bluuebunny/crossref_metadata_2025_split huggingface dataset:
Keratin 17 modulates the immune topography of pancreatic cancer
Authors: Delgado-Coka Lyanne A. , Horowitz Michael , Torrente-Goncalves Mariana , Roa-Peña Lucia , Leiton Cindy V. , Hasan Mahmudul , Babu Sruthi , Fassler Danielle , Oentoro Jaymie , Bai Ji-Dong Karen , Petricoin Emanuel F , Matrisian Lynn M. , Blais Edik Matthew , Marchenko Natalia , Allard Felicia D. , Jiang Wei , Larson Brent , Hendifar Andrew , Chen Chao , Abousamra Shahira , Samaras Dimitris , Kurc Tahsin , Saltz Joel , Escobar-Hoyos Luisa F. , Shroyer Kenneth 
Published: February 2024

Abstract

Background:
The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potential modulator of the immune response in most cancers, Keratin 17 (K17), a biomarker of the most aggressive (basal) molecular subtype of PDAC, is intimately involved in the histogenesis of the immune response in psoriasis, basal cell carcinoma, and cervical squamous cell carcinoma. Thus, we hypothesized that K17 expression could also impact the immune cell response in PDAC, and that uncovering this relationship could provide insight to guide the development of immunotherapeutic opportunities to extend patient survival.
Methods:
Multiplex immunohistochemistry (mIHC) and automated image analysis based on novel computational imaging technology were used to decipher the abundance and spatial distribution of T cells, macrophages, and tumor cells, relative to K17 expression in 235 PDACs.
Results:
K17 expression had profound effects on the exclusion of intratumoral CD8 + T cells and was also associated with decreased numbers of peritumoral CD8 + T cells, CD16 + macrophages, and CD163 + macrophages (p < 0.0001). The differences in the intratumor and peritumoral CD8 + T cell abundance were not impacted by neoadjuvant therapy, tumor stage, grade, lymph node status, histologic subtype, nor KRAS, p53, SMAD4, or CDKN2A mutations.
Conclusions:
Thus, K17 expression correlates with major differences in the immune microenvironment that are independent of any tested clinicopathologic or tumor intrinsic variables, suggesting that targeting K17-mediated immune effects on the immune system could restore the innate immunologic response to PDAC and might provide novel opportunities to restore immunotherapeutic approaches for this most deadly form of cancer.
Incompleteness and misclassification of maternal deaths in Zimbabwe: data from two reproductive age mortality surveys, 2007-08 and 2018-19
Authors: Musarandega Reuben , Nystrom Lennarth , Murewanhema Grant , Gwanzura Chipo , Ngwenya Solwayo , Pattinson Robert , Machekano Rhoderick , Munjanja Stephen Peter 
Published: February 2024

Abstract
Introduction: Reducing maternal mortality is a high-priority global health goal, especially in sub-Saharan Africa, where the maternal mortality ratios (MMRs) of most of the countries is higher than the average global MMR. We implemented two cross-sectional reproductive age mortality surveys, in 2007-08 and 2018-19, to assess changes in the MMR and causes of death in Zimbabwe after a raft of interventions implemented to reduce maternal mortality. This paper analysed the missingness and misclassification of deaths in the surveys.
Methods: We compared percentages of missed deaths in each survey using the Chi-square test. The risk ratios of missing deaths in different data sources in each survey were calculated using log-linear regression models. Proportions of misclassified deaths were compared using Fisher’s exact test and sensitivity and specificity of incompleteness and misclassification of deaths compared using the six-box method and the Chi-square test.
Results: The proportion of missed pregnancy-related deaths decreased from 27% in 2007-08 to 18% in 2018-19 (p=0.044) and the proportion of missed maternal deaths decreased from 30% in 2007-08 to 19% in 2018-19. Misclassification of maternal deaths in health records was 17% in 2007-08 and 8.5% in 2018-19 (p=0.160). The proportion of pregnancy-related deaths identified through health records increased from 11% in 2007-08 to 60% in 2018-19 (p<0.001). Sensitivity of incompleteness and misclassification of deaths was 95% in 2007-08 and 77% in 2018-19, and specificity was 29% and 83% respectively.
Conclusion: Incompleteness and misclassification of maternal deaths are still a challenge in Zimbabwe. Maternal death studies must triangulate data sources to improve the completeness of data and efforts to reduce misclassification of deaths should continue to improve maternal mortality estimates.
Segmented and actuated tool electrode for transverse wave flushing in sinking electrical discharge machining (S-EDM)
Authors: Uhlmann Eckart , Ludwig Jonas , Lahoda Christian , Westhoff Bela Schulte , Maas Jürgen 
Published: February 2024

