bluuebunny/crossref_metadata_2025_split huggingface dataset:
CDKL1 potentiates the antitumor efficacy of radioimmunotherapy by binding to transcription factor YBX1 and blocking PD-L1 expression in lung cancer
Authors: Li Zixuan , Xue Huichan , Li Jinsong , Zheng Zhikun , Liu Zhiwei , Dong Xiaorong , Wang Hongbo , Chen Jing , Xu Shuangbing 
Published: March 2024

Abstract
Background
The evasion of the immune response by tumor cells through programmed death-ligand 1 (PD-L1) has been identified as a factor contributing to resistance to radioimmunotherapy in lung cancer patients. However, the precise molecular mechanisms underlying the regulation of PD-L1 remain incompletely understood. This study aimed to investigate the role of cyclin-dependent kinase-like 1 (CDKL1) in the modulation of PD-L1 expression and the response to radioimmunotherapy in lung cancer.

Methods
The tumorigenic roles of CDKL1 were assessed via cell growth, colony formation, and EdU assays and an in vivo nude mouse xenograft model. The in vitro radiosensitization effect of CDKL1 was evaluated using a neutral comet assay, γH2AX foci formation analysis, and a clonogenic cell survival assay. The protein‒protein interactions were confirmed via coimmunoprecipitation and GST pulldown assays. The regulation of PD-L1 by CDKL1 was evaluated via chromatin immunoprecipitation (ChIP), real-time quantitative PCR, and flow cytometry analysis. An in vitro conditioned culture model and an in vivo C57BL/6J mouse xenograft model were developed to detect the activation markers of CD8+ T cells and evaluate the efficacy of CDKL1 overexpression combined with radiotherapy (RT) and an anti-PD-L1 antibody in treating lung cancer.

Results
CDKL1 was downregulated and suppressed the growth and proliferation of lung cancer cells and increased radiosensitivity in vitro and in vivo. Mechanistically, CDKL1 interacted with the transcription factor YBX1 and decreased the binding affinity of YBX1 for the PD-L1 gene promoter, which consequently inhibits the expression of PD-L1, ultimately leading to the activation of CD8+ T cells and the inhibition of immune evasion in lung cancer. Moreover, the combination of CDKL1 overexpression, RT, and anti-PD-L1 antibody therapy exhibited the most potent antitumor efficacy against lung cancer.

Conclusions
Our findings demonstrate that CDKL1 plays a crucial role in regulating PD-L1 expression, thereby enhancing the antitumor effects of radioimmunotherapy. These results suggest that CDKL1 may be a promising therapeutic target for the treatment of lung cancer.
Preferences in adolescents and young people’s sexual and reproductive health services in Nigeria: a discrete choice experiment
Authors: Arije Olujide , Madan Jason , Hlungwani Tintswalo 
Published: March 2024

Abstract
Background
Barriers to utilization of sexual and reproductive health (SRH) services by adolescents and young people (AYP) have persisted despite evidence that youth-friendly services have a positive effect on contraceptive use, and patient knowledge and satisfaction.

Objective
The objective of this study was to elicit, and derive relative valuations for, attributes of SRH services that adolescents and young people value, and their willingness to pay for these services, in public health facilities.

Methods
A discrete-choice-experiment (DCE) that was developed using a mixed methods approach was administered to AYP from Ogun State, Southwest Nigeria. The DCE attributes were: the type of staff; physical environment; health worker attitude; cost; waiting time; contraceptive availability; and opening hours. The choice tasks had two unlabeled alternatives and an opt-out option. Panel mixed logit choice model was used to fit the choice data, along with estimation of willingness to pay (WTP). Also, a latent class logit model was used to detect underlying preference heterogeneity among the respondents. Finally, the uptake of the services in health facilities was investigated by estimating the probabilities for selecting hypothetical health facilities under different scenarios.

Results
A total of 859 AYP participated resulting in 6872 choice observations. The physical environment attribute had the highest utility rating relative to the other attributes, followed by preference for a doctor and for a service provider who was open and friendly. The cost and time coefficients were negative, revealing preference for lower cost and shorter waiting time. The latent class model had three classes that varied by their background characteristics. Probability of choosing any of the facility alternatives increased with introduction of more favorable facility characteristics.

