bluuebunny/crossref_metadata_2025_split huggingface dataset:
Capsaicin enhances cisplatin-induced anti-metastasis of nasopharyngeal carcinoma by inhibiting EMT and ERK signaling via serpin family B member 2
Authors: Xu Yafei , Kong Weimiao , Zhao Simin , Xiong Dan , Wang Yejun 
Published: May 2024

Abstract
Cisplatin (DDP)-based combined chemotherapy or concurrent chemoradiotherapy is the mainstay treatment for advanced-stage nasopharyngeal carcinoma (NPC), but needs improvement due to its severe side effects. Capsaicin (CAP) can enhance the anti-tumor activity of cytotoxic drugs. The aim of this study was to investigate the anti-metastasis activity of CAP in combination with DDP in NPC. Herein, CAP and DDP showed synergistic cytotoxic effects on NPC cells. CAP alone and DDP alone inhibited NPC migration and invasion in vitro and in vivo, and the combination of CAP and DDP had the greatest effect. Moreover, CAP upregulated the mRNA and protein expressions of serpin family B member 2 (SERPINB2). Further results showed that both SERPINB2 mRNA and protein expressions were downregulated in NPC cell lines and tissues and SERPINB2 overexpression inhibited NPC migration and invasion in vitro and in vivo, while silencing SERPINB2 acted oppositely. In addition, SERPINB2 was abnormally expressed in head and neck squamous cell carcinoma and other multiple cancers, and downregulation of SERPINB2 predicted poor prognosis in head and neck squamous cell carcinoma according to the Cancer Genome Atlas database. We further found that SERPINB2 overexpression inhibited epithelial–mesenchymal transition (EMT) and the phosphorylated extracellular signal-regulated kinase (p-ERK), and the inhibitory effect was enhanced by CAP and DDP. Altogether, our results suggest that the combined inhibition of CAP and DDP on NPC metastasis may be related to the inhibition of epithelial–mesenchymal transition and ERK signals mediated by SERPINB2, and CAP may help to improve the efficacy of DDP in the treatment of NPC and develop new therapeutic approaches.
Rapid and Sensitive Detection of Fentanyl and Its Analogs by a Novel Chemiluminescence Immunoassay
Authors: Zhao Jiang-yang , Uddin Mezbah , Unsihuay Daisy , Butler William , Xia Terrance W , Xu Jayson Z , Wang Simon , Sheng Xiaolin , Jannetto Paul J , Wang Ping , Xia Xiaofeng 
Published: May 2024

Abstract

Background
Abuse of fentanyl and its analogs is a major contributor to the opioid overdose epidemic in the United States, but detecting and quantifying trace amounts of such drugs remains a challenge without resorting to sophisticated mass spectrometry-based methods.

Methods
A sensitive immunoassay with a sub-picogram limit of detection for fentanyl and a wide range of fentanyl analogs has been developed, using a novel high-affinity antibody fused with NanoLuc, a small-size luciferase that can emit strong and stable luminescence. When used with human urine samples, the assay has a sub-picogram limit of detection for fentanyl, with results fully concordant with LC-MS.

Results
When applied to clinical samples, the novel chemiluminescence immunoassay can detect low positive fentanyl missed by routine screening immunoassays, with a limit of detection of 0.8 pg/mL in human urine. When applied to environmental samples, the assay can detect levels as low as 0.25 pg fentanyl per inch2 of environment surface. Assay turnaround time is less than 1 h, with inexpensive equipment and the potential for high-throughput automation or in-field screening.

Conclusions
We have established a novel assay that may have broad applications in clinical, environmental, occupational, and forensic scenarios for detection of trace amounts of fentanyl and its analogs.
Incidence and factors associated with PrEP discontinuation in France
Authors: Garofoli Nina , Siguier Martin , Robineau Olivier , Valette Michel , Phung Bao , Bachelard Antoine , Rioux Christophe , Le Gac Sylvie , Digumber Marc , Pialoux Gilles , Ghosn Jade , Champenois Karen 
Published: May 2024

Abstract

Objectives
HIV pre-exposure prophylaxis (PrEP) is effective in preventing HIV, but some seroconversions occur due to poor adherence or PrEP discontinuation. Our objective was to estimate the incidence of PrEP discontinuation and describe the reasons and factors associated with discontinuations.