Abstract
In sinking electrical discharge machining (S-EDM), high-precision manufacturing processes require numerous tool electrodes for compensating excessive tool electrode wear. The manufacturing of tool electrodes leads to high costs and process times within the process chain. A novel approach is the segmentation of the tool electrode for a variable shaping, which is realised by an actuation of single tool electrode segments using miniaturised linear actuators to perform the roughing process. In addition, the segmentation of the tool electrode allows the implementation of novel flushing strategies. During the process debris particles emerge in the working gap, which need to be flushed out to improve the process conditions and maximise the material removal rate MRR. In this study, the generation of transverse waves is experimentally analysed in a test setup and was modelled in computational fluid dynamics (CFD) to investigate the flushing behaviour of 25 actuated single tool electrode segments. The experimental series showed a direct fluid movement with maximum fluid velocities of vs,max = 62.5 mm/s in the working gap with an actuated amplitude A = 1.5 mm and a frequency f = 5 Hz. This allows a novel efficient flushing strategy in S-EDM to remove debris particles out of the working gap for an increasing material removal rate.
Enhancing soil health and fruit yield through Tephrosia biomass mulching in rainfed guava (Psidium guajava L.) orchards
Authors: Ali Abeer , Das Bikash , Dhakar M. K. , Naik S. K. , Patel V. B. , Mishra G. P. 
Published: February 2024

Abstract

Tephrosia candida, a leguminous green manuring crop, exhibits superior biomass production and notably higher concentrations of carbon, nitrogen, phosphorus, potassium, and essential micronutrients. The research was undertaken to standardize the quantity of Tephrosia candida biomass for mulching in high density guava orchard. The experiment was initiated in the year 2019 comprising of four treatments viz. T1 = 3.0 kg dry biomass per square meter of the plant basin, T2 = 2.0 kg dry biomass per square meter of the plant basin, T3 = 1.0 kg dry biomass per square meter of the plant basin and T4 = control (No mulch). The treatments were imposed in the plant basin of a 12-year-old guava (cultivar: Allahabad Safeda) orchard planted at a spacing of 1.0m x 2.0m, accommodating 5000 plants per hectare. Each treatment was replicated five times. The present investigation recorded the data pertaining to the effects of the treatments during the third year of experimentation. Mulching with 3 kg of biomass per m2 resulted in hastening of the winter bud stage by 29.17 days, increase in trunk diameter by 50.47%, fruit yield of winter crop by 42.25%, fruit weight by 11.00%, specific leaf area by 18% over the control. Moreover, there were notable increases in the levels of leaf total chlorophyll, total nitrogen, phosphorus, potassium, iron, zinc and manganese. Additionally, there was a marked reduction in total anthocyanin content of the leaves during the winter dormancy. Biomass mulching at rates of 3.0 kg/m2 or 2.0 kg/m2 significantly improved soil properties, including EC, available nitrogen, available phosphorus, exchangeable potassium, DTPA extractable micronutrients (Fe, Zn, Cu, and Mn), and Ctot, Ctot, Cfrac1,2,3,4, and microbial biomass carbon within 0 to 15cm and 15 to 30cm soil depths. The FDA and DHA peaked in April 2022 and reached minimum values in January 2022, in both soil depths.
Role of antidepressant receptor antagonism and the development of gestational diabetes: a nested case-control study
Authors: Robiyanto Robiyanto , Veldkamp Neel , Puijenbroek Eugène P , Vos Stijn , Bos Jens H J , Hak Eelko , Schuiling-Veninga Catharina C M 
Published: February 2024

