data, necessitating the development of efficient and precise computational tools and algorithms. This review provides an extensive update on RNA–RNA interaction (RRI) analysis via thermodynamic- and comparative-based RNA secondary structure prediction (RSP) and RNA–RNA interaction prediction (RIP) tools and their general functions. We also highlighted the current knowledge of RRIs and the limitations of RNA interactome mapping via experimental data. Then, the gap between RSP and RIP, the importance of RNA homologues, the relationship between pseudoknots, and RNA folding thermodynamics are discussed. It is hoped that these emerging prediction tools will deepen the understanding of RNA-associated interactions in human diseases and hasten treatment processes.
Accurate TCR-pMHC interaction prediction using a BERT-based transfer learning method
Authors: Zhang Jiawei , Ma Wang , Yao Hui 
Published: December 2023

Abstract
Accurate prediction of TCR-pMHC binding is important for the development of cancer immunotherapies, especially TCR-based agents. Existing algorithms often experience diminished performance when dealing with unseen epitopes, primarily due to the complexity in TCR-pMHC recognition patterns and the scarcity of available data for training. We have developed a novel deep learning model, ‘TCR Antigen Binding Recognition’ based on BERT, named as TABR-BERT. Leveraging BERT's potent representation learning capabilities, TABR-BERT effectively captures essential information regarding TCR-pMHC interactions from TCR sequences, antigen epitope sequences and epitope-MHC binding. By transferring this knowledge to predict TCR-pMHC recognition, TABR-BERT demonstrated better results in benchmark tests than existing methods, particularly for unseen epitopes.
Online Optimization Method of Learning Process for Meta-Learning
Authors: Xu Zhixiong , Zhang Wei , Li Ailin , Zhao Feifei , Jing Yuanyuan , Wan Zheng , Cao Lei , Chen Xiliang 
Published: December 2023

Abstract
Meta-learning is a pivotal and potentially influential machine learning approach to solve challenging problems in reinforcement learning. However, the costly hyper-parameter tuning for training stability of meta-learning is a known shortcoming and currently a hotspot of research. This paper addresses this shortcoming by introducing an online and easily trainable hyper-parameter optimization approach, called Meta Parameters Learning via Meta-Learning (MPML), to combine online hyper-parameter adjustment scheme into meta-learning algorithm, which reduces the need to tune hyper-parameters. Specifically, a basic learning rate for each training task is put forward. Besides, the proposed algorithm dynamically adapts multiple basic learning rate and a shared meta-learning rate through conducting gradient descent alongside the initial optimization steps. In addition, the sensitivity with respect to hyper-parameter choices in the proposed approach are also discussed compared with model-agnostic meta-learning method. The experimental results on reinforcement learning problems demonstrate MPML algorithm is easy to implement and delivers more highly competitive performance than existing meta-learning methods on a diverse set of challenging control tasks.
KVFL: Key-Value-Based Persistent Fuzzing for IoT Web Servers
Authors: Wang Chiheng , Zhao Shibin , Peng Jianshan , Zhu Junhu 
Published: December 2023

Abstract
As the number of Internet of Thing (IoT) devices increases, attacks against their vulnerabilities have become a serious threat. The web servers (WSs) in IoT devices provide management services for end-users, which are currently the major attack surface. Several fuzzing solutions for identifying vulnerabilities in IoT devices have been proposed, but there is currently no grey-box fuzzer specifically designed for the unique features of WSs in IoT to effectively detect memory corruption vulnerabilities. We design and implement KVFL, an efficient grey-box fuzzer, to address the issues of low throughput and slow exploration of deep code when fuzzing for IoT WSs. Firstly, KVFL employs a delicate hooking technology that heuristically hijacks and emulates hardware-dependent functions, ensuring WSs can be accurately and efficiently emulated in user-mode. On this basis, KVFL fully utilizes the loop parsing HTTP requests feature of WSs through a redesigned fork-server, to minimize nonessential rebooting losses of the target, thereby significantly improving fuzzing throughput. Secondly, KVFL leverages code coverage feedback to automatically infer a set of valid Keys and derive a Key-Value mutation. This enables the generation of high-quality test cases that can facilitate deeper code exploration of WSs. The evaluation results show that compared to the state-of-the-art IoT grey-box fuzzer FIRM-AFL, KVFL improves the throughput by over 2× and explores 4.5× more edges. Additionally, it identifies all 1-day vulnerabilities with over 7× faster speed than the baseline and detects three previously unknown 0-day vulnerabilities. These all indicate that KVFL is effective and efficient at fuzzing IoT WSs.
Mortality among people who inject drugs – the interwoven roles of fentanyl and HIV: a community-based cohort study
Authors: Salekešin Maris , Vorobjov Sigrid , Des Jarlais Don , Uusküla Anneli 
Published: December 2023