Methods
A retrospective cohort was conducted in three French hospitals between January 2016 and June 2022. PrEP users who attended at least twice within 6 months during study period were included and followed up until December 2022. The incidence rate of PrEP discontinuation was estimated by censoring lost to follow up individuals. Factors associated with PrEP discontinuations were identified using a multivariate Cox model.

Results
A total of 2785 PrEP users were included, with 94% men and 5% transgender people. Median age was 35 years. By December 2022, 653 users had stopped PrEP (24%). The incidence rate was 10.8 PrEP discontinuations for 100 person-years (PY). The main causes of discontinuation were being in a stable relationship (32%), and not judging the treatment useful anymore (12%). Individuals who discontinued PrEP were younger [&lt;29, HR = 1.45 (1.17–1.80)], and more likely to be women [HR = 2.44 (1.50–3.96)] or sex workers [HR = 1.53 (0.96–2.44)]. They were more likely to report PrEP side effects [HR = 2.25 (1.83–2.77)] or ≥2 sexually transmitted infections [HR = 1.87 (1.53–2.27)] during the last year.

Conclusion
The incidence of PrEP discontinuations was quite low compared to rates observed in other cohorts. Users who stopped PrEP were sometimes still exposed to HIV, emphasizing the need for targeted interventions to prepare and support PrEP discontinuations and limit seroconversion risk.
Knowledge, awareness and practices of healthcare workers regarding antimicrobial use, resistance and stewardship in Zambia: a multi-facility cross-sectional study
Authors: Mudenda Steward , Chabalenge Billy , Daka Victor , Jere Elimas , Sefah Israel Abebrese , Wesangula Evelyn , Yamba Kaunda , Nyamupachitu Julian , Mugenyi Nathan , Mustafa Zia Ul , Mpundu Mirfin , Chizimu Joseph , Chilengi Roma 
Published: May 2024

Abstract

Background
Antimicrobial resistance (AMR) poses a threat to public health globally. Despite its consequences, there is little information about the knowledge, awareness, and practices towards AMR among healthcare workers (HCWs). Therefore, this study assessed the knowledge, awareness and practices regarding antimicrobial use (AMU), AMR and antimicrobial stewardship (AMS) among HCWs who are involved in the implementation of AMS activities across eight hospitals in Zambia.

Methods
A cross-sectional study was conducted among 64 HCWs from October to December 2023 using a semi-structured questionnaire. Data were analysed using IBM SPSS version 25.0.

Results
Of the 64 HCWs, 59.4% were females, 60.9% were aged between 25 and 34 years, 37.5% were nurses, 18.7% were pharmacists, 17.2% were medical doctors and only one was a microbiologist. Overall, 75% of the HCWs had good knowledge, 84% were highly aware and 84% had good practices regarding AMU, AMR and AMS. Most of the HCWs (90.6%) responded that they had a multidisciplinary AMS team at their hospitals and were implementing the use of the WHO AWaRe classification of antibiotics.

Conclusion
This study found good knowledge levels, high awareness and good practices regarding AMU, AMR and AMS among HCWs who were involved in the implementation of AMS activities in hospitals in Zambia. Additionally, most hospitals have been conducting AMS training and implementing the use of the WHO AWaRe classification of antibiotics. However, there is still a need to address some identified gaps in AMU and AMR through the strengthening of AMS activities in hospitals.
Model checking distributed temporal logic
Authors: Dionísio Francisco , Ramos Jaime , Subtil Fernando , Viganò Luca 
Published: May 2024

Abstract
The distributed temporal logic (DTL) is a logic for reasoning about temporal properties of distributed systems from the local point of view of the system’s agents, which are assumed to execute sequentially and to interact by means of synchronous event sharing. Different versions of DTL have been provided over the years for a number of different applications, reflecting different perspectives on how non-local information can be accessed by each agent. In this paper, we propose an automata-theoretic model checking algorithm for DTL. To this end, we propose a notion of distributed transition system that will be used to specify the system to be verified. The properties that the system should meet are specified in DTL. In order to capture the models of these properties, we propose the notions of generalized distributed Büchi automaton and of distributed Büchi automaton. With these concepts, we are able to adapt results from automata-theoretic approaches to model checking in LTL to the distributed case.
Establishment of artificial intelligence model for precise histological subtyping of lung adenocarcinoma and its application to quantitative and spatial analysis
Authors: Miura Eisuke , Emoto Katsura , Abe Tokiya , Hashiguchi Akinori , Hishida Tomoyuki , Asakura Keisuke , Sakamoto Michiie 
Published: May 2024

