bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single-cell deconvolution algorithms analysis unveils autocrine IL11-mediated resistance to docetaxel in prostate cancer via activation of the JAK1/STAT4 pathway
Authors: Cheng Bisheng , Li Lingfeng , Luo Tianlong , Wang Qiong , Luo Yong , Bai Shoumin , Li Kaiwen , Lai Yiming , Huang Hai 
Published: March 2024

Abstract
Background
Docetaxel resistance represents a significant obstacle in the treatment of prostate cancer. The intricate interplay between cytokine signalling pathways and transcriptional control mechanisms in cancer cells contributes to chemotherapeutic resistance, yet the underlying molecular determinants remain only partially understood. This study elucidated a novel resistance mechanism mediated by the autocrine interaction of interleukin-11 (IL-11) and its receptor interleukin-11 receptor subunit alpha(IL-11RA), culminating in activation of the JAK1/STAT4 signalling axis and subsequent transcriptional upregulation of the oncogene c-MYC.

Methods
Single-cell secretion profiling of prostate cancer organoid was analyzed to determine cytokine production profiles associated with docetaxel resistance.Analysis of the expression pattern of downstream receptor IL-11RA and enrichment of signal pathway to clarify the potential autocrine mechanism of IL-11.Next, chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) was performed to detect the nuclear localization and DNA-binding patterns of phosphorylated STAT4 (pSTAT4). Coimmunoprecipitation and reporter assays were utilized to assess interaction between pSTAT4 and the cotranscription factor CREB-binding protein (CBP) as well as their role in c-MYC transcriptional activity.

Results
Autocrine secretion of IL-11 was markedly increased in docetaxel-resistant prostate cancer cells. IL-11 stimulation resulted in robust activation of JAK1/STAT4 signalling. Upon activation, pSTAT4 translocated to the nucleus and associated with CBP at the c-MYC promoter region, amplifying its transcriptional activity. Inhibition of the IL-11/IL-11RA interaction or disruption of the JAK1/STAT4 pathway significantly reduced pSTAT4 nuclear entry and its binding to CBP, leading to downregulation of c-MYC expression and restoration of docetaxel sensitivity.

Conclusion
Our findings identify an autocrine loop of IL-11/IL-11RA that confers docetaxel resistance through the JAK1/STAT4 pathway. The pSTAT4-CBP interaction serves as a critical enhancer of c-MYC transcriptional activity in prostate cancer cells. Targeting this signalling axis presents a potential therapeutic strategy to overcome docetaxel resistance in advanced prostate cancer.

Graphical Abstract
Improving chemical reaction yield prediction using pre-trained graph neural networks
Authors: Han Jongmin , Kwon Youngchun , Choi Youn-Suk , Kang Seokho 
Published: March 2024

AbstractGraph neural networks (GNNs) have proven to be effective in the prediction of chemical reaction yields. However, their performance tends to deteriorate when they are trained using an insufficient training dataset in terms of quantity or diversity. A promising solution to alleviate this issue is to pre-train a GNN on a large-scale molecular database. In this study, we investigate the effectiveness of GNN pre-training in chemical reaction yield prediction. We present a novel GNN pre-training method for performance improvement.Given a molecular database consisting of a large number of molecules, we calculate molecular descriptors for each molecule and reduce the dimensionality of these descriptors by applying principal component analysis. We define a pre-text task by assigning a vector of principal component scores as the pseudo-label to each molecule in the database. A GNN is then pre-trained to perform the pre-text task of predicting the pseudo-label for the input molecule. For chemical reaction yield prediction, a prediction model is initialized using the pre-trained GNN and then fine-tuned with the training dataset containing chemical reactions and their yields. We demonstrate the effectiveness of the proposed method through experimental evaluation on benchmark datasets.
Accuracy of heart failure ascertainment using routinely collected healthcare data: a systematic review and meta-analysis
Authors: Goonasekera Michelle. A. , Offer Alison , Karsan Waseem , El-Nayir Muram , Mallorie Amy E. , Parish Sarah , Haynes Richard J. , Mafham Marion M. 
Published: March 2024

Abstract
Background
Ascertainment of heart failure (HF) hospitalizations in cardiovascular trials is costly and complex, involving processes that could be streamlined by using routinely collected healthcare data (RCD). The utility of coded RCD for HF outcome ascertainment in randomized trials requires assessment. We systematically reviewed studies assessing RCD-based HF outcome ascertainment against “gold standard” (GS) methods to study the feasibility of using such methods in clinical trials.