Abstract

Background
Excess all-cause mortality is a key indicator for assessing direct and indirect consequences of injection drug use and data are warranted to delineate sub-populations within people who inject drugs at higher risk of death. Our aim was to examine mortality and factors associated with mortality among people who inject drugs in Estonia.

Methods
Retrospective cohort study using data from people who inject drugs recruited in the community with linkage to death records. Standardized mortality ratios were used to compare the cohort mortality to the general population and potential predictors of death were examined through survival analysis (Cox regression). The cohort include a total of 1399 people who inject drugs recruited for cross-sectional surveys using respondent driven sampling between 2013 and 2018 in Estonia. A cohort with follow-up through 2019 was formed with linkage to national causes of death registry.

Results
Among 1399 participants with 4684 person-years of follow-up, 10% were deceased by 2019. The all-cause mortality rate in the cohort was 28.9 per 1000 person-years (95% confidence interval 25.3–35.3). Being HIV positive, injecting mainly opioids (fentanyl), living in the capital region and the main source of income other than work were associated with greater mortality risk.

Conclusions
While low-threshold services have been available for a long time for people who inject drugs, there is still a need to widen the availability and integration of services, particularly the integration of HIV and opioid treatment.
How does lowering psychosocial risks influence sickness absence? A prospective cohort study analyzed as a quasi-experiment
Authors: Shiri Rahman , Mattila-Holappa Pauliina , Kauppi Maarit , Aalto Ville , Oksanen Tuula , Ervasti Jenni 
Published: December 2023

Abstract

Background
We examined how reducing work-related psychosocial stressors affected long-term sickness absence of younger and older employees.

Methods
We used data from 43 843 public sector employees in Finland who participated in surveys in 2018 and 2020. We assessed psychosocial factors, such as job demands, job control, work effort, job rewards and worktime control. We obtained sickness absence data from registers for spells longer than 10 consecutive working days. We applied age-specific propensity score weighting and generalized linear models to estimate the effects of changes in psychosocial factors between 2018 and 2020 on sickness absence in 2020.

Results
Among employees under 50 years, increasing job rewards by 1 SD reduced the risk of sickness absence by 17% [risk ratio (RR) 0.83, 95% CI 0.72–0.96]. Among employees aged 50 years or older, decreasing job demands by 1 SD reduced the risk of sickness absence by 13% (RR 0.87, 95% CI 0.78–0.98), and increasing job control by 1 SD reduced the risk by 12% (RR 0.88, 95% CI 0.76–1.01). Changes in efforts and worktime control had no significant associations with sickness absence.

Conclusions
Reducing psychosocial stressors can lower the occurrence of long-term sickness absence, but the associations differ by age group. Younger workers benefit more from enhancing job rewards, while older workers benefit more from lowering job demands and increasing job control. To establish the causal impact of psychosocial risk reduction on sickness absence across age groups, future research should employ randomized controlled trials as the methodological approach.
Consider the time dimension: theorizing and formalizing sequential media selection
Authors: Gong Xuanjun , Huskey Richard 
Published: December 2023