Conclusion
The pattern of preferences identified are potential targets for service design and delivery optimization that may result in improvements in service acceptability and utilization. These results strengthen the call for involving AYP in decision-making in health interventions for them and developing context-specific SRH programs for AYP in public health facilities.
Edge intelligence empowered delivery route planning for handling changes in uncertain supply chain environment
Authors: Peng Gaoxian , Wen Yiping , Dou Wanchun , Li Tiancai , Xu Xiaolong , Ye Qing 
Published: March 2024

AbstractTraditional delivery route planning faces challenges in reducing logistics costs and improving customer satisfaction with growing customer demand and complex road traffic, especially in uncertain supply chain environment. To address these challenges, we introduce an innovative two-phase delivery route planning method integrating edge intelligence technology. The novelty of our approach lies in utilizing edge computing devices to monitor real-time changes in road conditions and dynamically adjust delivery routes, thereby providing an effective solution for efficient and flexible logistics. Initially, we construct a mixed-integer programming model that minimizes the total cost under constraints such as customer destinations and time windows. Subsequently, in the cloud-edge collaborative mode, edge computing devices are utilized to collect real-time road conditions and transmit it to the cloud server. The cloud server comprehensively considers customer demand and road condition changes and employs adaptive genetic algorithms and A-star algorithms to adjust the delivery routes dynamically. Finally, comprehensive experiments are conducted to validate the effectiveness of our method. The results demonstrate that our approach can promptly respond to changes in customer demands and road conditions and flexibly plan the optimal delivery routes, thereby significantly reducing overall costs and enhancing customer satisfaction.
Short-term forecasting of surface solar incident radiation on edge intelligence based on AttUNet
Authors: Cui Mengmeng , Zhao Shizhong , Yao Jinfeng 
Published: March 2024

AbstractSolar energy has emerged as a key industry in the field of renewable energy due to its universality, harmlessness, and sustainability. Accurate prediction of solar radiation is crucial for optimizing the economic benefits of photovoltaic power plants. In this paper, we propose a novel spatiotemporal attention mechanism model based on an encoder-translator-decoder architecture. Our model is built upon a temporal AttUNet network and incorporates an auxiliary attention branch to enhance the extraction of spatiotemporal correlation information from input images. And utilize the powerful ability of edge intelligence to process meteorological data and solar radiation parameters in real-time, adjust the prediction model in real-time, thereby improving the real-time performance of prediction. The dataset utilized in this study is sourced from the total surface solar incident radiation (SSI) product provided by the geostationary meteorological satellite FY4A. After experiments, the SSIM has been improved to 0.86. Compared with other existing models, our model has obvious advantages and has great prospects for short-term prediction of surface solar incident radiation.
Security issues of news data dissemination in internet environment
Authors: Song Kang , Shang Wenqian , Zhang Yong , Yi Tong , Wang Xuan 
Published: March 2024

AbstractWith the rise of artificial intelligence and the development of social media, people's communication is more convenient and convenient. However, in the Internet environment, the untrue dissemination of news data leads to a large number of problems. Efficient and automatic detection of rumors in social platforms hence has become an important research direction in recent years. This paper leverages deep learning methods to mine the changing trend of user features related to rumor events, and designs a rumor detection model called Time Based User Feature Capture Model(TBUFCM). To obtain a new feature vector representing the user's comprehensive features under the current event, the proposed model first recomputes the user feature vector by using feature enhancement function. Then it utilizes GRU(Gate Recurrent Unit, GRU) and CNN(Convolutional Neural Networks, CNN) models to learn the global and local changes of user features, respectively. Finally, the hidden rumor features in the process of rumor propagation can be discovered by user and time information. The experimental results show that TBUFCM outperforms the baseline model, and when there are only 20 forwarded posts, it can also reach an accuracy of 92%. The proposed method can effectively solve the security problem of news data dissemination in the Internet environment.
Assessing the potential for improved predictive capacity of antimicrobial resistance in outpatient Staphylococcus aureus isolates using seasonal and spatial antibiograms
Authors: Carrel Margaret , Shi Qianyi , Clore Gosia S. , Hasegawa Shinya , Smith Matthew , Perencevich Eli N. , Goto Michihiko 
Published: March 2024