Methods
Studies assessing International Classification of Disease (ICD) coded RCD-based HF outcome ascertainment against GS methods and reporting at least one agreement statistic were identified by searching MEDLINE and Embase from inception to May 2021. Data on study characteristics, details of RCD and GS data sources and definitions, and test statistics were reviewed. Summary sensitivities and specificities for studies ascertaining acute and prevalent HF were estimated using a bivariate random effects meta-analysis. Heterogeneity was evaluated using I2 statistics and hierarchical summary receiver operating characteristic (HSROC) curves.

Results
A total of 58 studies of 48,643 GS-adjudicated HF events were included in this review. Strategies used to improve case identification included the use of broader coding definitions, combining multiple data sources, and using machine learning algorithms to search free text data, but these methods were not always successful and at times reduced specificity in individual studies. Meta-analysis of 17 acute HF studies showed that RCD algorithms have high specificity (96.2%, 95% confidence interval [CI] 91.5–98.3), but lacked sensitivity (63.5%, 95% CI 51.3–74.1) with similar results for 21 prevalent HF studies. There was considerable heterogeneity between studies.

Conclusions
RCD can correctly identify HF outcomes but may miss approximately one-third of events. Methods used to improve case identification should also focus on minimizing false positives.
Serum proteome analysis identifies a potential biomarker for axial psoriatic arthritis
Authors: Lu Chaofan , Yang Fan , He Shihao , Yu Hongxia , Wang Qian , Li Mengtao , Zeng Xiaofeng , Leng Xiaomei 
Published: March 2024

Abstract
Background
To identify potential serum biomarkers for differentiating between axial psoriatic arthritis (axPsA) and peripheral psoriatic arthritis (pPsA).

Methods
Serum samples were collected from patients with PsA to create a biomarker discovery cohort and a verification cohort. Patients with PsA were classified into axial or peripheral subtypes based on imaging criteria. Untargeted proteomics technology was used in the discovery phase to screen for biomarkers, and candidate biomarkers were evaluated using enzyme-linked immunosorbent assay (ELISA) in the verification phase.

Results
We identified 45 significantly differentially expressed proteins (DEPs) between axPsA (n = 20) and pPsA (n = 20) with liquid chromatography-mass spectrometry. Among these DEPs, serum pigment epithelium-derived factor (PEDF) was identified as a candidate biomarker using the Boruta algorithm and lasso regression. Results of ELISA further confirmed that the level of serum PEDF expression was significantly higher in axPsA (n = 37) than in pPsA (n = 51) at the verification cohort (37.9 ± 10.1 vs. 30.5 ± 8.9 μg/mL, p < 0.001). Receiver operating characteristics analysis showed that PEDF had an area under the curve (AUC) of 0.72. Serum PEDF was positively correlated with body mass index and C-reactive protein. Additionally, there was a tendency towards a positive correlation between PEDF and the Bath Ankylosing Spondylitis Disease Activity Index.

Conclusions
This study provided a comprehensive characterization of the proteome in axPsA and pPsA and identified a candidate biomarker, PEDF, that may contribute to early diagnosis for axPsA.
Drug conjugates for the treatment of lung cancer: from drug discovery to clinical practice
Authors: Zhou Ling , Lu Yunlong , Liu Wei , Wang Shanglong , Wang Lingling , Zheng Pengdou , Zi Guisha , Liu Huiguo , Liu Wukun , Wei Shuang 
Published: March 2024

AbstractA drug conjugate consists of a cytotoxic drug bound via a linker to a targeted ligand, allowing the targeted delivery of the drug to one or more tumor sites. This approach simultaneously reduces drug toxicity and increases efficacy, with a powerful combination of efficient killing and precise targeting. Antibody‒drug conjugates (ADCs) are the best-known type of drug conjugate, combining the specificity of antibodies with the cytotoxicity of chemotherapeutic drugs to reduce adverse reactions by preferentially targeting the payload to the tumor. The structure of ADCs has also provided inspiration for the development of additional drug conjugates. In recent years, drug conjugates such as ADCs, peptide‒drug conjugates (PDCs) and radionuclide drug conjugates (RDCs) have been approved by the Food and Drug Administration (FDA). The scope and application of drug conjugates have been expanding, including combination therapy and precise drug delivery, and a variety of new conjugation technology concepts have emerged. Additionally, new conjugation technology-based drugs have been developed in industry. In addition to chemotherapy, targeted therapy and immunotherapy, drug conjugate therapy has undergone continuous development and made significant progress in treating lung cancer in recent years, offering a promising strategy for the treatment of this disease. In this review, we discuss recent advances in the use of drug conjugates for lung cancer treatment, including structure-based drug design, mechanisms of action, clinical trials, and side effects. Furthermore, challenges, potential approaches and future prospects are presented.
Simultaneous determination of ethyl glucuronide, cocaine, cocaethylene, and benzoylecgonine in hair by using LC–MS/MS
Authors: Shin Dong Won , Kim Seon Yeong , Suh Sung Ill , Kim Jin Young 
Published: March 2024