Abstract

Background
How receptor binding profiles of antidepressants (ADs) influence the development of gestational diabetes mellitus (GDM) is infrequently examined. We aimed to investigate which receptor antagonism of antidepressants is associated with GDM development in pregnancy.
Methods
A nested case-control study (1994–2021) comprising 4014 singleton pregnancies was conducted using the pregnancy subset from the IADB.nl prescription database. GDM cases were pregnant women receiving GDM medication (insulin and or oral hypoglycemic agent) for the first time. Exposure was defined as the recent use of ADs (between six months before and week 16 of pregnancy), stratified by AD antagonistic properties on H1, 5-HT2C, and M3 receptors. Crude and adjusted odds ratios of GDM were compared between recent users and past users using the logistic regression model.
Results
Antidepressant use with antagonistic properties on H1 receptors (aOR 2.25(95% CI 1.15–4.10)) and 5-HT2C receptors (aOR 1.90 (95% CI 1.06–3.23)) were associated with increased odds of GDM. No association was found for AD antagonists on M3 receptors (aOR 1.35(0.82–2.27)).
Conclusion
The antagonism affinity of antidepressants on H1 receptor and 5-HT2C receptor antagonism is more associated with the odds of GDM than on M3 receptor. This emphasizes the importance of prescribing antidepressants with weak or non-affinity on these two receptors to minimize the risk for GDM.
Prolactin And Non-Puerperal Mastitis: A Cohort Study Using Real-World Data
Authors: yin yulian , Le Haoxin , Cheng Yifan , Zhong Yuanyuan , Cheng Yiqin , Wang Bing , Wu Jingjing , Ye Meina , Chen Hongfen 
Published: February 2024

Abstract
Objective
Non-puerperal mastitis (NPM) is an umbrella term for non-specific inflammatory mastitis inflammation with unclear etiology. The objective of the current study is to characterize NPM patients and examine the determinants associated with NPM severity.
Method
This study analyzed the NPM inpatients admitted to the Department of Breast Surgery, Longhua Hospital Affiliated with Shanghai University of Traditional Chinese Medicine from 2016 to 2020. We explored NPM patient characteristics through demographics, physical risks, lab tests, and medical history indicators. Multivariable logistic regression was conducted to identify the relationship between the prolactin (PRL) level and NPM severity stratified by breast structure.
Result
The majority of NPM inpatients had normal breast structures and were of lower average age than those with congenital nipple deformity (p = 0.002). Significant positive risk (p < 0.001) association between PRL level and NPM severity was observed among NPM inpatients with normal breast structure in both crude and adjusted model(adjusted OR: 2.91; 95%CI:1.88–4.52), with age as a protective factor (OR:0.94; 95%CI:0.91–0.97) and smoking history as a risk factor(OR:2.22; 95%CI:1.22–4.05). For NPM patients with nipple deformity, increasing odds of NPM severity regarding higher PRL level was observed while the result is not statistic significant at 0.05 level. (OR: 2.17; 95%CI: 0.94–5.03; p = 0.076).
Conclusion
The risk of NPM severe episodes is higher among patients with higher PRL levels, of which the association is stronger for NPM patients with normal breast structure, implying different pathogenesis between NPM patients with varied breast anatomy. Disagreement of the interaction effect testification indicates an improvement window for current study.
Trial registration
ChiCTR2000035929. Registered 20 August 2020(retrospectively registered).
Neurocognitive Dynamics and Behavioral Differences of Symmetry and Asymmetry Processing in Working Memory: Insights from fNIRS
Authors: Sztuka Izabela Maria , Kühn Simone 
Published: February 2024

Abstract

Symmetry is a ubiquitous property of the visual world. It facilitates cognitive processing and fosters aesthetic appeal. Despite its importance to aesthetic experience and perceptual prominence, the integration of symmetry in working memory remains underexplored. In our study, participants engaged in working memory delayed matching to sample task involving both symmetrical and asymmetrical stimuli, while their brain activity was monitored using functional Near Infrared Spectroscopy (fNIRS). The study revealed that symmetry significantly enhances memory performance. Symmetry significantly improves task performance, with symmetrical stimuli leading to higher accuracy and faster recall than asymmetrical ones, especially under high cognitive load. This effect varies with the type of symmetry, with diagonal symmetry being the most effective. Neuroimaging data showed distinct brain activation patterns when participants processed symmetrical stimuli, particularly in the memory-straining condition. Significant differences in brain activity were observed in various brain regions, with lateral occipital, posterior parietal, medial and dorsolateral prefrontal cortices reacting to symmetry with decreased oxygenated hemoglobin (HbO), while in left orbitofrontal (HbO) and right ventrolateral prefrontal cortex (HbO and HbR) hemoglobin concentration increased. Overall, our findings highlight the complex, region-specific brain activation patterns in response to visual symmetry, emphasizing the nuanced role of symmetry in cognitive processing during memory tasks and their potential implication for creative thinking.
Full Field Optical Coherence Tomography (FFOCT) to analyze prostate biopsy core in-office: a new step to real-time cancer diagnosis
Authors: ANRACT Julien , CHEN Weihua , DUQUESNE Igor , SIBONY Mathilde , DELONGCHAMPS Nicolas BARRY 
Published: February 2024