AbstractExisting media-selection theories predominantly consider media selection at a static moment-in-time. However, such theorizing is out-of-step with today’s media landscape, which is dominated by sequential media consumption where future media selection is dependent on previously selected media. Ignoring the dependencies among sequential media selection leads to a failure to theorize and model the time-evolving nature of media selection. To bridge this gap, we review computational modeling methods and offer an integrative theoretical framework for studying sequential media selection. In doing so, we lay the theoretical and methodological foundation necessary for state-of-the-art research focused on understanding the underlying mechanisms of, and sequential dependencies among, media selection. Our sequential media-selection framework helps media researchers by theorizing and formalizing processes related to learning, exploration vs. exploitation, and foraging. The outcome is a manuscript that builds on existing theory and research to offer a roadmap for next-generation media-selection inquiry.
The Impacts of the COVID-19 Pandemic on Receipt of Needed Medical Care and At-Home Support among U.S. Households Receiving Supplemental Security Income and Social Security Disability Insurance on the Basis of Disability
Authors: McLean Kiley J , Muentner Luke , Bishop Lauren 
Published: December 2023

Abstract
More than 8.1 million Americans with disabilities qualify for Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI). Individuals with disabilities were particularly vulnerable to COVID-19, which may have altered individual and household behavior. Research on the impact of COVID-19 on individuals with disabilities and their families remains limited. Authors analyzed 2020 National Health Interview Survey data. Logistic regression models were applied, controlling for the effects of age, race, sex, income, education, employment, and health status. Households with SSI/SSDI beneficiaries with disabilities were associated with significantly greater odds of delaying or forgoing medical care and receiving needed personal and household care at home due to COVID-19 compared with households without beneficiaries. The health and well-being of households with individuals with disabilities may require more robust and inclusive social work initiatives that aim to reduce adverse pandemic impacts.
Forensic analysis of mosquito blood meal digestion process and the impact of heroin opiate: determination of the post-feeding interval as a PMI estimation
Authors: Alharbi Hend M , Elnakady Yasser A , Aldahmash Badr A , Alajmi Reem , ALOthman Zeid A , Badjah-Hadj-Ahmed Ahmed-Yacine , Aqel Ahmad , Ahmed Ashraf M 
Published: December 2023

Abstract
Females of some mosquito species are anthropophilic, as they feed on human blood to support egg production and, hence, are forensically valuable if found at a crime scene. The present study investigated the blood meal digestion process in Culex pipiens L. both with and without heroin and proposed a method for estimating the post-feeding interval (PFI). Mosquitoes were fed on a control mouse, a heroin-injected mouse, or in vitro heroin-treated mouse blood. The blood meal digestion was then investigated at different hours post-feeding. Data showed that the blood meal size ingested by control mosquitoes was 0.681 ± 0.04 mg/mosquito and was completely digested within 45 h post-feeding. An estimation of the PFI was proposed in terms of the rate of hemoglobin (Hb) digestion. The blood meal size of the mosquitoes fed on the in vitro heroin-treated blood and the heroin-injected mouse was 0.96 ± 0.06 and 0.79 ± 0.01 mg/mosquito and was completely digested within 50 and 55 h post-feeding, respectively. The digestion of Hb started similarly in all experimental mosquitoes until 10 h post-feeding, after which it significantly decreased in heroin-treated blood meals compared with the control ones. This may suggest that heroin impacted the digestion process, as it took an extra 5–10 h to complete. These findings could be valuable in the forensic context since an estimation of PFI is proposed as a potential estimation of the postmortem interval (PMI). However, care should be taken as heroin in the host blood has significantly impacted the overall digestion process and, hence, may bias the PFI/PMI estimation.
Black frontline workers navigating everyday workplace tensions through professionalism
Authors: Nyawaga Christine , Mitra Rahul 
Published: December 2023

Abstract
Professionalism has been widely criticized for its biased standards modeled around dominant identities while excluding minoritized groups. Nevertheless, it remains a powerful social discourse, adopted widely by workers and organizations, and frontline workers—who became particularly salient during the COVID-19 pandemic—are no different, even as they are mainly Black and Brown. Our exploratory study, based on in-depth interviews with 15 Black frontline workers, examines how they use discourses of professionalism to navigate everyday tensions stemming from both their minoritized racial identity and the precarious nature of frontline work. Participants described three intersecting communicative practices—bottling their emotions, striving for (elusive) excellence, and navigating (in)visibility. Our research thus addresses the communicative practice of professionalism among an important yet undeserved category of workers, showing how it is both hegemonic and exclusionary, but may nevertheless be subverted strategically by precarious workers.
Black hole growths in gamma-ray bursts driven by the Blandford–Znajek mechanism
Authors: Li Xiao-Yan , Liu Tong 
Published: December 2023