AbstractAlcohol and cocaine (COC) are commonly co-used drugs that cause addiction and have harmful effects. Their abuse may threaten the health of the abuser and public safety by causing serious accidents or crimes. The recidivism rate of drug-related crimes closely correlates with alcoholism. Several incidences of alcohol consumption in combination with drug abuse have been reported. Here, liquid chromatography tandem mass spectrometric method was developed to simultaneously analyze ethyl glucuronide (EtG), a metabolite of ethanol; COC; cocaethylene (CE), an alcohol-derived metabolite of COC; and benzoylecgonine (BZE), a major metabolite of COC, to determine the concurrent use of alcohol with COC. For pre-treatment, ultracentrifugation (5 min, 50,000 g) and mixed-mode anion exchange solid-phase extraction were used to increase the recovery of target compounds and minimize the matrix effect of hair. The lower limits of quantification were: 7 pg/mg (EtG), 2 pg/mg (COC), 10 pg/mg (CE), and 1 pg/mg (BZE). The correlation coefficient (r) of the calibration curve within the quantified range of target compounds was ≥ 0.9978. The intra- and inter-day accuracies were − 6.1–9.7% and − 9.3–8.3%, and intra- and inter-day precisions were 0.5–10.3% and 0.6–14.4%, respectively. The recovery, matrix effect, process efficiency, and autosampler stability were 89.2–104.8%, 81.6–105.4%, 81.5–107.1%, and 96.6–109.7%, respectively. The novel analytical method was validated with hair samples from individuals suspected of alcohol and COC use, and the method could distinguish between independent and concurrent use. Based on the findings, the analytical approach developed in this study is anticipated to be valuable in drug and alcohol dependence tests that require the simultaneous detection of alcohol and COC abuse.
Impedance of electric field sensors in magnetized plasmas: particle-in-cell simulations
Authors: Fukasawa Ibuki , Miyake Yohei , Usui Hideyuki , Kusachi Koshiro , Kurita Satoshi , Kojima Hirotsugu 
Published: March 2024

AbstractTo obtain both the intensities and phases of electric fields, it is necessary to calibrate the data observed by the sensor by consulting the sensor characteristics. The frequency profile of the sensor impedance obtained from the simulation is roughly consistent with that obtained from the theory. However, some differences are identified in the frequency profile of the sensor impedance obtained from the simulation compared to the theory. We conducted simulations using the particle-in-cell (PIC) simulation tool to analyze the impedance of electric field sensors immersed in magnetized space plasmas. The simulation model comprised a dipole sensor placed in a three-dimensional simulation box filled with electrons and ions. The dipole sensor was represented by perfect conductor rods. We carefully selected simulation parameters and employed an appropriate feeding technique to accurately evaluate the sensor impedance. We observed significant changes in the frequency dependence of the sensor impedance as cyclotron frequency varied. To understand the simulation results, we introduced the linear dispersion relation. By comparing the real part of the sensor impedance with the $$\omega-k$$

ω
-
k

diagram, we found that the impedance peaks corresponded to frequencies at which branches of plasma waves were present, with $$k=k_{\text{half}}$$

k
=

k
half

, representing half the wavelength equal to the tip-to-tip sensor length, i.e., the sensor can be assumed as the half-wavelength dipole antenna.
Graphical Abstract
Evaluating mean platelet volume and platelet distribution width as predictors of early-onset pre-eclampsia: a prospective cohort study
Authors: Udeh Patience Ijeoma , Olumodeji Ayokunle Moses , Kuye-Kuku Taiwo Olufunmilayo , Orekoya Oluwaseun Olubowale , Ayanbode Olufemi , Fabamwo Adetokunbo Olusegun 
Published: March 2024

Abstract
Background
Platelets are pivotal players in the pathophysiology of pre-eclampsia, with observed lower counts in affected individuals compared to normotensive counterparts. Despite advancements, the elusive cause of pre-eclampsia persists, motivating intense global efforts to identify reliable predictors. The currently recommended predictors of pre-eclampsia are not readily available in many resource-limited regions like Nigeria. This cohort study explores the potential of mean platelet volume (MPV) and platelet distribution width (PDW) as predictive markers of early-onset pre-eclampsia. Both platelet indices are components of the full blood count, a widely available routine test in pregnancy.