Abstract

Background
The histological subtype of lung adenocarcinoma is a major prognostic factor. We developed a new artificial intelligence model to classify lung adenocarcinoma images into seven histological subtypes and adopted the model for whole-slide images to investigate the relationship between the distribution of histological subtypes and clinicopathological factors.

Methods
Using histological subtype images, which are typical for pathologists, we trained and validated an artificial intelligence model. Then, the model was applied to whole-slide images of resected lung adenocarcinoma specimens from 147 cases.

Result
The model achieved an accuracy of 99.7% in training sets and 90.4% in validation sets consisting of typical tiles of histological subtyping for pathologists. When the model was applied to whole-slide images, the predominant subtype according to the artificial intelligence model classification matched that determined by pathologists in 75.5% of cases. The predominant subtype and tumor grade (using the WHO fourth and fifth classifications) determined by the artificial intelligence model resulted in similar recurrence-free survival curves to those determined by pathologists. Furthermore, we stratified the recurrence-free survival curves for patients with different proportions of high-grade components (solid, micropapillary and cribriform) according to the physical distribution of the high-grade component. The results suggested that tumors with centrally located high-grade components had a higher malignant potential (P &lt; 0.001 for 5–20% high-grade component).

Conclusion
The new artificial intelligence model for histological subtyping of lung adenocarcinoma achieved high accuracy, and subtype quantification and subtype distribution analyses could be achieved. Artificial intelligence model therefore has potential for clinical application for both quantification and spatial analysis.
Unraveling immune heterogeneity across pan-cancer and deep insights in lung adenocarcinoma based on alternative splicing
Authors: Wang Yuquan , Guo Erliang , Zou Min , Lv Chen , Cui Yanrui , Zhai Songmei , Sang Shaocong , Xiong Kai , Yang Xiuqi , Zhuang Shuping , Gu Yunyan , Liang Haihai 
Published: May 2024

Abstract
Alternative splicing (AS) participates in tumor development and tumor microenvironment formation. However, the landscape of immune-infiltrating AS events in pan-cancer and mechanisms of AS in lung adenocarcinoma (LUAD) have not been comprehensively characterized. We systematically profiled the immune-infiltrating AS event landscape of pan-cancer using data from The Cancer Genome Atlas, analyzing both commonalities and specific characteristics among different cancer types. We found that AS events tend to occur specifically in one cancer type rather than in multiple cancer types. AS events were used to classify 512 LUAD samples into 2 subtypes by unsupervised clustering: the aberrant splicing subtype and the immune-infiltrating subtype. The 2 subtypes showed significant differences in clinicopathology, prognosis, transcriptomics, genomics, and immune microenvironment. We constructed a classification signature comprising 10 genes involved in 14 AS events using logistic regression. The robustness of the signature was validated in 3 independent datasets using survival analysis. To explore AS mechanisms in LUAD, we constructed subtype-specific coexpression networks using Pearson correlation analysis. AS event of AKT3 regulated by splicing factor ENOX1 was associated with poor prognosis in LUAD. Overall, we outline AS events associated with immune infiltration in pan-cancer, and this study provides insights into AS mechanisms in LUAD patient classification.
Machine Learning-Enabled Image Classification for Automated Electron Microscopy
Authors: Day Alexandra L , Wahl Carolin B , Gupta Vishu , dos Reis Roberto , Liao Wei-keng , Mirkin Chad A , Dravid Vinayak P , Choudhary Alok , Agrawal Ankit 
Published: May 2024

Abstract
Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of “big data” and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.
A closer look at the host-galaxy environment of high-velocity Type Ia supernovae
Authors: Lin Han-Tang , Pan Yen-Chen , Abdurro’uf  
Published: May 2024