ABSTRACT
The Blandford–Znajek (BZ) mechanism in stellar-mass black hole (BH) hyperaccretion systems is generally considered to power gamma-ray bursts (GRBs). Based on observational GRB data, we use the BZ mechanism driven by the BH hyperaccretion disc to investigate the evolution of the BH mass and spin after the jets break out from the progenitors. We find that the BH growths are almost independent of initial BH masses. Meanwhile, the BH growths will be more efficient with smaller initial spin parameters. We conclude that (i) the BZ mechanism is efficient for triggering BH growths for only 1 of 206 typical long-duration GRBs; (ii) the mean BH mass growths of ultra-long GRBs are marginal for all 7 samples collected; (iii) for the short-duration GRBs, the results that BHs show minimal growths is consistent with the mass supply limitation in the scenario of compact object mergers.
Model-independent confirmation of a constant speed of light over cosmological distances
Authors: Melia Fulvio 
Published: December 2023

ABSTRACT
Recent attempts at measuring the variation of c using an assortment of standard candles and the redshift-dependent Hubble expansion rate inferred from the currently available catalogue of cosmic chronometers have tended to show that the speed of light appears to be constant, at least up to z ∼ 2. A notable exception is the use of high-redshift ultraviolet + X-ray quasars, whose Hubble diagram seems to indicate an ∼2.7σ deviation of c from its value c0 (≡ 2.99792458 × 1010 cm s−1) on Earth. We show in this paper, however, that this anomaly is due to an error in the derived relation between the luminosity distance, DL, and H(z) when c is allowed to vary with redshift, and an imprecise calibration of the quasar catalogue. When these deficiencies are addressed correctly, one finds that c/c0 = 0.95 ± 0.14 in the redshift range 0 ≲ z ≲ 2, fully consistent with zero variation within the measurement errors.
Cell–cell communication in kidney fibrosis
Authors: He Meizhi , Liu Zhao , Li Li , Liu Youhua 
Published: December 2023

ABSTRACT
Kidney fibrosis is a common outcome of a wide variety of chronic kidney diseases, in which virtually all kinds of renal resident and infiltrating cells are involved. As such, well-orchestrated intercellular communication is of vital importance in coordinating complex actions during renal fibrogenesis. Cell–cell communication in multicellular organisms is traditionally assumed to be mediated by direct cell contact or soluble factors, including growth factors, cytokines and chemokines, through autocrine, paracrine, endocrine and juxtacrine signaling mechanisms. Growing evidence also demonstrates that extracellular vesicles, lipid bilayer–encircled particles naturally released from almost all types of cells, can act as a vehicle to transfer a diverse array of biomolecules including proteins, mRNA, miRNA and lipids to mediate cell–cell communication. We recently described a new mode of intercellular communication via building a special extracellular niche by insoluble matricellular proteins. Kidney cells, upon injury, produce and secrete different matricellular proteins, which incorporate into the local extracellular matrix network, and regulate the behavior, trajectory and fate of neighboring cells in a spatially confined fashion. This extracellular niche–mediated cell–cell communication is unique in that it restrains the crosstalk between cells within a particular locality. Detailed delineation of this unique manner of intercellular communication will help to elucidate the mechanism of kidney fibrosis and could offer novel insights in developing therapeutic intervention.
Occupational asthma, rhinitis and contact urticaria from greenhouse work
Authors: Lindström I , Hölttä P , Airaksinen L , Suuronen K , Suomela S , Suojalehto H 
Published: December 2023

Abstract

Background
The current knowledge about occupational allergic diseases among greenhouse workers is scant.

Aims
To describe greenhouse workers’ occupational allergic diseases.