AbstractBackgroundWhile the use of cumulative susceptibility reports, antibiograms, is recommended for improved empiric therapy and antibiotic stewardship, the predictive ability of antibiograms has not been well-studied. While enhanced antibiograms have been shown to better capture variation in susceptibility profiles by characteristics such as infection site or patient age, the potential for seasonal or spatial variation in susceptibility has not been assessed as important in predicting likelihood of susceptibility.MethodsUtilizingStaphylococcus aureusisolates obtained in outpatient settings from a nationwide provider of care, the Veterans Health Administration, and a local provider of care, the University of Iowa Hospitals and Clinics, standard, seasonal and spatial antibiograms were created for five commonly used antibiotic classes: cephalosporins, clindamycin, macrolides, tetracycline, trimethoprim/sulfamethoxazole.ResultsA total of 338,681S. aureusisolates obtained in VHA outpatient settings from 2010 to 2019 and 6,817 isolates obtained in UIHC outpatient settings from 2014 to 2019 were used to generate and test antibiograms. Logistic regression modeling determined the capacity of these antibiograms to predict isolate resistance to each antibiotic class. All models had low predictive capacity, with areas under the curve of < 0.7.ConclusionsStandard antibiograms are poor in predictingS. aureussusceptibility to antibiotics often chosen by clinicians, and seasonal and spatial antibiograms do not provide an improved tool in anticipating non-susceptibility. These findings suggest that further refinements to antibiograms may be necessary to improve their utility in informing choice of effective antibiotic therapy.
Characterization of lamina propria remodeling in pediatric eosinophilic esophagitis using second harmonic generation microscopy
Authors: Haugen Ezekiel J. , Locke Andrea K. , Correa Hernán , Baba Justin S. , Mahadevan-Jansen Anita , Hiremath Girish 
Published: March 2024

AbstractEosinophilic esophagitis (EoE) is a chronic inflammatory condition characterized by an intense infiltration of eosinophils into the esophageal epithelium. When not adequately controlled, eosinophilic inflammation can lead to changes in components of the extracellular matrix (ECM) of the lamina propria. Particularly, alterations to the collagen fiber matrix can lead to lamina propria fibrosis (LPF), which plays an important role in the fibrostenotic complications of EoE. Current approaches to assess LPF in EoE are prone to inter-observer inconsistencies and provide limited insight into the structural remodeling of the ECM. An objective approach to quantify LPF can eliminate inter-observer inconsistencies and provide novel insights into the fibrotic transformation of the lamina propria in EoE. Second harmonic generation (SHG) microscopy is a powerful modality for objectively quantifying disease associated alterations in ECM collagen structure that is finding increasing use for clinical research. We used SHG with morphometric analysis (SHG-MA) to characterize lamina propria collagen fibers and ECM porosity in esophageal biopsies collected from children with active EoE (n = 11), inactive EoE (n = 11), and non-EoE (n = 11). The collagen fiber width quantified by SHG-MA correlated positively with peak eosinophil count (r = 0.65, p < 0.005) and histopathologist scoring of LPF (r = 0.52, p < 0.005) in the esophageal biopsies. Patients with active EoE had a significant enlargement of ECM pores compared to inactive EoE and non-EoE (p < 0.005), with the mean pore area correlating positively with EoE activity (r = 0.76, p < 0.005) and LPF severity (r = 0.65, p < 0.005). These results indicate that SHG-MA can be utilized to objectively characterize and provide novel insights into lamina propria ECM structural remodeling in children with EoE, which could aid in monitoring disease progression.
Pulmonary CT perfusion robustly measures cardiac output in the context of multilevel pulmonary occlusion: a porcine study
Authors: Silva Diogo , Muders Thomas , Wodack Karin , Putensen Christian , Leonhardt Steffen , Siepmann Robert , Hentze Benjamin , Reinartz Sebastian 
Published: March 2024

Abstract
Background
To validate pulmonary computed tomography (CT) perfusion in a porcine model by invasive monitoring of cardiac output (CO) using thermodilution method.