Methods
In this prospective cohort study, 648 healthy pregnant women attending antenatal care at Lagos State University Teaching Hospital and General Hospital Ifako-Ijaiye, Lagos, were recruited between 14-18weeks gestational age. Platelet count (PC), MPV and PDW were measured from their venous blood at recruitment. Participants were monitored until 34weeks of gestation, focusing on the occurrence of early-onset preeclampsia as the outcome of interest. Individuals with chronic medical conditions were excluded from the study. Data analysis involved t-test, Chi-Square and Mann–Whitney U tests, with statistical significance set at a confidence level of 95% and p < 0.05. Sensitivity, specificity, and predictive values were determined using receiver operating characteristics (ROC) curves.

Results
The incidence of early-onset pre-eclampsia in the study was 5.9%. Women who later developed pre-eclampsia had higher median MPV and PDW at 14-18weeks (10.8 fl. and 24.8 fl.) compared to normotensive women (8.1 fl. and 13.3 fl.)(p < 0.001). The median PC was lower in pre-eclamptics (190 × 103/µl) compared to normotensives(264 × 103/µl)(p < 0.001). Using Youden’s test, cut-off values identified: PC < 211.5 × 103/µl, MPV > 9.4 fl., and PDW > 21.3 fl., predicted early-onset pre-eclampsia with 96.6% sensitivity and 65.6% specificity for PC; 79.3% sensitivity and 97.7% specificity for PDW; and 82.8% sensitivity and 96.1% specificity for MPV. Cut-offs of PC < 185 × 103/µl, MPV > 10.7 fl., and PDW > 28.3 fl., predicted severe early-onset pre-eclampsia with 100.0% sensitivity and 90.9% specificity for PC, 100.0% sensitivity and 99.4% specificity for MPV, and 100.0% sensitivity and 99.8% specificity for PDW, with corresponding area under the ROC curves of 0.983, 0.996, and 0.998, respectively.

Conclusion
The evaluation of MPV and PDW between 14 and 18 weeks of gestation appears to be a reliable predictor of severe early-onset pre-eclampsia.
Prevalence and determinants of minimum dietary diversity for women of reproductive age in Uganda
Authors: Kimuli Derrick , Nakaggwa Florence , Namuwenge Norah , Nsubuga Rebecca N. , Kasule Kenneth , Nyakwezi Sheila , Odong Jimmy , Isabirye Paul , Sevume Solome , Mubiru Norbert , Mwehire Daniel , Matovu Fatuma , Wandera Bonnie , Amuron Barbara , Bukenya Daraus 
Published: March 2024

Abstract
Background
Globally, over a billion women of reproductive age (WRA) suffer from some kind of undernutrition micronutrient deficiencies, and/or anemia as a result of inadequate dietary diversity. This leads to poor maternal and child health outcomes, however, there is limited research on population level research on minimum dietary diversity for women (MDD-W). This study assessed the prevalence and predictors of MDD-W among WRA in Uganda.

Methods
This study was a secondary analysis of data from the lot quality assurance sampling (LQAS) survey conducted across 55 Ugandan districts between May and September 2022. Women of various ages were interviewed across 5 study subgroups that this study used to construct its study population (WRA). Descriptive analyses, tests for outcome differences, and multilevel mixed-effects logistic regression were conducted at a 5% statistical significance level using STATA version 17. The results were reported using Adjusted Odds Ratios (aOR) as the measure of the outcome.

Results
The study analyzed responses from 29,802 WRA with a mean age of 27.8 (± 6.8) years. Only 8.8% (95% CI 8.5–9.3) achieved the MDD-W, the least proportion was observed in the South-Central region (3.13%). In the adjusted analysis, WRA who were older than 25 years (aOR 1.1, 95% CI 1.1–1.3, p < 0.001), had secondary education (aOR = 1.4, 95% CI 1.1–1.7, p = 0.003) or above (aOR = 1.7, 95% CI 1.3–2.2, p < 0.001), and used modern contraceptives (aOR = 1.1, 95% CI 1.0-1.3, p = 0.01) were more likely to achieve the MDD-W. Conversely, WRA who travelled longer distances to the nearest household water source (aOR = 0.8, 95% CI 0.7–0.9, p = 0.002) and those residing in larger households (aOR = 0.9, 95% CI 0.8-1.0, p = 0.019) were less likely to achieve the MDD-W.