ABSTRACT
Recent studies suggested that the ejecta velocity of Type Ia supernova (SN Ia) is a promising indicator in distinguishing the progenitor systems and explosion mechanisms. By classifying the SNe Ia based on their ejecta velocities, studies found that SNe Ia with high $\mathrm{Si}\, {\rm{\small II}}\, \lambda 6355$ velocities (HV SNe Ia; $v \gtrsim 12\,000$ km s−1) tend to be physically different from their normal-velocity counterparts (NV SNe Ia). In this work, we revisit the low-z sample studied in previous work and closely look into the spatially resolved environment local to the site of SN explosion. Our results reveal a possible trend (at 2.4σ significance) that HV SNe Ia are likely associated with older stellar populations than NV SNe Ia. While the trend is inconclusive, the local host-galaxy sample studied in this work is likely skewed towards massive galaxies, limiting the parameter space that we would like to investigate from the original parent sample. Nevertheless, our results do not rule out the possibility that parameters other than the host-galaxy age (such as metallicity) could be the underlying factors driving the differences between HV and NV SNe Ia due to the limitation of our data set.
A survey for radio emission from white dwarfs in the VLA Sky Survey
Authors: Pelisoli Ingrid , Chomiuk Laura , Strader Jay , Marsh T R , Aydi Elias , Dage Kristen C , Kyer Rebecca , Molina Isabella , Panurach Teresa , Urquhart Ryan , Maccarone Thomas J , Rich R Michael , Rodriguez Antonio C , Breedt E , Brown A J , Dhillon V S , Dyer M J , Gaensicke Boris T , Garbutt J A , Green M J , Kennedy M R , Kerry P , Littlefair S P , Munday James , Parsons S G 
Published: May 2024

ABSTRACT
Radio emission has been detected from tens of white dwarfs, in particular in accreting systems. Additionally, radio emission has been predicted as a possible outcome of a planetary system around a white dwarf. We searched for 3 GHz radio continuum emission in 846 000 candidate white dwarfs previously identified in Gaia using the Very Large Array Sky Survey (VLASS) Epoch 1 Quick Look Catalogue. We identified 13 candidate white dwarfs with a counterpart in VLASS within 2 arcsec. Five of those were found not to be white dwarfs in follow-up or archival spectroscopy, whereas seven others were found to be chance alignments with a background source in higher resolution optical or radio images. The remaining source, WDJ204259.71+152108.06, is found to be a white dwarf and M-dwarf binary with an orbital period of 4.1 d and long-term stochastic optical variability, as well as luminous radio and X-ray emission. For this binary, we find no direct evidence of a background contaminant, and a chance alignment probability of only ≈2 per cent. However, other evidence points to the possibility of an unfortunate chance alignment with a background radio and X-ray emitting quasar, including an unusually poor Gaia DR3 astrometric solution for this source. With at most one possible radio emitting white dwarf found, we conclude that strong (≳1–3 mJy) radio emission from white dwarfs in the 3 GHz band is virtually non-existent outside of interacting binaries.
Towards automatic detection and classification of swimming pectinids behaviour: first developments on great scallops (Pecten maximus)
Authors: Chauvaud Arthur , Reynaud Sarah , Mars Jérôme , Retailleau Elie , Chauvaud Laurent , Jolivet Aurélie , Mathias Delphine , Chauvaud Sylvain 
Published: May 2024

ABSTRACT
Over the past decades, valvometric techniques have been commonly used to record valve opening activities of bivalves. Various relationships with environmental variations have been elucidated through different types of metrics extracted from valvometric signals (e.g. valve opening, cyclicity, specific behaviours). Although automated data processing methods exist, many specific behaviours are still annotated manually. This study proposes an algorithm to detect and classify the behaviours performed by the great scallop (Pecten maximus) in two categories: jump-like (JL) behaviours and other behaviours (OBs). These two categories differ in the shape of their valvometric signal, JL being movements of high amplitudes associated with ‘displacement movements’ (rotation, swimming, jumping, flipping) and OB grouping all other movements of lower amplitudes (‘common movements’), such as partial closures, which are produced routinely. This algorithm has been developed and tested on 10 scallop valve opening time series recorded using fully autonomous valvometers based on the Hall effect principle. The algorithm detected 93.65% ± 5.5 of manually annotated behaviours produced by scallops, with a false detection rate of less than 6.3% ± 5.5. Classification performances vary according to the type of behaviour. JL behaviours and OBs were well classified at 83.72% ± 23.09 and 98.92% ± 1.80, respectively. Analysis of the algorithm's outputs, highlighting potential daily trends in the production of certain behaviours, shows their relevance for acquiring information on the biology of scallops. By providing an efficient and flexible detection and classification method, this study is a first step towards the automation of bivalve behaviour detection. This study also highlights the importance of simultaneously using Hall sensors and accelerometers to accurately classify the complex behaviours of mobile bivalves such as P. maximus.
Mediterranean Diet and Mental Health in Children and Adolescents: A Systematic Review
Authors: Camprodon-Boadas Patricia , Gil-Dominguez Aitana , De la Serna Elena , Sugranyes Gisela , Lázaro Iolanda , Baeza Immaculada 
Published: May 2024