Abstract
BACKGROUND Focal therapy for prostate cancer is rising. One of the actual challenge is the management of the margins. A real-time cancer diagnosis device could be a useful tool to control margins during focal therapy. Full Field Optical Coherence Tomography (FFOCT) is a recent technique to analyze tissue in real time. The aim of our study was to assess the accuracy of FFOCT in prostate cancer diagnosis on biopsy cores by urologists.
METHODS 91 patients undergoing prostatic biopsies were included. Among these patients, we randomly selected 991 biopsy cores for the FFOCT analysis. FFOCT images were analyzed by two urologists and two urology residents, blinded for the results of the standard histological analysis (gold standard). The FFOCT analysis included the presence of prostate cancer, and clinically significant prostate cancer (ISUP≥2). Results were compared to the histological analysis.
RESULTS All the 991 cores were analyzed. Among them, 236 cores (23,7%) were positive for prostate cancer and 37 cores (3,7%)for clinically significant prostate cancer (csPCa). Global accuracy was 86,9% for csPCa. Global negative predictive value (NPV) was 97,5% for csPCa. Reproducibility between readers was K= 0,46 (IC95%[0,37 – 0,48]).
CONCLUSIONS Our results confirmed that FFOCT is feasible and accurate to eliminate prostate cancer on biopsy cores (NPV=97,5%). Further studies should evaluate FFOCT for framing biopsies during focal therapy procedures.
Genome-wide identification of the SAUR gene family and screening for SmSAURs involved in root development in Salvia miltiorrhiza
Authors: Wang Wei , Zheng Yuwei , Qiu Lin , Yang Dongfeng , Zhao Ziyang , Gao Yuanyuan , Meng Ru , Zhao Hongguang , Zhang Shuncang 
Published: February 2024

Abstract

Salvia miltiorrhiza is a widely utilized medicinal plant in China. Its roots and rhizomes are the main medicinal parts and crucial in determining the quality of the herb. Previous studies reveal that auxin plays pivotal roles in S. miltiorrhiza root development. As the crucial early auxin-response genes, whether small auxin-up RNA genes (SAURs) are involved in the auxin-mediated root development in S. miltiorrhiza is worthy of investigation. In this study, 55 SmSAUR genes in S. miltiorrhiza were identified and their physical and chemical properties, gene structure, cis-acting elements, and evolutionary relationship were analyzed. The expression levels of SmSAUR genes in different organs of S. miltiorrhiza were detected by RNA-seq combined with qRT-PCR. The root development of S. miltiorrhiza seedlings was altered by the application of indole-3-acetic acid (IAA) and Pearson correlation coefficient analysis was conducted to screen SmSAURs that potentially participate in this physiological process. As the results shown, the diameter of primary lateral root was positively correlated with SmSAUR4. The secondary later root number was positively correlated with SmSAUR18 and negatively correlated with SmSAUR4. The root length showed a positive correlation with SmSAUR28 and SmSAUR37 and a negative correlation with SmSAUR38. The root fresh biomass exhibited a positive correlation with SmSAUR38 and a negative correlation with SmSAUR28. The SmSAURs mentioned above were probably involved in the auxin-mediated root development in S. miltiorrhiza. Our study presents a comprehensive overview of SmSAURs and establishes the groundwork for elucidating the molecular mechanism underlying root morphogenesis in this species.
N6-methylandenosine-related lncRNAs have the prognostic predictive ability for patients with Endometrial Cancer
Authors: She Jiajie , Shuai Ling , Su Danna , Ye Xiaofeng , Liu Xuemin , Li Dongdong , Diao Ruiying , Guo Yan 
Published: February 2024