Methods
Animals were studied at a single center, using a Swan-Ganz catheter for invasive CO monitoring as a reference. Fifteen pigs were included. Contrast-enhanced CT perfusion of the descending aorta and right and left pulmonary artery was performed. For variation purposes, a balloon catheter was inserted to block the contralateral pulmonary vascular bed; additionally, two increased CO settings were created by intravenous administration of catecholamines. Finally, stepwise capillary occlusion was performed by intrapulmonary arterial injection of 75-μm microspheres in four stages. A semiautomatic selection of AFs and a recirculation-aware tracer-kinetics model to extract the first-pass of AFs, estimating blood flow with the Stewart-Hamilton method, was implemented. Linear mixed models (LMM) were developed to calibrate blood flow calculations accounting with individual- and cohort-level effects.

Results
Nine of 15 pigs had complete datasets. Strong correlations were observed between calibrated pulmonary (0.73, 95% confidence interval [CI] 0.6–0.82) and aortic blood flow measurements (0.82, 95% CI, 0.73–0.88) and the reference as well as agreements (± 2.24 L/min and ± 1.86 L/min, respectively) comparable to the state of the art, on a relatively wide range of right ventricle-CO measurements.

Conclusions
CT perfusion validly measures CO using LMMs at both individual and cohort levels, as demonstrated by referencing the invasive CO.

Relevance statement
Possible clinical applications of CT perfusion for measuring CO could be in acute pulmonary thromboembolism or to assess right ventricular function to show impairment or mismatch to the left ventricle.

Key points
• CT perfusion measures flow in vessels.
• CT perfusion measures cumulative cardiac output in the aorta and pulmonary vessels.
• CT perfusion validly measures CO using LMMs at both individual and cohort levels, as demonstrated by using the invasive CO as a reference standard.

Graphical Abstract
Predictors of mortality among children at a tertiary hospital in Tanzania: a cohort study
Authors: Damian Diana K. , Furia Francis F. , Leyna Germana 
Published: March 2024

Abstract
Background
Tanzania is among the countries in sub-Saharan Africa with the highest under-five mortality rate. The leading causes of mortality among these children include vaccine-preventable infections. Strategies for reducing under-five mortality in hospital settings require a good knowledge of driving factors, which are largely unknown in Tanzania. This study was conducted at Muhimbili National Hospital to determine mortality and its predictors among under-five admitted in the general paediatric wards.

Methods
We conducted a prospective cohort study among children aged between 1 and 59 months admitted in the paediatric wards at Muhimbili National Hospital from 2nd October 2017 to 13th April 2018. We recruited eligible children consecutively and followed them up until discharge or death. We calculated the mortality rate as the incidence density rate and determined the causes and predictors of mortality. We analyzed data to identify and quantify predictors of deaths and used Kaplan-Meir and Cox regression analyses to determine predictors of survival. A P-value of < 0.05 was considered statistically significant.

Results
We recruited 925 children aged 1–59 months with a median age of 13 and (IQR) of (20) months, females constituted 40.8%. The overall mortality rate was 12.2% (95% CI: 10.2%-14.5%). We found septicaemia (27%), malnutrition (12%), congenital heart disease (12%), pneumonia (11%), and Human Immunodeficiency Virus infection (9%) to be leading causes of mortality. More deaths were observed at night, during the first 24 h of admission, and on weekends. Independent factors for mortality were found to be low wealth quintiles (lowest quintile (AOR = 4.0; 95% CI: 1.19–13.51), second quintile (AOR = 5.2; 95% CI: 1.65–16.69) and middle quintile (AOR = 3.6; 95% CI: 1.14–11.33), unconsciousness on admission (AOR = 18; 95% CI: 6.70–56.82), inability to feed (AOR = 5.7; 95% CI: 1.97–16.51), lethargy (AOR = 4.9; 95% CI: 2.32–10.40), severe wasting (AOR = 4.5; 95% CI: 2.49–8.10), and respiratory distress (AOR = 2.6; 95% CI: 1.40–4.97).