Abstract

Context
Childhood and adolescence are periods of critical importance in the development of mental health disorders. The Mediterranean diet (MD) has been linked to multiple positive health outcomes, including reduced incidence of mental health disorders and fewer psychiatric symptoms.

Objective
This study aimed to investigate the association between adherence to an MD and mental health outcomes in children and adolescents.

Methods
A systematic literature review was conducted of original research that explored the relationship between psychiatric symptoms or disorders and adherence to an MD. The literature search was conducted on PubMed, Scopus, Web of Science, MEDES, Dialnet, and Latindex from inception to November 2022, and the Newcastle-Ottawa Scale was used to evaluate the quality of studies.

Results
A total of 13 studies (6 cross-sectional, 4 case-control, 2 randomized clinical trials, and 1 longitudinal cohort) out of 450 met the inclusion criteria. A total of 3058 children or adolescents with a mean age range from 8.6 to 16.2 years were included. Among the reviewed studies, 5 (71.42%) of those looking at attention-deficit/hyperactivity disorder, 4 (80%) examining depression, and 2 (50%) assessing anxiety found a significant protective association. Seven articles (53.84%) were found to be of high quality and 6 (46.15%) of moderate quality.

Conclusion
Adherence to an MD could be a protective factor for mental health in child and adolescent populations. This suggests that promoting an MD could help prevent the onset of clinical psychiatric symptoms, reduce symptom severity, and improve prognosis in young patients.

Systematic Review Registration
PROSPERO registration no. CRD42021276316.
Micromorphological and Chemical Characterization of Drimys winteri Leaf Surfaces: The Secondary Alcohols Forming Epicuticular Wax Crystals Are Accompanied by Alkanediol, Alkanetriol and Ketol Derivatives
Authors: Zhang Zhonghang , Mistry Dwiti , Jetter Reinhard 
Published: May 2024

Abstract
The cuticle is a hydrophobic coating of most aerial plant surfaces crucial for limiting non-stomatal water loss. Plant cuticles consist of the lipid polyester cutin and associated waxes with compositions varying widely between plant species and organs. Here, we aimed to provide a comparative analysis of the dark-glossy adaxial and pale-glaucous abaxial sides of Drimys winteri (Winteraceae) leaves. Scanning electron microscopy showed nanotubular wax crystals lining the entire abaxial side of the leaf (including stomatal pores), while the adaxial side had patches of mixed platelet/tubule crystals and smooth areas between them. Consecutive treatments for wax removal and cutin depolymerization revealed that the waxes were deposited on a cutin network with micron-scale cavities across the entire abaxial surface including the stomata pores, and on a microscopically smooth cutin surface on the adaxial side of the leaf. Gas chromatography coupled to mass spectrometry and flame ionization detection showed that the wax mixtures on both sides of the leaf were complex mixtures of very-long-chain compounds dominated by the secondary alcohol nonacosan-10-ol and alkanediols with one hydroxyl on C-10. It is therefore very likely that the characteristic tubular wax crystals of both leaf sides are formed by these alcohols and diols. Further secondary alcohols and alkanediols, as well as ketols and alkanetriols with one functional group on C-10, were identified based on mass spectral fragmentation patterns. The similarities between all these mid-chain-functionalized compounds suggest that they are derived from nonacosan-10-ol via regio-specific hydroxylation reactions, likely catalyzed by three P450-dependent monooxygenases with different regio-specificities.