Conclusion
A low proportion of WRA met the MDD-W. Age, education level, household sizes and use of modern contraception were predictors of MDD-W among WRA in Uganda. MDD-W-related program efforts in Uganda should strengthen multisectoral collaboration with prioritization of younger women, education, household sizes and access to safe water sources.
Effect of COVID-19 Pandemic Lockdowns on Body Mass Index of Primary School Children from Different Socioeconomic Backgrounds
Authors: Piesch Ludwig , Stojan Robert , Zinner Jochen , Büsch Dirk , Utesch Katharina , Utesch Till 
Published: March 2024

AbstractBackgroundChildhood obesity is associated with various health outcomes. Restrictive measures to contain the spread of the Coronavirus Disease 2019 (COVID-19) pandemic, like lockdowns and school closures, affected children’s daily structure, physical activity, dietary habits, and sleep quality, possibly exacerbating risk factors for childhood obesity and higher body mass index (BMI) in children. Poor socioeconomic conditions may have led to relatively higher risk for elevated BMI levels following pandemic measures. In this study, the impact of measures related to the COVID-19 pandemic on the BMI of third graders was investigated regarding children’s socioeconomic background (SEB).MethodsData from 41,728 children (8.84 ± 0.56 years, 20,431 female) were collected in the context of a cohort study. Children were tested either before the pandemic (preCOVID: Sept2017–March2020,n = 26,314), or following the first (postLDI: Aug2020–Dec2020,n = 6657) or second lockdown in Germany (postLDII: Aug2021–Jan2022,n = 8757). SEB was based on the official school type classification of the state of Berlin. Outcome was BMI standard deviation scores (SDS).ResultsSignificant effects of Time and SEB revealed elevated BMIs in postLDI(M = 0.23,p = 0.011) and postLDII(M = 0.22,p = 0.011) compared to preCOVID(M = 0.17) cohorts and higher BMIs for children with lower SEB (b = − 0.13, p < 0.001). A significant Time × SEB interaction indicated that the effect of SEB on children’s BMI increased in response to lockdowns, especially in postLDII(b = − 0.05, p = 0.006). Results suggest that the COVID-19-related measures lead to increased BMI in children, and that children of lower SEB were at particular risk for higher BMIs following lockdowns.ConclusionsThese findings highlight the dependency of children’s BMI on societal circumstances. Over the course of two lockdowns in Germany, children have experienced BMI increments, particularly in low socioeconomic areas. Authorities are called into action to counteract increasing rates of childhood weight by promoting physical activity of children and establishing related post-pandemic offers.
Construction of individualised care programmes for patients with pancreatic cancer with postoperative weight-loss control based on the Delphi method: a cross-sectional study in China
Authors: Chen Leying , Huang Zhongyan , Tian Qiuju , Zha Qinghua , Zhang Shiyu , Chen Zhe , Dong Ziyun , Zhou Yuqing , Zhang Ming , Wei Xiaoyan 
Published: March 2024

AbstractBackgroundAt present, clinical nutritional care for patients with pancreatic cancer focuses more on the observation of the effect of enteral parenteral nutrition, and there is a lack of personalised care plans for weight-loss control. We used the Delphi method to construct a set of personalised nursing programmes to effectively control the rate of postoperative weight loss in patients with pancreatic cancer.MethodsThis study was a cross-sectional investigation. Through literature analysis, literature review and data review, a personalised nursing plan for the postoperative weight-loss control in patients with pancreatic cancer was preliminarily developed. From October to December 2022, the Delphi method was adopted to conduct two questionnaires for 32 experts working in fields related to pancreatic diseases in Grade-A tertiary hospitals from four different departments. After statistical processing, the personalised nursing plan was determined according to the perceived level of importance, coefficient of variation, full score rate and recognition rate of the indicators.ResultsThe recovery rates of the two rounds of consultation were 93.75% and 100%, respectively, and the overall authority coefficient of the experts was 0.918, which represented ‘authoritative’. In terms of importance, the coefficient of variation was 0–0.137; in terms of feasibility, the coefficient of variation ranged from 0.09 to 0.194. Finally, a scheme consisting of 36 entries in 8 dimensions was built. This programme is comprehensive in content, meets the nutritional diagnosis and treatment needs of patients in the stage of postoperative rehabilitation, provides relatively comprehensive nutritional assessment and support and has a robust system and feasibility.ConclusionsThe individualised nursing plan for patients with pancreatic cancer with postoperative weight-loss control based on the Delphi method is highly scientific and reliable and has positive significance.