Abstract
Endometrial carcinoma (EC) is the fourth most common cancer with increasing morbidity and mortality in recent years. Therefore, it’s urgent and crucial to identify potential reliable biomarkers as useful therapeutic targets for the prognosis of EC patients. In this study, we screened 1,560 m6A-related lncRNAs through Pearson correlation coefficient based on the Cancer Genome Atlas (TCGA) datasets and the GENCODE annotation. Based on the univariate Cox regression analysis, we identified 187 m6A-related lncRNAs related to the prognosis of EC patients. Based on the LASSO Cox analysis, twelve m6A-related prognostic lncRNAs were used to construct a m6A-related lncRNA prognostic signature (m6A-LPS). Our results indicated that the m6A-LPS had a robust prognostic ability and the constructed nomogram (based on m6A-LPS, age, and pathological grade) had great ability to predict the OS of EC patients. Through comparing the differences of tumor-infiltrating immune cells between high-risk and low-risk groups (based on the median value of risk score), we found that EC patients in low-risk group had higher immune cell infiltration and lower tumor purity. Furthermore, we constructed a competing endogenous RNA (ceRNA) network which was used to reveal potential function of those m6A-related prognostic lncRNAs. In general, we established the m6A-LPS, which had stable and robust ability to predict the OS of EC patients. Our study might contribute to the identification of reliable biomarkers as therapeutic targets for the prognosis of EC and provide novel insights into the mechanism of pathogenesis of EC.
Potential of Niacin Skin Flush Response in adolescent Depression Identification and Severity Assessment : A Case-Control Study
Authors: Feng Jie , Min Wenjiao , Wang Dandan , Yuan Jing , Chen Junming , Chen Lisha , Chen Wei , Zhao Meng , Cheng Jia , Wan Chunling , Zhou Bo , Huang Yulan , Zhang Yaoyin 
Published: February 2024

Abstract
Background
The diagnosis of adolescent Depressive Disorder (DD) lacks specific biomarkers, posing significant challenges. This study investigates the potential of Niacin Skin Flush Response (NSFR) as a biomarker for identifying and assessing the severity of adolescent Depressive Disorder, as well as distinguishing it from Behavioral and Emotional Disorders typically emerging in childhood and adolescence(BED).
Methods
In a case-control study involving 196 adolescents, including 128 Depressive Disorder, 32 Behavioral and Emotional Disorders, and 36 healthy controls (HCs), NSFR was assessed. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9) and anxious symptoms with the Generalized Anxiety Disorder 7-item scale (GAD-7). Pearson correlation analysis determined the relationships between NSFR and the severity of depression in DD patients. Receiver Operating Characteristic (ROC) was used to identify DD from BED integrating NSFR data with clinical symptom measures.
Results
The adolescent Depressive Disorder group exhibited a higher rate of severe blunted NSFR (21.4%) compared to BED (12.5%) and HC ( 8.3%). Adolescent Depressive Disorder with psychotic symptoms showed a significant increase in blunted NSFR (p = 0.016). NSFR had negative correlations with depressive (r = -0.240, p = 0.006) and anxious (r = -0.2, p = 0.023) symptoms in adolescent Depressive Disorder. Integrating NSFR with three clinical scales improved the differentiation between adolescent Depressive Disorder and BED (AUC increased from 0.694 to 0.712).
Conclusion
NSFR demonstrates potential as an objective biomarker for adolescent Depressive Disorder, aiding in screening, assessing severity, and enhancing insights into its pathophysiology and diagnostic precision.
Dynamic Q-planning for Online UAV Path Planning in Unknown and Complex Environments
Authors: Rocha Lidia Gianne Souza da , Caldas Kenny Anderson Queiroz , Terra Marco Henrique , Ramos Fabio , Vivaldini Kelen Cristiane Teixeira 
Published: February 2024

Abstract
Unmanned Aerial Vehicles need an online path planning capability to move in high-risk missions in unknown and complex environments to complete them safely. However, many algorithms reported in the literature may not return reliable trajectories to solve online problems in these scenarios. The Q-Learning algorithm, a Reinforcement Learning Technique, can generate trajectories in real-time and has demonstrated fast and reliable results. This technique, however, has the disadvantage of defining the iteration number. If this value is not well defined, it will take a long time or not return an optimal trajectory. Therefore, we propose a method to dynamically choose the number of iterations to obtain the best performance of Q-Learning. The proposed method is compared to the Q-Learning algorithm with a fixed number of iterations, A*, Rapid-Exploring Random Tree, and Particle Swarm Optimization. As a result, the proposed Q-learning algorithm demonstrates the efficacy and reliability of online path planning with a dynamic number of iterations to carry out online missions in unknown and complex environments.