Conclusion
A high mortality rate was noted in this study and low wealth quantile, low parental education, and lack of health insurance were associated with high mortality. Patients had the highest risk of mortality within 24 h of admission, therefore it is important to raise awareness among clinicians regarding the need for improvement in the monitoring of patients, especially within 24 h of admission.
Abnormal theta and alpha oscillations in children and adolescents with first-episode psychosis and clinical high-risk psychosis
Authors: Zhang Yaru , Yang Tingyu , He Yuqiong , Meng Fanchao , Zhang Kun , Jin Xingyue , Cui Xilong , Luo Xuerong 
Published: March 2024

Background
Cognitive control deficits are one of the main symptoms of psychosis. The basic neural oscillation patterns associated with cognitive control are already present in early adolescence. However, as previous studies have focused on adults with psychosis, it is unclear whether neurobiological impairments in cognitive control are present in children and adolescents with first-episode psychosis (FEP) or clinical high-risk (CHR) state for psychosis.

Aims
To explore the deficits of electroencephalogram related to cognitive control tasks in children and adolescents with FEP and CHR.

Method
Electroencephalogram was recorded in untreated 48 patients with FEP, 24 patients with CHR and 42 healthy controls aged 10–17 years, while performing the visual oddball task. The N2 amplitude, theta and alpha oscillations were then analysed and compared between groups.

Results
There was no significant group difference in N2 amplitude (P = 0.099). All groups showed increased theta and alpha oscillations relative to baseline before the stimulus in the frontal, central, left fronto-central and right fronto-central areas. These changes differed significantly between groups, with the FEP group showing significantly smaller theta (P < 0.001) and alpha (P < 0.01) oscillation than healthy controls. Theta and alpha oscillations in the CHR group did not differ significantly from the FEP group and healthy controls.

Conclusions
These results suggest that neural damage has already occurred in the early stage of psychosis, and that abnormal rhythmic activity of neurons may constitute the pathophysiological mechanism of cognitive dysfunction related to early-onset psychosis.
Diabetic Ketoacidosis With the Use of Alpelisib in a Patient With Metastatic Breast Cancer Without Diabetes
Authors: Polisetty Lakshmi , Teresa Selvin Sneha , Tan Jia Wei 
Published: March 2024

Abstract
Diabetic ketoacidosis (DKA) is a life-threatening medical condition. Alpelisib, a new drug used to treat phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha mutated breast cancer, is reported to cause DKA as a rare adverse effect. We present a case of alpelisib-induced DKA in a patient with metastatic breast cancer without diabetes. An 81-year-old female with a history of hormone receptor-positive, human epidermal growth factor receptor 2-negative metastatic breast cancer presented to the emergency room with clinical features and blood work consistent with DKA. She was started on alpelisib 6 weeks before her presentation to the hospital. She did not have a documented history of diabetes. Upon admission, alpelisib was held, and her blood glucose returned to baseline with intravenous insulin and hydration. Post-discharge, she was managed with sitagliptin. Subsequent attempts to reintroduce alpelisib were associated with hyperglycemia, which led to the permanent discontinuation of alpelisib and the transition to alternative treatment options. Alpelisib causes hyperglycemia by inhibiting the phosphatidylinositol 3-kinase/activated protein kinase-B pathway, which regulates blood glucose levels. This case report illustrates DKA as a presenting symptom and provides potential management options for alpelisib-induced DKA. Hyperglycemia is a frequent adverse effect of alpelisib in patients with diabetes. This case report is unique as our patient developed uncontrolled diabetes within a few weeks after initiation of alpelisib.
Monolithic deformable mirror based on lithium niobate single crystal for high-resolution X-ray adaptive microscopy
Authors: Inoue Takato , Nakabayashi Sota , Uematsu Kota , Tanaka Yuto , Nakamori Hiroki , Kohmura Yoshiki , Yabashi Makina , Matsuyama Satoshi 
Published: March 2024

X-ray microscopy is very promising not only for nondestructive and high-spatial-resolution observation of the internal structure of a sample but also for elemental distribution and chemical state analysis. However, the spatial resolution of microscopes remains unsatisfactory owing to the fabrication error in the objective lens. To realize an ultra-high-resolution, we propose and develop a monolithic deformable mirror based on a lithium niobite single crystal and a novel adaptive imaging system based on it. An X-ray interferometer confirmed that shape modification is possible with an accuracy of 0.67 nm in peak to valley under high stability (0.17 nm over 7 h) and hysteresis-free deformation control. Introducing this adaptive mirror into an X-ray microscope based on advanced Kirkpatrick-Baez mirror optics and correcting the wavefront aberration demonstrated that the X-ray image quality could be significantly improved.