Methods
We identified 28 greenhouse workers with occupational allergic diseases in 2002–2020 by conducting a systematic search in the patient register of the Finnish Institute of Occupational Health. All the patients worked in tomato- or cucumber-growing greenhouses and showed immunoglobulin-E-mediated sensitization to occupational agents. Specific inhalation challenges or workplace peak expiratory flow monitoring confirmed occupational asthma (OA), nasal allergen challenges confirmed occupational rhinitis (OR) and open skin tests confirmed occupational contact urticaria (OCU).

Results
Most patients had more than one occupational disease and were sensitized to several workplace agents. Tomato plants were the most common cause of occupational diseases and induced 22 allergic diseases in 14 patients. Cucumber plants caused occupational diseases in 10 patients (3 OA, 7 OR and 6 OCU). The pest control mite Amblyseius swirskii and a mixture of parasitic wasps Encarsia formosa and Eretmocerus eremicus both induced two OA cases. Three patients had an occupational disease caused by storage mites and three others had a work-related systemic reaction to a bumblebee sting.

Conclusions
The greenhouse workers typically suffered from several occupational allergic diseases and were sensitized to cultivated plants, various pest control organisms and storage mites. All these can cause OA and OR, but in this study, OCU was only induced by cultivation plants. Cucumber plant is a novel cause of OA and OR, and A. swirskii is a novel cause of OA.
Effectiveness of Sotrovimab in Preventing COVID-19-Related Hospitalizations or Deaths Among US Veterans During Omicron BA.1
Authors: Young-Xu Yinong , Korves Caroline , Zwain Gabrielle , Satram Sacha , Drysdale Myriam , Reyes Carolina , Cheng Mindy M , Bonomo Robert A , Epstein Lauren , Marconi Vincent C , Ginde Adit A 
Published: December 2023

Abstract

Background
The real-world clinical effectiveness of sotrovimab in preventing coronavirus disease 2019 (COVID-19)–related hospitalization or mortality among high-risk patients diagnosed with COVID-19, particularly after the emergence of the Omicron variant, needs further research.

Method
Using data from the US Department of Veterans Affairs (VA) health care system, we adopted a target trial emulation design in our study. Veterans aged ≥18 years, diagnosed with COVID-19 between December 1, 2021, and April 4, 2022, were included. Patients treated with sotrovimab (n = 2816) as part of routine clinical care were compared with all eligible but untreated patients (n = 11,250). Cox proportional hazards modeling estimated the hazard ratios (HRs) and 95% CIs for the association between receipt of sotrovimab and outcomes.

Results
Most (90%) sotrovimab recipients were ≥50 years old, and 64% had ≥2 mRNA vaccine doses or ≥1 dose of Ad26.COV2. During the period that BA.1 was dominant, compared with patients not treated, sotrovimab-treated patients had a 70% lower risk of hospitalization or mortality within 30 days (HR, 0.30; 95% CI, 0.23–0.40). During BA.2 dominance, sotrovimab-treated patients had a 71% (HR, 0.29; 95% CI, 0.08–0.98) lower risk of 30-day COVID-19-related hospitalization, emergency room visits, or urgent care visits (defined as severe COVID-19) compared with patients not treated.

Conclusions
Using national real-world data from high-risk and predominantly vaccinated veterans, administration of sotrovimab, compared with contemporary standard treatment regimens, was associated with reduced risk of 30-day COVID-19-related hospitalization or all-cause mortality during the Omicron BA.1 period.
Serious Adverse Events and Laboratory Monitoring Regimens for Outpatient Parenteral Antimicrobial Therapy With Cefazolin and Ceftriaxone
Authors: Sunagawa Shawnalyn W , Arduser Sarah , Miller Molly M , Lyden Elizabeth , LeMaster Melissa , Cortes-Penfield Nicolas , Hankins Richard J , Bergman Scott J , Alexander Bryan T 
Published: December 2023

Abstract
The optimal laboratory monitoring frequency for outpatient parenteral antimicrobial therapy–related adverse events (OPAT-AEs) during cefazolin and ceftriaxone therapy is not well defined. We identified 2.7 OPAT-AEs per 1000 sets of weekly laboratory tests in this population, suggesting that less intensive laboratory monitoring may be safe and reasonable.